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How Sky Achieved an 87 NPS and Readied Inclusive Leadership Roleplays for 2,000 Employees with Yoodli
TL;DR
Sky is one of the UK’s largest media and entertainment companies, with about 30,000 employees. Above all, it wanted its inclusive leadership training to do more than teach theory. Employees learned how to disagree well and handle difficult conversations. However, using those skills in a real conversation still felt daunting.
So Sky’s D&I Learning & Advisory team built three Yoodli roleplays: Workplace Adjustments, Disagreeing Well, and Mid-Year Review. Then the team tested them with representative colleague groups, and Yoodli scored inclusive behaviors in every session. As a result, the pilot earned an NPS of 87 across 21 survey responses. In addition, every test group gave strongly positive feedback. Testers also found zero critical issues, and users felt more confident before real conversations. Consequently, Sky has approved all three scenarios for Sky Learn. They will launch to about 2,000 employees in Sky’s Inclusive Leadership Programme.
The Challenge: Turning Inclusive Leadership Training Into Practice
In Sky’s People team, the D&I Learning & Advisory function builds programs that grow inclusive behaviors across the business. One of these is Sky’s internal Inclusive Leadership program.
This inclusive leadership training gave employees strong foundations. For example, it taught them how to have a difficult conversation, how to disagree well, and how to lead inclusively. Still, knowing the theory and using it in the moment are two different things.
After the course, employees had to walk into a real conversation with their manager and apply what they learned. For most people, that first real attempt still felt intimidating. In other words, the program lacked a safe space to practice before the stakes were real.
Sky also doesn’t take tools off the shelf. Instead, any solution had to prove three things. First, it had to be fit for purpose. Second, it had to work for any type of difficult conversation. Finally, it had to justify its cost over cheaper tools with fewer capabilities.
“A lot of programs will give you the theory, here’s how you have a difficult conversation, here’s how you disagree well. It’s a brilliant course, but the ability to take those learnings and put them into practice in real life is still quite daunting. Having a safe space to practice what we’re teaching was needed, and Yoodli really plugged that gap.” – Wesley Lewin, Group D&I Learning & Advisory Manager, Sky
The Solution: A Pilot-First Path to Inclusive Leadership Training
Building and testing the pilot
Sky started with a structured test-and-learn pilot. First, the D&I team built three Yoodli roleplays. The team matched each one to a representative colleague group and a real workplace conversation. Then it used surveys and listening groups to assess five areas: user experience, scenario realism, learning impact, confidence building, and readiness for deployment.
Test group Scenario Sky Disability Community Workplace Adjustments Home Service Disagreeing Well Performance Sprint Team Mid-Year Review The formula: Inclusive leadership training content + customized Yoodli AI roleplays for any difficult conversation + inclusive behavior evaluation in every scenario.
How it works: No matter how Sky customizes a roleplay, every session gives users feedback on their inclusive behaviors. For example, it shows how well they communicated and how well they recognized intent versus impact. Users practice, review their coaching, and try again. As a result, they build confidence before the real conversation.
Refining before rollout
Participants’ suggestions focused on enhancements, not barriers to adoption. Together, Sky and Yoodli made five refinements. They slowed conversation pacing to give users more thinking time. They also improved onboarding guidance and personalized scenario content. In addition, they smoothed dialogue flow and shifted feedback emphasis away from scores. Ultimately, the team made every recommended change before rollout.
The pilot answered Sky’s two questions. Is it great? Yes. Is it worth it? Yes. Because of this, the D&I team had the evidence to secure leadership buy-in and move to wider deployment.
From pilot to champion
Today, Wesley champions Yoodli across the business. For example, he demos it at town halls and shares a short clip of himself practicing with a notably awkward AI manager. It always gets a laugh.
“The more you use it, the more you practice. If you practice a difficult conversation, you take the feedback, you do it again, you are so much more equipped and feel more confident when you actually have it in real life.” – Wesley Lewin, Group D&I Learning & Advisory Manager, Sky
Why Yoodli for Inclusive Leadership Training
Sky evaluated other options for its inclusive leadership training. However, those tools lacked Yoodli’s depth of coaching, analysis, and customization. Therefore, that combination made Yoodli worth the investment over cheaper, less capable alternatives.
Key advantages of Yoodli for Sky:
- Fully customizable roleplays: They fit any type of difficult conversation, a broad use case other tools couldn’t match.
- Realism: Fast responses and natural conversation mean users quickly forget they’re talking to an AI.
- Instant, actionable coaching: After every attempt, users get a one-paragraph summary of strengths and areas to develop.
- Delivery analytics: Yoodli tracks filler words, repeated words, pauses, and pacing [link: Yoodli analytics or feedback feature page]. In other words, users get feedback on how they speak, not just what they say.
- Inclusive behavior scoring: Every roleplay includes it, so Sky can measure D&I outcomes in any scenario.
“I tell people all the time how good it is, but I let them find out for themselves. Jump in, use it yourself, and the feedback is always, this is brilliant. You can see people thinking, we could use it for this, we could use it for that.” – Wesley Lewin, Group D&I Learning & Advisory Manager, Sky
Impact
Pilot results
All three test groups gave strongly positive feedback:
Metric Result Net Promoter Score 87 across 21 survey responses Scenarios tested 3 roleplays with 3 representative colleague groups Critical issues 0; Sky and Yoodli made every recommended improvement Confidence Users felt more confident before real-life conversations Inclusive behavior scores Rose with repeated attempts Deployment Sky approved all 3 scenarios for Sky Learn, launching to ~2,000 employees in the Inclusive Leadership Programme What participants said
Overall, participants said the conversations felt natural and adaptive. They also said the scenarios reflected real workplace situations and needed little support. In addition, they valued the specific examples in the feedback. Playback and analytics also helped them understand how they came across.
“It was much better than expected and felt more natural.” – Pilot participant, Sky
“Loved how fluid it was and easy to use.” – Pilot participant, Sky
What’s next for Sky’s inclusive leadership training
Next, Sky plans to expand its inclusive leadership training with new scenarios that match business priorities. For example, new scenarios will cover transformation, managing wellbeing, performance feedback, customer escalations, and influencing. Because every roleplay includes inclusive behavior scoring, Sky can track D&I outcomes as each new use case goes live. Finally, Sky will feature participants’ own advice in internal comms and on Sky Learn pages. Their tips: practice regularly, use playback and insights, and focus on progress over perfection.
“The one thing we’ve always sold is that the more attempts a user has, the more their inclusive behavior scores increase. For me, in my role and the purpose of why we even have Yoodli, that metric and that impact is there in the analysis, which is really good.” – Wesley Lewin, Group D&I Learning & Advisory Manager, Sky
“Just the measure of before and after the pilot gave us the answer, and it gave my director the ammo to say, yes, we should invest in this tool.” – Wesley Lewin, Group D&I Learning & Advisory Manager, Sky
Read more customer stories.
About Sky
Sky is one of Europe’s leading media and entertainment companies, serving millions of customers across the UK, Ireland and Italy. Part of Comcast Corporation, Sky brings customers the best in entertainment, sport, news and arts, alongside innovative TV, broadband and mobile services. Through our award-winning original content, world-class sports coverage and trusted journalism, we connect people to the stories, experiences and services they love. Guided by our belief in better, we’re committed to making a positive contribution to our customers, our communities and the world around us.
About Yoodli
Yoodli is a skills readiness platform that helps individuals and teams practice real-world conversations, presentations, and professional interactions through customizable AI roleplays and AI Tutors. Whether preparing for difficult conversations, leadership moments, sales calls, or certifications, users get targeted, real-time feedback to build confidence and improve communication. The Seattle-based company is trusted by Fortune 100 companies, leading training providers, and educational institutions to deliver scalable, judgment-free coaching across sales, leadership, customer success, and more. Learn more at yoodli.ai.
Want to see what Yoodli can do for your team? Contact: sales@yoodli.ai | yoodli.ai
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Build vs. Buy: AI roleplays in 20 minutes
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How to Improve First Call Resolution With Practice-Based Agent Training
First call resolution measures how often a customer’s issue gets solved on the first contact, with no callback, transfer, or follow-up ticket. Support leaders who want to improve first call resolution usually start with routing rules and knowledge base cleanup. Those help. The agent on the line is the bigger lever, and so is whether that agent has worked through the call before a customer is waiting on the other end.
This guide covers what FCR measures, why it moves customer satisfaction so directly, where unresolved calls come from, and how to build agent training that raises the number. It is written for contact center leaders, support enablement teams, and QA managers who own the metric.
What First Call Resolution Measures
The math is simple. Qualtrics gives the standard formula as resolved incidents on first contact divided by total incidents, times 100. The hard part is agreeing on what “resolved” means. Some teams use a post-call survey question. Some count a contact as unresolved if the same customer calls back within a set window, often seven days. Others rely on the agent’s disposition code, which tends to run high because agents mark calls closed when the customer hangs up satisfied in the moment.
Pick one definition and hold it steady. A repeat-contact window is the most honest of the three, because it catches the customer who thought the issue was fixed and found out later it wasn’t.
Benchmarks vary by industry. Qualtrics, citing SQM Group, puts the average call center’s first call resolution rate at about 70% to 79%, and lists complaint calls as the hardest type to resolve on first contact. Tech support and telecom run lower than retail. Compare yourself to your own baseline first and to industry numbers second.
Why FCR Moves Customer Satisfaction and Cost
FCR has one of the most direct links to customer satisfaction of any contact center metric. SQM Group’s research found that for every 1% improvement in FCR, there is a 1% improvement in customer satisfaction. The same research ties each 1% gain to a 1.4-point increase in transactional Net Promoter Score.
The cost side is just as clear. SQM’s 2012 research reports that 30% of customers have to call back because their issue was not resolved on the first call. It also reports that repeat calls represent 23% of the average call center’s operating budget. Every repeat call is a second handle time, a second queue wait, and a customer who now trusts the next answer a little less.
That makes FCR a useful north-star metric for a support training program. It rewards agents for solving the whole problem, and it shows up in both the CSAT report and the budget.
Where Unresolved Calls Come From
Most repeat contacts trace back to a short list of causes. Some sit outside the agent’s control, like a broken process or a policy that requires a second team. Many sit squarely inside it.
- Diagnosis. The agent solves the problem the customer described instead of the problem the customer has. A few more questions at the start of the call would have found it.
- Product and policy knowledge. The agent knows the answer exists but can’t find or recall it fast enough, so the call ends with a promise to follow up.
- Confirming resolution. The agent fixes the issue but never checks that the customer can complete the task on their own, so the customer calls back the next day.
- Setting expectations. A refund takes five business days, and nobody said so. The customer calls on day two.
- Emotion. An upset customer derails the call, and the agent spends the time calming them down instead of solving the issue.
Every one of these is a skill. Skills improve with repetition and feedback, which is why the training model matters as much as the content. SQM’s FCR best-practices research lists agent coaching among its top 10 practices for improving FCR, so the plan below puts coaching and feedback at the center.
How to Improve First Call Resolution Through Agent Training
The programs that raise FCR treat it as a set of behaviors agents can practice. Here is a sequence that works for new hire classes and for tenured teams.
Step What it involves 1. Start with repeat contacts Pull the call drivers behind repeat contacts and note where calls went sideways 2. Build practice scenarios Turn each driver into a realistic customer call agents can run by voice 3. Score resolving behaviors Score diagnosis, accurate answers, confirmed fixes, and clear next steps 4. Certify before live calls Agents pass scored mock calls before they take customers on their own 5. Practice the hard calls Calm angry or anxious customers and still solve the issue on the same call 6. Close the loop Compare practice scores with repeat-contact rates monthly, then write new scenarios Train agents on the behaviors that resolve calls the first time 1. Start with your repeat-contact data
Pull the top call drivers that generate repeat contacts. Ten drivers usually cover most of the volume. Listen to a handful of calls for each one and note where the first call went sideways. That list becomes your curriculum.
2. Turn each driver into a practice scenario
Write a scenario for each driver with a realistic customer, the details they share up front, and the details they only share if asked. AI roleplays let agents run these calls by voice as many times as they need, with a customer who reacts to what they say. A billing dispute where the real issue is a duplicate account only gets solved if the agent asks the right question.
3. Score the behaviors that resolve calls
Build a rubric around the FCR behaviors: diagnostic questions, accurate answers, confirmation that the issue is fixed, and clear next steps. Use the same criteria your call center quality assurance team uses on live calls, so practice scores and QA scores mean the same thing.
4. Certify before agents take live calls
Certification on mock calls is where many programs stall, because every mock call needs a manager to listen and grade it. RingCentral solved this with AI roleplays and saw a 90% reduction in call-center certification time. Managers spend their review time on the agents who need it instead of every call in the queue.
5. Practice the calls that go sideways
Emotional calls drag down FCR because agents lose the thread of the problem. Give agents reps on angry and anxious customers with a de-escalation training track, then return them to the original scenario so they practice calming the customer and solving the issue in the same call.
6. Close the loop with live-call data
Compare practice scores to repeat-contact rates by agent and by call driver each month. Yoodli Measure shows which skills are improving against your rubric. Your repeat-contact report shows which drivers still produce callbacks. Then write new scenarios for those drivers.
Practice Scenarios That Move FCR
Generic customer service scenarios teach generic skills. The scenarios that improve first call resolution are built from your own repeat-contact drivers. A few patterns show up in almost every contact center:
- A customer who already called twice and expects the agent to know the history.
- A technical issue where the first fix fails and the agent has to keep troubleshooting on the same call.
- A billing question that hides a second issue the customer hasn’t mentioned.
- A request that needs a policy exception, where the agent has to decide whether to approve it or escalate it.
- A multi-part call where the customer has three questions and only mentions the first one.
New agents need these during onboarding. Tenured agents need them when products, policies, or systems change. Our guide to call center agent training covers how to sequence them across the first 90 days.
How Yoodli Supports First Call Resolution Training
Yoodli gives support teams a place to practice real customer calls before they happen. Enablement teams build AI roleplays from their own call drivers and knowledge base, set the scoring rubric, and assign practice by team or by skill. Agents practice by voice and get feedback on each call right away. Managers see who is ready and who needs coaching.
Teams use it for customer support training across onboarding, product changes, and ongoing coaching. It also handles the step that slows most programs down, which is onboarding and certification at scale. For a closer look at scenario design, read how to use AI roleplay for customer support training.
Repeat contacts cost money and customer trust. Teams that improve first call resolution do it by giving agents practice on the calls that come back. If you want to see how a support team builds that practice into onboarding and coaching, talk to the Yoodli team.
FAQ
What is a good first call resolution rate?
The average call center resolves about 70% to 79% of calls on first contact, according to SQM Group figures cited by Qualtrics. The top of that range is a solid target. Retail tends to run higher, and tech support and telecom tend to run lower. Complaint calls are the hardest type to resolve on first contact. Track your own baseline by call driver and aim to raise it steadily from there.
How do you calculate first call resolution?
You calculate first call resolution by dividing the number of issues resolved on the first contact by the total number of issues, then multiplying by 100. Most teams define “resolved” with a repeat-contact window, such as no callback on the same issue within seven days. Post-call surveys and agent disposition codes are common alternatives.
What is the difference between first call resolution and first contact resolution?
First call resolution and first contact resolution measure the same outcome, and many teams use the terms interchangeably. First contact resolution is the broader name because it includes chat, email, and messaging as well as phone calls. If your support team works across channels, first contact resolution is the more accurate label for the metric.
How does training improve first call resolution?
Training improves first call resolution when agents practice the specific calls that generate repeat contacts. Effective programs build scenarios from real call drivers, score the behaviors that resolve issues, and certify agents before they take live calls. Repetition with feedback builds diagnosis, product knowledge, and expectation-setting skills faster than classroom training alone.
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Partner Onboarding Process: How to Get New Partner Reps Selling Sooner
A partner onboarding process decides how quickly a new reseller, referral partner, or systems integrator can put your product in front of a customer and describe it well. Most vendors put real effort into recruiting partners. The first 60 to 90 days after the agreement is signed often get less attention, and that is the window where partner reps form their habits for selling your product.
The stakes are high. Omdia expects partners to account for 66.7% of the total addressable IT market in 2026, according to its analysis of channel spending trends. When two-thirds of the market flows through partners, the quality of partner conversations becomes a direct input to your own revenue.
This guide covers what a strong partner onboarding process includes, how to structure the first 90 days, where practice fits, and how to measure partner readiness. It is written for partner and channel enablement teams, alliance managers, and the revenue leaders who rely on partner-sourced pipeline.
What Is a Partner Onboarding Process?
A partner onboarding process is the structured path a new partner organization and its reps follow from signed agreement to first qualified opportunity. It usually covers four layers: business setup, product knowledge, the sales motion, and certification.
Business setup includes portal access, deal registration rules, pricing authority, and co-selling expectations. Product knowledge covers what the product does, who buys it, and how it compares with alternatives. The sales motion layer teaches partner reps how your best sellers run discovery, position value, and handle objections. Certification confirms that a partner rep can deliver the pitch to a clear standard before taking it to customers.
Most programs handle the first two layers well. Portals and content libraries are good at distributing information. The last two layers take more work because they depend on spoken skill, and spoken skill improves through practice and feedback.
Why Channel Partner Onboarding Needs Its Own Playbook
Internal onboarding and channel partner onboarding look similar on paper. In practice, partner reps work under very different conditions than your own sellers.
Partner reps split their attention across many vendors. A reseller rep might carry a dozen product lines and sell yours a few times a quarter. You also don’t manage them directly, so you can’t require a weekly coaching session or join their calls. Partner organizations span time zones and languages, which makes live training sessions hard to schedule. And a large channel can include thousands of reps who all need the same baseline.
Memory works against occasional sellers too. Murre and Dros replicated Ebbinghaus’ forgetting curve in 2015 and confirmed the steep early drop in retention that Ebbinghaus first described. A partner rep who attends a launch webinar and then waits three weeks for a qualified conversation will have lost much of what they heard. The answer is short, repeatable practice that partners can return to right before the customer call.
Many teams already use AI roleplay for partner and reseller enablement so partner reps can rehearse the pitch on their own schedule, as often as they need.
How to Structure Your Partner Onboarding Process in 90 Days
A 90-day structure gives partners a clear path and gives your team checkpoints to review. Adjust the timing to your sales cycle and product complexity.
Phase What it covers 1. Setup and orientation Portal access, deal registration, named contacts and the use cases to lead with 2. Product and pitch fluency Short modules that each end in spoken practice of pitch, discovery and objections 3. Certification and first opportunities Certify reps on key conversations, then pair them with a partner manager Partner onboarding moves from setup to pitch fluency to certified selling Days 1 to 15: Setup and orientation
Get the partner organization operational. Confirm portal access, deal registration, and the named contacts on both sides. Share a short orientation that covers your ideal customer profile, the problems you solve, and the two or three use cases partners should lead with. Keep this phase light on content and specific about who to call for help.
Days 16 to 45: Product and pitch fluency
This is where partner training programs often run long. Break the material into short modules that each end in a spoken exercise. A partner rep should practice the core pitch, a discovery conversation, and the two objections they will hear most. Each practice round should produce feedback against the same standard your own reps are held to.
Days 46 to 90: Certification and first opportunities
Certify partner reps on the conversations that matter most, then support their first live opportunities. Pair each newly certified rep with a partner manager for the first deal review. Use what you learn from those early deals to update the practice scenarios for the next cohort.
Where AI Roleplays Fit in Partner Onboarding
AI roleplays give partner reps a realistic buyer to practice with at any hour, in their own time zone, without waiting for a manager or a partner account lead. With Yoodli, enablement teams can build this practice into the onboarding path directly.
A typical setup looks like this. The enablement team uploads the partner pitch deck and competitive positioning guide into Yoodli Create and generates a learning journey from a single prompt. The journey ends with an AI roleplay where the partner rep pitches to an AI buyer. For example, the buyer might be an IT director at a mid-market manufacturer who is already evaluating an alternative. The AI buyer asks follow-up questions, raises objections, and responds to what the rep actually says.
Every attempt in Yoodli Roleplays is graded against a rubric the vendor defines. A rubric for a partner pitch might check three things:
- Whether the rep named the three core use cases.
- Whether the rep asked at least two discovery questions before pitching.
- Whether the rep handled the pricing objection without offering a discount.
The rep sees the score and specific feedback right away, then tries again.
Global channels need practice in more than one language. Yoodli supports multi-language AI roleplays across 25+ languages, so a reseller in Madrid and a systems integrator in Tokyo can each practice in the language they sell in. Programs can also live where partners already learn, since Yoodli lets you embed programs into your learning tools and website, including a partner portal.
Partner Certification: The Checkpoint That Protects Your Brand
Partner reps speak for your brand in rooms you will never see. Certification is how you confirm they are ready before they walk in. A good partner certification sets a clear pass standard, allows retries, and tests the specific conversations partners will have with customers.
The same approach works at very large scale. Google Cloud used Yoodli to roll out a new GTM pitch certification to 15,000+ employees, as described in the Google Cloud pitch certification case study. Partner programs can apply the same model of a defined pitch, a scored rubric, and a certification gate to their channel.
Keep certification current. Recertify partner reps when you launch a major product, change pricing, or reposition against a competitor. Short recertification rounds keep the bar consistent without forcing partners back through the full onboarding path. Yoodli’s onboarding and certification use case shows how teams structure these checkpoints.
How to Measure Partner Readiness
Partner onboarding should produce data you can act on, both for your team and for partner leaders. These are the metrics most enablement teams track:
- Time to certification: days from signed agreement to the first certified rep at each partner.
- Certification pass rate and attempts: how many tries reps need, which shows where the content or the scenario needs work.
- Rubric scores by skill: which parts of the pitch partners deliver well and which they skip.
- Time to first registered deal: the clearest signal that onboarding turned into selling.
- Partner-sourced pipeline per certified rep: the link between readiness and revenue.
Yoodli Measure shows progress across programs and against rubrics, by learner, by team, and by program. Partner managers can bring that view into business reviews and show each partner exactly where their reps stand.
What Strong Partner Onboarding Programs Do Differently
The best partner onboarding programs share a few habits. They keep modules short and end each one with a spoken exercise. They write scenarios for each partner type, because a referral partner, a reseller, and a systems integrator have very different conversations. They give partner managers visibility into practice scores so coaching conversations start from evidence.
They also treat onboarding as the start of ongoing partner enablement. Each launch adds a new practice scenario, and each quarter’s deal feedback improves the next cohort’s training. Gartner found that 67% of B2B buyers prefer a rep-free experience, so the conversations buyers do choose to have with a partner rep need to deliver clear value. Practice is how partner reps get there.
For a broader view of how vendors run channel programs with practice built in, see Yoodli’s partner enablement solution.
To see how a partner onboarding process with AI roleplays, certification, and readiness data could work for your channel, talk to the Yoodli team.
FAQ
What should a partner onboarding process include?
A partner onboarding process should include business setup, product training, sales motion practice, and certification. Setup covers portal access and deal registration. Product training explains use cases and positioning. Practice lets partner reps rehearse the pitch, discovery, and objections. Certification confirms each rep can deliver the conversation to your standard before meeting customers.
How long does partner onboarding take?
Partner onboarding usually takes 60 to 90 days from signed agreement to first certified reps and first registered opportunity. Simple referral programs can move faster. Complex products with technical sales cycles may need longer. A phased plan with clear checkpoints at day 15, day 45, and day 90 helps both sides track progress and spot partners who need more support.
How do you certify channel partners at scale?
You certify channel partners at scale by defining a scored rubric for the pitch and testing every rep against it with AI roleplays. Reps practice and attempt certification on their own schedule, in their own language. Scores stay consistent across thousands of reps, and partner managers can review results without grading every attempt by hand.
How is partner onboarding different from partner enablement?
Partner onboarding is the first phase of partner enablement. Onboarding gets a new partner from signed agreement to first certified reps and first opportunity. Partner enablement is the ongoing work after that, including launch training, recertification, deal support, and coaching. A strong onboarding process sets the habits and standards that ongoing enablement builds on.
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AI Mock Sales Calls: A Buyer’s Guide for Enablement Teams
AI mock sales calls are practice conversations in which a rep works through a real selling moment with an AI buyer, then gets scored against the team’s own rubric. The right platform lets you build those buyers and scenarios from your own deals, run practice for every rep at once, and see who is ready before the live call.
Enablement leaders are paying attention because ramp keeps getting longer. The Bridge Group’s 2026 study of 158 B2B companies put average AE ramp time at 6.2 months, the highest in the study’s history. The same study found 48% of reps at quota, down from 51% in 2024.
Source: The Bridge Group, 2026 AE Models, Motions and Metrics This guide is for sales enablement, RevOps, and L&D leaders who are comparing AI practice call platforms and planning a program. We build Yoodli, the AI Platform for Human Skills, so we use it as the worked example and say so when we do.
What Are AI Mock Sales Calls and How Do They Work?
An AI mock call is a spoken practice conversation between a rep and an AI buyer with a role, priorities, and objections of its own. The rep runs the conversation in real time, and the platform scores it against a rubric as soon as it ends.
Three inputs decide whether the practice feels real. The scenario sets the moment, such as a cold call opener, a first discovery call, or a pricing conversation with procurement. The buyer persona sets the pressure: how skeptical the buyer is, which objections come up, and how much the buyer reveals without being asked. The rubric turns the conversation into feedback a rep can use on the next attempt.
In Yoodli Roleplays, reps practice by video, chat, or avatar, and every attempt is scored against your rubric. Yoodli Personas sets each AI buyer’s appearance, voice, and context, so the buyer a new AE meets in week one sounds like the buyers in your pipeline. Reps see feedback right away and can run the same call again that afternoon. Managers see results across the team and spend review time on the attempts that need a human ear.
Why Do Sales Teams Use AI Practice Calls?
Sales teams use AI practice calls because reps keep more of what they learn when they have to use it. AI also lets every rep practice without waiting for a manager to play the buyer.
Curriculum-based training on its own fades fast. Frank Cespedes and Yuchun Lee make this case in an article listed on Harvard Business School’s faculty site. They cite studies showing that participants in traditional curriculum-based training forget more than 80% of the information they were taught within 90 days. They recommend giving reps chances to practice in time frames connected to real buying processes.
Enablement teams already lean on practice. The Association for Talent Development surveyed professionals at 71 organizations for its 2023 State of Sales Training. Scenario-based learning was the top method for making sales training engaging and interactive, at 69 percent. The same report found that 65 percent of high-performing organizations used non-technology practice such as in-person roleplays, compared with 39 percent of other organizations.
In-person practice depends on a manager or peer being free to play the buyer, so reps often get only a few turns. AI removes that limit. Forrester’s Peter Ostrow reports that high-performing reps are four times more likely to use AI roleplay. A new hire who has run a dozen discovery calls against a skeptical AI buyer starts the first live call with a structure for questions, objections, and next steps.
What Are the Best AI Practice Call Tools for Sales Teams?
The best AI practice call tool for a sales team scores practice against your own rubric and lets you build scenarios from your own deals. It also reaches every rep in the systems they already use. Vendors cover different slices of that, so start with what each one was built to do.
We start with Yoodli, our own platform, which has more than 1 million users and runs more than 3 million minutes of AI roleplay every month. The tools below are not ranked. Capabilities come from vendor pages and help centers, and review themes come from G2 as of October 2026.
Tool Platform type Built for Watch-outs Yoodli The AI Platform for Human Skills, end to end. Company-wide programs in sales, partners, support, and L&D. More platform than a handful of reps needs. Outdoo Revenue intelligence platform with roleplay. Sales, customer success, and service teams. G2 reviewers report inconsistent grading. Build It Yourself on Claude General-purpose AI model. Teams with engineering time. Scoring, tracking, LMS packaging, and security review are yours to build. Second Nature Point solution for AI roleplay delivered through the LMS. Sales and service teams. G2 reviewers report a steep learning curve. Hyperbound Point solution for sales roleplay and call scoring. SDR and AE teams. It covers sales roles only, and G2 reviewers report call lag. Mindtickle All-in-one revenue enablement suite. Revenue and support teams on one suite. G2 reviewers report about two months to implement. Avarra Point solution for avatar roleplay on Zoom. Sales teams. It does not publicly document LMS delivery or programs outside sales. Gong Conversation intelligence with a roleplay feature. Revenue teams that record calls in Gong. It depends on Gong as the recorder. If one of the point solutions is already on your shortlist, our Yoodli vs. Hyperbound comparison and Yoodli vs. Second Nature comparison walk through the differences for enterprise programs.
Which AI Mock Call Platforms Offer Customizable Sales Scenarios?
Look for a platform where your own team can write the scenario, build the buyer, and set the rubric, with no vendor ticket for each change. That control keeps practice close to your product and to the buyers your reps meet.
Test customizable sales scenarios on your own material during the demo. Ask the vendor to build a scenario from this quarter’s pitch and the objections your reps keep hearing. Then have it set up AI buyer personas that match a real account by role, industry, and temperament. The rubric should follow the framework your team sells with, whether that is BANT, MEDDPICC, Sandler, Challenger, or criteria your managers wrote.
Here is how an enablement team might set up AI mock calls by deal stage in Yoodli. A cold call scenario uses a busy AI buyer who gives the rep about thirty seconds before pushing back. A demo call uses two-way screen share, so the rep presents while the AI buyer asks about what is on the screen. A late-stage call brings in a buying committee of AI personas, such as a CFO and an IT lead, who talk to each other as well as to the rep. Reps who sell alongside a solutions engineer can practice in multiplayer mode, with a live teammate on the call.
Google Cloud built its pitch certification on this kind of customization. The enablement team wrote Google Cloud scenarios and objections, created custom rubrics for the AI to grade against, and set the talking points every learner had to hit. Google Cloud certified 15,000+ employees on a new GTM pitch at 92% training CSAT.
Which AI Mock Call Tool Is Suitable for Scalable Call Practice?
A tool built for scalable call practice runs your whole sales org at once and scores every attempt the same way. Leaders see who is ready without anyone grading calls by hand. Test it against your real team size and your busiest launch week.
Scale shows up in a few places. Scoring has to be automated and consistent, or managers end up regrading calls. Look for LMS delivery through SCORM or LTI, plus a web embed for portals, so practice reaches reps where they already learn. Global teams need feedback in their own language, and Yoodli supports 25+ languages. Admins need provisioning and guardrails, and Yoodli runs programs of 100,000+ learners.
Snowflake moved pitch and objection-handling practice to Yoodli for its global sales org, with rubric-based feedback in each rep’s native language. The program eliminated ~1,215 hours of manual grading per quarter and saved an estimated $170K quarterly.
Mock call certification works the same way outside sales. RingCentral’s onboarding team used to certify new support agents by having managers observe and grade each mock call. With Yoodli AI roleplays, RingCentral cut support call certification time by 90%, from nine hours to one hour per agent.
What Trusted AI Practice Call Solutions Are Available for Sales Organizations?
A trusted solution passes your security review and explains how it handles call recordings and customer data. It should also have published results from companies like yours. Send the security questionnaire when the pilot starts, so a strong pilot does not stall in review.
Most established vendors in this category publish a SOC 2 Type 2 report, so ask the follow-up questions that tell them apart. Does the vendor train AI models on your practice calls? Do its AI model and speech providers keep your data? Does it support SSO and SCIM provisioning? Can admins set how long recordings are kept?
Yoodli has a SOC 2 Type 2 report issued in July 2026, a SOC 3 report, and GDPR and EU AI Act compliance, with documentation on its Trust Center. Yoodli never trains AI models on customer data, and every AI model and speech provider it uses is held to zero data retention. Admins get SSO, SCIM provisioning, and retention settings of up to 365 days.
How Do Leading AI Practice Call Platforms Compare? Use This Demo Checklist
Compare platforms on the work your team will do with them: building scenarios, scoring against your standard, delivering practice where reps work, and reporting readiness. Bring one real scenario and your rubric to every demo, and ask each vendor to run it live.
- Can our enablement team build a scenario from our own pitch and objections without the vendor’s help?
- Can we load our rubric, weight each criterion, and see which part of the call earned each score?
- Can the AI buyer react to a shared screen, and can several AI personas join one call?
- Can a live teammate, such as a solutions engineer, join the practice call?
- Does practice run inside our LMS through SCORM or LTI, or embed in our sales portal?
- Can leaders see readiness by rep, team, and program?
- How long does a rollout to every rep take, and what happens between contract and go-live?
- Does the vendor train AI models on our data, and which of its providers keep it?
Score each vendor on the same scenario with the same rubric, so the comparison is fair. With Yoodli, roleplays take minutes to build, and enterprise go-live takes about three weeks, including integrations and testing.
How to Run Your First AI Mock Sales Calls Program
Start with one audience, one selling moment, and one rubric. Run a four to six week pilot with a named owner, and expand once the first cohort’s scores move.
- Pick the audience and the moment. New hires preparing for their first discovery calls are a common first cohort.
- Write the rubric with your strongest managers. Keep it to five or six behaviors you can hear in a conversation, and use our guide to building a sales call scorecard for structure.
- Build two or three scenarios and a small set of buyer personas from real objections in your pipeline.
- Set a cadence of short sessions spread over several weeks. Our guide on how often reps should complete roleplay practice gives a starting schedule.
- Share early results with managers, starting with the criteria where the cohort scores lowest.
- Review the pilot against one business measure, such as certification time, time to first deal, or conversion at the stage you practiced.
How you space the sessions matters. Kauffeld and Lehmann-Willenbrock compared spaced and massed sales training in a field study of 64 bank employees. They found that “spaced rather than massed training practice resulted in greater transfer quality, higher self-reports of sales competence, and improved key figures”.
Loopio’s three-person enablement team followed this pattern for demo certification. Reps read a short playbook, watched a recorded demo, and then worked with an AI tutor that taught the demo flow and tested them on objections in the same session. Loopio cut demo certification attempts by 67% and certified 60 reps.
How to Measure Whether AI Mock Sales Calls Change Results
Track participation, rubric scores over time, and one business outcome your leaders already watch. Completion data shows who practiced, and the trend in scores over several weeks tells you whether practice is working.
Start with the skill data. Look at score trends by rep, team, and criterion. If a cohort’s discovery scores rise from the first attempt to the fifth, the practice is working on that skill. A criterion that stays flat shows managers where to coach. Yoodli Measure shows progress by learner, team, and program against your rubrics, so enablement and RevOps work from the same view.
Then connect the skill data to outcomes in the reports you already run. Compare cohorts that practiced with cohorts that did not on ramp time, certification time, and conversion at the stages you practiced.
Real calls close the loop. For teams on Gong or Kaia, Yoodli Coach gives post-call coaching on recorded calls and suggests what to practice next. A gap that shows up in a live deal becomes the rep’s next mock call. Review the highest and lowest scoring calls with managers each month. They make good coaching material, and they show where the rubric needs tuning.
FAQ
What are AI mock sales calls?
An AI mock call is a spoken practice conversation between a sales rep and an AI buyer built to act like a real prospect. The buyer has a role, priorities, and objections, and the platform scores the rep against the team’s rubric when the call ends. Reps get feedback within minutes and can repeat the call before a live deal.
What are the best AI practice call tools for sales teams?
The best AI practice call tool for your team scores reps against your own rubric, supports custom scenarios and buyer personas, and scales to every rep. Buyers often compare Yoodli, Outdoo, Second Nature, Hyperbound, Mindtickle, Avarra, and Gong, and each was built for a different scope. Bring the same scenario and rubric to every demo to compare them fairly.
How often should reps do AI mock sales calls?
Short sessions spread over several weeks work better than one long session. A field study of bank sales training found that spaced practice produced greater transfer quality than massed practice. Many teams schedule a few mock calls a week during onboarding, then a lighter cadence tied to launches, new messaging, and the skills with the lowest scores.
How do AI mock sales calls work with manager coaching?
AI practice calls give managers more time for the coaching that needs their judgment. Reps handle the repetition on their own, and managers review the calls that matter most, such as a stalled deal or a rep whose scores are flat. The AI scores every attempt the same way, so each coaching conversation starts from the same evidence.
Start With One Scenario
Pick the selling moment that costs your team the most deals, build one scenario around it, and run it with one cohort before you scale. To see AI mock calls built from your own pitch, personas, and rubric, talk to our team.
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Customer Success Enablement: How to Build a Program CSMs Use
Customer success enablement is the work of preparing CSMs to run the conversations that keep and grow customers. That includes kickoffs, adoption check-ins, business reviews, renewals, and the hard calls when an account is at risk. Many enablement programs are built for new business sales, so CS teams often learn these conversations on the job, in front of the customer.
This guide covers why CS teams need their own enablement program, which conversations to build it around, and how to structure training, certification, and ongoing practice so CSMs stay ready.
What is customer success enablement?
Customer success enablement gives CSMs the knowledge, skills, and practice they need to drive adoption, show value, and secure renewals. It covers product knowledge and process, but the hardest part is the conversation layer. A CSM can know every feature and still struggle to tell an executive sponsor that adoption is behind plan.
Demand for this work has been building for years. A 2022 Gainsight Pulse session covered world-class enablement for customer success teams. Its description notes that “Effective training for Customer Success teams has been the #1 inquiry for 2 years running” in TSIA’s Customer Success practice.
Why CS teams need their own enablement program
Revenue leaders are putting more weight on existing customers. A Gartner survey of 243 CSOs and senior sales leaders found that 73% of CSOs are prioritizing growth from existing customers for 2025. That growth runs through conversations CSMs lead.
At the same time, CS teams are expected to prove the value they create. TSIA’s State of Customer Success 2025 summary describes the challenge directly: “Customer Success teams are under increasing pressure to prove value but often lack the tools and metrics to demonstrate business impact.”
Sales enablement programs rarely fit this need. A sales program trains reps to open opportunities and close them. A CSM’s conversations are longer-running and more varied. The same CSM may run an onboarding call in the morning, a technical escalation at lunch, and an expansion discussion in the afternoon. Customer success enablement has to prepare people for all of it.
The conversations to build the program around
Start with the moments in the customer lifecycle where a strong conversation changes the outcome. For most CS teams, that list looks like this.
- Kickoff. The first meeting sets expectations, success criteria, and the working relationship. Our customer kickoff meeting guide covers the agenda and prep.
- Adoption check-ins. These calls catch low usage early and turn it into a plan the customer agrees to.
- Business reviews. QBRs and executive reviews are where CSMs show value in the customer’s terms. See our post on QBR preparation for customer success managers.
- Renewals and expansion. These are the conversations with the clearest revenue impact. Our guide to renewal and expansion conversations covers how to practice them.
- Risk and escalation calls. A sponsor leaves, a key integration fails, or a budget gets cut. CSMs need to stay calm, own the plan, and keep the relationship intact.
- Sponsor changes. When a champion moves on, the CSM has to rebuild the relationship with someone new. Our post on finding and building a champion applies here as well.
Pick the three or four moments that matter most for your book of business and build there first. CSMs finish focused programs, and you can add more moments once the first ones are working.
How to structure a customer success enablement program
Onboarding: knowledge plus practice
New CSMs need product knowledge, internal process, and their first reps on the key conversations before they own accounts. Pair each knowledge module with a practice scenario. After a module on your renewal process, for example, the CSM runs a renewal conversation with an AI customer who raises a budget concern.
In Yoodli, teams build these as AI roleplays based on their own content and score them against their own rubric. Yoodli Roleplays support screen share, videos, and slides inside the conversation, so a CSM can practice walking a customer through a real dashboard or business review deck.
Certification: proof of readiness
Certification gives CS leaders confidence before a CSM takes over a strategic account. Define what a passing conversation looks like for each lifecycle moment, then certify every CSM on the same standard. Our page on onboarding and certification shows how teams set this up.
AI roleplays cut the manager time that certification at scale used to take. RingCentral used Yoodli AI roleplays to cut customer support call certification time by 90%. Another enterprise team used Yoodli to certify its CSMs during a virtual SKO.
Ongoing practice: before the call that matters
The best time to practice is right before a high-stakes conversation. A CSM preparing for a tough renewal can run the conversation a few times the day before. The AI customer can push back on price and ask about a missing feature. That rehearsal is short, private, and repeatable.
Ongoing practice also keeps skills from fading between formal training events. Yoodli Coach provides post-call coaching on calls recorded in Gong and Kaia and suggests new practice based on what it finds. CSMs get feedback tied to their real customer calls.
Manager coaching: a shared standard
CS managers coach best when they and their team agree on what good looks like. Use the same rubric for certification, practice, and call reviews. Managers can then spend one-on-one time on the specific skill a CSM needs, guided by practice data. Our post on coaching skills for managers covers how to build that habit.
Where CS enablement programs usually fall short
Most CS programs start strong in onboarding and then thin out. New CSMs get a few weeks of structured training, and after that they are on their own until the next annual kickoff. The skills that matter most, like handling a renewal objection or resetting a stalled rollout, get the least structured practice.
A second gap is content that stops at knowledge. A CSM can pass a quiz on the renewal process and still freeze when a customer says the budget moved to another team. Knowledge checks have a place, but every module that ends in a customer conversation should also end in practice.
The third gap is uneven standards. When each manager defines a good QBR differently, CSMs get mixed feedback and leaders cannot compare readiness across teams. A shared rubric fixes this. It also makes coaching faster, because managers and CSMs are working from the same definition of what good looks like.
Closing these gaps takes a short list of priority conversations, a clear standard for each one, and practice that is available whenever a CSM needs it.
Move What it involves 1. Pick priority conversations Start with the three or four lifecycle moments that matter most. 2. Set a clear standard Define a passing conversation for each moment and use one shared rubric. 3. Keep practice available Let CSMs rehearse whenever they need it, especially before the calls that count. Three moves close the usual gaps in CS enablement How to measure the program
Measure readiness first, then business results. Readiness metrics tell you whether the program is working, and business metrics connect it to retention and growth.
For readiness, track certification status, rubric scores by skill, and how scores change across practice attempts. Yoodli Measure shows progress across programs and against rubrics for each learner and team. Leaders can see where a cohort is strong and where it needs more practice.
For business results, connect enablement to the metrics CS leaders already report: gross retention, net revenue retention, expansion pipeline, and time to first value for new customers. Look at trends by cohort. A team that certified on renewal conversations should show its impact in the renewal numbers over the following quarters.
FAQ
What is customer success enablement?
Customer success enablement is the program that prepares CSMs to drive adoption, show value, and secure renewals. It combines product knowledge, process training, and practice on key customer conversations such as kickoffs, business reviews, renewals, and escalations. Strong programs also include certification and ongoing coaching so CSMs stay ready as products and customers change.
How is customer success enablement different from sales enablement?
Customer success enablement focuses on the post-sale relationship, while sales enablement focuses on winning new business. CSMs run a wider range of conversations over a longer time, from onboarding and adoption to renewals and escalations. Their training has to cover relationship management, value reporting, and risk handling along with product knowledge.
What should a CSM training program include?
A CSM training program should include product and process onboarding, practice on the key customer conversations, certification against a clear standard, and ongoing coaching. Practice matters most for high-stakes moments like renewals and escalations. AI roleplays let CSMs rehearse those conversations as often as they need before facing a real customer.
How do you measure the impact of CS enablement?
Measure CS enablement with readiness metrics first and business metrics second. Readiness metrics include certification rates and rubric scores by skill. Business metrics include gross retention, net revenue retention, expansion pipeline, and time to first value. Compare trends by cohort to see whether trained CSMs perform better over the following quarters.
Building a program CSMs use
CS teams already know which conversations decide renewals. A dedicated program gives CSMs a safe place to practice those conversations and a clear standard to meet. Start with the few lifecycle moments that matter most, certify against one rubric, and keep practice available right before the calls that count.
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Call Center Compliance Training: A Practice-First Guide for Support Leaders
Call center compliance training prepares agents to follow the legal, regulatory, and company rules that apply to every customer conversation. Most of those rules show up in spoken moments: verifying a caller’s identity, reading a required disclosure, handling a card number, or deciding what account details to share. Agents can know every policy and still miss one when a caller is frustrated and the queue is long.
That is why the strongest support teams treat compliance as a conversation skill. They teach the policy, then have agents practice it out loud under realistic pressure until the right behavior is automatic. This guide covers what a compliance program should include, how to build practice into it, how to certify agents before they take live calls, and how to measure compliance readiness.
Requirements vary by industry, region, and company. Your legal and compliance teams define what agents must do. The training approach below helps agents do it consistently.
What Is Call Center Compliance Training?
Call center compliance training is the part of agent training that teaches the rules governing customer conversations and confirms agents can apply them on real calls. It covers external regulations, industry standards, and internal policies.
The regulations depend on what your contact center does. Outbound sales calls in the United States fall under the FTC’s Telemarketing Sales Rule, which helps protect consumers from fraudulent telemarketing calls. Teams that take card payments work within PCI DSS, which the PCI Security Standards Council describes as a baseline of technical and operational requirements designed to protect payment account data. Healthcare support teams follow the HIPAA Privacy Rule, including its minimum necessary standard for using and disclosing protected health information.
Internal policies sit on top of these. They include escalation rules, approved language for refunds and credits, recording notices, and how to handle a customer who asks to speak with a supervisor.
Why Compliance Has to Be Practiced Out Loud
Most compliance training ends with a quiz that confirms an agent knows the rule. Rehearsal prepares them to apply it when a caller refuses a security question or asks them to skip the disclosure.
Real calls add pressure that a quiz can’t reproduce. Agents work against handle-time targets. Callers interrupt, get upset, or try to rush the process. Edge cases come up that the policy document covers in a footnote. Under that pressure, people fall back on what they have actually rehearsed.
Rehearsal builds that habit. When an agent has rehearsed a refused verification ten times, the eleventh time on a live call feels familiar. This is the same principle behind effective call center agent training, applied to the moments where a mistake carries regulatory risk.
Core Topics to Cover in Agent Compliance Training
Every contact center has its own list, but most compliance programs cover these areas:
- Identity verification: confirming the caller’s identity before discussing account details, and what to do when they can’t or won’t verify.
- Required disclosures and recording notices: what must be said, when, and in what words.
- Payment card handling: following your secure payment process so card data is protected.
- Privacy and data minimization: sharing only the information the caller is entitled to and the task requires.
- Outbound consent and do-not-call rules: for teams that make sales or follow-up calls.
- Complaints and escalations: recognizing a formal complaint and routing it correctly.
- Accurate statements: avoiding promises about refunds, timelines, or outcomes the agent can’t guarantee.
Each topic should map to specific, observable behaviors. That mapping becomes the rubric for practice, certification, and quality assurance.
How to Build Call Center Compliance Training Around Practice
A practice-first program follows a simple sequence. The steps below work for new-hire onboarding and for refresh training when a rule changes.
Step What it involves 1. Define observable behaviors Rewrite each requirement as something a reviewer could hear on a call. 2. Write pressure scenarios Build scenarios around the moments that go wrong, like a refused verification. 3. Practice with AI roleplays AI callers push back, and each attempt is graded against your rubric. 4. Reinforce through QA Use the same rubric on live calls and turn gaps into new practice. Practice-first compliance training turns each policy into a rehearsed behavior Turn each policy into observable behaviors
Rewrite each requirement as something a reviewer could hear on a call. “Protect customer privacy” becomes “verified identity with two approved data points before discussing the account.” Clear behaviors make scoring consistent across reviewers and teams.
Write scenarios that test the behavior under pressure
Build scenarios around the moments that tend to go wrong. One scenario might feature a caller who is locked out and angry about verification. Another might feature a customer who starts reading their card number aloud before the secure process begins, or a family member asking for account details. Each scenario should push on one or two compliance behaviors.
Let agents practice with AI roleplays
With Yoodli, support enablement teams turn these scenarios into AI roleplays. The AI caller plays the frustrated customer, responds to what the agent says, and pushes back the way real callers do. Each attempt in Yoodli Roleplays is graded against the team’s own rubric. An agent who skipped the recording notice or shared details before verification sees it immediately and tries again.
Teams can also turn a policy document into a full training path. Yoodli Create builds a learning journey from a single prompt, so a new disclosure requirement can become a short module with a practice roleplay at the end.
Reinforce through quality assurance
Use the same rubric in practice and in live call review. When QA finds a recurring gap, add or update a practice scenario so agents can work on it before their next shift. A strong call center quality assurance program uses call scores to decide what agents practice next.
Certify Agents Before They Take Live Calls
Certification gives compliance and operations leaders confidence that each agent has demonstrated the required behaviors before speaking with customers. Traditional mock-call certification depends on a manager listening to every call and grading it by hand, which slows down every new-hire class.
AI roleplays make certification faster and more consistent. RingCentral cut customer support call certification time by 90% using Yoodli AI Roleplays, as described in the RingCentral case study. Managers can then focus their time on the agents who need coaching.
Set a clear pass standard for each compliance behavior, allow retries, and recertify agents when regulations or internal policies change. Yoodli’s customer support solution shows how support teams structure onboarding and certification around practice.
How to Measure Compliance Readiness
Completion rates show who finished the course. Pair them with signals that show who is ready for live calls:
- Pass rate by compliance behavior: which requirements agents meet consistently and which they miss.
- Attempts to certify: a high number points to a confusing policy or a scenario that needs better instruction.
- QA findings in the first 30 and 60 days: whether practice performance carries over to live calls.
- Repeat findings by topic: where refresh training should focus next.
Yoodli Measure shows progress across programs and against rubrics, by agent, team, and program. For monitoring compliance on recorded customer calls after training, see this guide on how to track compliance in recorded calls.
Compliance Training in Regulated Industries
Some support teams carry heavier compliance requirements than others. Banks, lenders, and insurers handle account access, disclosures, and complaints under close regulatory review. Yoodli works with financial services teams that need consistent, documented customer conversations across branches and contact centers.
Healthcare contact centers balance privacy rules with patients who are often anxious or in pain. Practice helps agents follow the minimum necessary standard while still showing care. Yoodli supports healthcare organizations that train frontline teams on these conversations.
In both cases, the training platform has to meet the same bar as the business. Yoodli is SOC 2 Type 2 and GDPR compliant and doesn’t store PII.
To see how practice-based compliance training could work for your support team, talk to the Yoodli team.
FAQ
What is call center compliance training?
Call center compliance training teaches agents the laws, industry standards, and company policies that govern customer conversations, and confirms they can apply them on calls. It typically covers identity verification, required disclosures, payment card handling, privacy, complaints, and outbound calling rules. Strong programs combine policy instruction with spoken practice and certification before agents take live calls.
How often should call center agents complete compliance training?
Call center agents should complete compliance training during onboarding, whenever a relevant regulation or internal policy changes, and on a regular refresh cycle set by your compliance team. Short practice rounds work well between formal refreshes. QA findings should also trigger targeted training for the specific behaviors agents are missing on live calls.
Can AI roleplays be used for compliance training?
Yes, AI roleplays work well for compliance training because they let agents rehearse high-risk moments before facing them on real calls. An AI caller can refuse verification, interrupt a disclosure, or push for information the agent shouldn’t share. Each attempt is scored against your compliance rubric, so agents get immediate feedback and leaders get consistent readiness data.
How do you measure compliance training effectiveness?
You measure compliance training effectiveness by tracking what agents do on calls. Look at pass rates for each compliance behavior and the number of attempts agents need. Then compare them with QA findings on live calls in the first 30 to 60 days. If practice scores and live call findings move together, the training is working.
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SAM Model: How L&D Teams Build Training in Fast Iterations
The SAM model is an instructional design process built on short cycles of design, prototyping, and review. SAM stands for Successive Approximation Model. Michael Allen and the team at Allen Interactions developed it as an alternative to linear course development. L&D teams use it when a program has to ship quickly and get better with each round of feedback.
This guide covers how SAM works, the difference between its two versions, how it compares with ADDIE, and how to apply it to training that ends in real practice.
What is the SAM model?
SAM treats every early version of a course as a draft meant to be tested. Allen Interactions puts it plainly in its overview of rapid instructional design with SAM. “Most simply put, SAM is an iterative prototyping process through which prototypes evolve into the final product.”
That idea changes how a project feels. Stakeholders react to something they can click through or try within the first days of the project, and the design improves after each review.
The model also shifts attention toward the learning experience and learner motivation. Content organization still matters, but the question the team keeps asking is whether the experience changes what people do. Michael Allen laid out the full approach in the book Leaving ADDIE for SAM, which is still the standard reference for teams adopting it.
SAM1 and SAM2: the two versions
There are two versions of the process, and the right one depends on project size.
SAM1 is the simpler version. It runs a loop of evaluate, design, and develop, and the loop usually repeats about two times before the product is complete. Small projects with a short content list and a small team fit SAM1 well.
SAM2 is built for larger projects with more content, more stakeholders, and more development work. It breaks the work into three phases and adds structure around reviews and releases. Most enterprise programs, such as a new hire curriculum or a certification for a whole sales org, end up on SAM2.
The three phases of SAM2
Preparation
The team gathers background information quickly. That includes the business goal, the audience, existing materials, and any constraints on delivery. Preparation is meant to be short. The point is to get enough context to make the first design session productive.
Iterative design
Iterative design opens with the Savvy Start. This is an intensive kickoff, usually one or two days, where the design team and key stakeholders brainstorm, sketch early designs, and test assumptions together. Allen Interactions describes the guiding question of the session as “why shouldn’t we do this?” instead of “what should we do?”
After the Savvy Start, the team builds rough prototypes and reviews them in small steps. The prototypes are intentionally unfinished. Allen Interactions advises working breadth before depth, so the team sketches every content area before polishing any single one.
Iterative development
Development starts with a Design Proof, a functional demonstration that tests both the design and the production process. Then the team produces three releases. The alpha is a complete version with all content in place. The beta fixes the problems found while validating the alpha. The gold release is the final version, and it ships once the beta performs as expected.
Phase What happens 1. Preparation Quickly gather the business goal, audience, existing materials and delivery constraints 2. Savvy Start Intensive kickoff where designers and stakeholders brainstorm, sketch and test assumptions 3. Iterative design Build rough prototypes and review them in small steps, breadth before depth 4. Design Proof A functional demonstration that tests both the design and the production process 5. Alpha, beta, gold A complete version, then fixes from validation, then the final release SAM2 moves from a quick start to rough prototypes to staged releases Teams rolling SAM out for the first time often lean on the Leaving ADDIE for SAM Field Guide from ATD, which adds checklists, templates, and job aids for each phase.
SAM model vs. ADDIE
The comparison comes up in almost every L&D team that considers SAM. The ADDIE model moves through analysis, design, development, implementation, and evaluation in order. Each phase produces a deliverable that feeds the next one, and learners usually see the program near the end.
SAM runs those activities in loops. Analysis, design, and development overlap, and stakeholders review working prototypes from the first week. Evaluation happens throughout the project, so problems surface while they are still cheap to fix.
Neither model is right for every project. ADDIE fits stable content with strict review requirements, such as regulated compliance courses where a documented sign-off at each phase matters. SAM fits content that changes often or depends on how learners respond. Product launches, new sales messaging, and conversation skills all fall into that second group. Teams that need speed without losing quality often pair SAM with rapid eLearning development practices.
Why SAM suits skills-based training
Conversation skills are hard to design on paper. A script that reads well in a document can fall apart the first time a rep tries it with a skeptical buyer or a frustrated customer. Successive approximation catches that early because people try the experience while it is still a prototype.
Practice-based programs also have more moving parts than a slide course. There is the scenario, the persona the learner talks to, the rubric used to score the conversation, and the feedback the learner sees afterward. Each of those pieces benefits from a few rounds of testing with real learners. Good learning journey design treats practice as the end point of a program, and SAM gives teams a way to tune that end point before launch.
AI roleplays make prototyping practice much faster. In Yoodli, an enablement or L&D team can build a roleplay around their own content, set the persona, and score responses against an org-defined rubric. A rough version is ready in time for the same review meeting where stakeholders discuss it. Yoodli Roleplays also support screen share, videos, and slides inside the conversation, so a prototype can include the materials a learner will actually use.
How to run a SAM project for a practice-based program
Here is how SAM maps to a program that ends in AI roleplay practice, such as onboarding or certification.
- Preparation. Collect the rubric your managers already use, the core product or process content, and examples of strong conversations. A prompt-based course creation workflow works best when these sources are ready before the first session.
- Savvy Start. Bring the program owner, a frontline manager, and one or two strong performers into the room. Build the first learning journey live. Yoodli Create generates a full learning journey from a single prompt, which gives the group something concrete to react to in the first hour.
- Iterative design. Run the rough roleplays with a small group of learners. Watch where they get stuck, where the persona feels unrealistic, and where the rubric scores do not match what a manager would say. Adjust and run them again.
- Design Proof. Finish one module end to end, including how learners will reach it. If the program lives in your LMS, test the delivery path now. Our guide to SCORM vs. LTI for AI training covers the tradeoffs.
- Alpha, beta, and gold. Release the full program to a pilot group, fix what they find, and then launch to everyone.
Scale raises the value of each round of testing. Google Cloud used Yoodli to certify 15,000+ employees on a new GTM pitch. When a program reaches that many people, a problem caught in a prototype saves far more time than a problem caught after launch.
How to measure each SAM iteration
Iteration only helps if the team knows what to change. Decide what each round of testing should tell you before it starts.
Early prototypes answer usability questions. Can learners find the practice, understand the instructions, and finish a roleplay without help? Later rounds answer skill questions. Are rubric scores rising across attempts, and do they line up with manager judgment of the same conversations?
Yoodli Measure shows progress across programs and against rubrics, which gives a SAM team real evidence to bring to each review. After launch, the Kirkpatrick model is a useful frame for evaluating reaction, learning, behavior, and results. Teams building a broader practice strategy can see how these pieces fit together on our learning and development solutions page.
FAQ
What does SAM stand for in instructional design?
SAM stands for Successive Approximation Model. It is an instructional design process developed by Michael Allen and Allen Interactions. The name describes how the work progresses: each prototype gets closer to the final product through repeated cycles of evaluation, design, and development. Stakeholders and learners review working versions along the way.
What is the difference between SAM and ADDIE?
ADDIE runs its five phases in sequence, while the SAM model repeats short design and development cycles. In ADDIE, learners usually see the program near the end. In SAM, stakeholders review working prototypes from the start, so feedback shapes the design early. ADDIE suits stable, heavily documented content, while SAM works better for programs that change often.
What is a Savvy Start?
A Savvy Start is the kickoff session that opens the iterative design phase of SAM2. It usually runs one or two days and brings the design team together with key stakeholders. The group brainstorms, sketches early designs, and tests assumptions quickly, so the project starts with rough prototypes everyone has already reacted to.
Is the SAM model an agile approach to training design?
Yes, SAM shares the core ideas of agile development. It works in short cycles, favors working prototypes over long documents, and builds in frequent review. Teams that already run agile sprints often find SAM easy to adopt, because the rhythm of build, review, and revise is the same.
Putting SAM to work
The SAM model gives L&D teams permission to show unfinished work early, and that is where most of its value comes from. Start with a short Savvy Start, get a rough version in front of real learners within days, and let their practice results decide what changes next. Programs built this way launch with fewer surprises and keep improving after the gold release.
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8 AI Tools for Sales Enablement Teams in 2026
AI tools for sales enablement now handle work that used to take an enablement team weeks. They build courses, certify reps on a new pitch, and show leadership who is ready to sell it. The need is real. RepVue’s Q2 2025 Cloud Sales Index put average quota attainment below 43% across roughly 47,000 sellers at 246 cloud companies, and every product launch resets what ready means.
Most enablement teams also run too many tools. An LMS, a content platform, a call recorder, and a roleplay tool each need their own login, data, and security review. This guide covers what to look for in AI tools for sales enablement and how eight options compare. We start with Yoodli, our own platform, which has more than 1 million users and runs more than 3 million minutes of AI roleplay every day.
A note on how we built this list: the tools are not ranked. Yoodli comes first because it is our platform. Capabilities come from each vendor’s public product pages and help centers, and review themes come from G2 as of October 2026. Software changes quickly, so some limitations noted here may already be addressed.
What to Look for in AI Tools for Sales Enablement
Customization to your methodology and content
Every enablement program runs on its own methodology, messaging, and launch materials. The tool should score reps on BANT, MEDDPICC, or a rubric you create and build personas for your buyers. It should also turn whatever you upload, from a launch deck to a recorded call, into practice.
Speed from launch deck to certification
Product launches reset what ready means. Look for a tool that builds a full learning journey from your materials, lets an AI tutor teach the new pitch, and certifies reps before launch day.
AI tool training
Enablement now owns adoption of Copilot, Salesforce, and internal AI tools. Check for ready-made tool training programs and for practice inside the software reps use.
Fit with your stack
Practice should run inside your LMS through SCORM or LTI, on internal portals, and inside CRM and enablement platforms such as Salesforce and Highspot. Tools that connect through MCP can also pull content and context from the systems your team already uses.
Readiness data and proof
Leaders want certification status by rep, team, and program, plus published results from companies running enablement at scale. Our explainer on sales readiness covers how to define it.
AI Tools for Sales Enablement at a Glance
Tool What it is Built for Yoodli The AI Platform for Human Skills: build, certify, coach, and measure enablement programs on one platform Sales, partner, support, and L&D enablement Outdoo Revenue intelligence with AI roleplay, tutoring, and assessments Sales and customer-facing teams Build it yourself on Claude A general-purpose model you configure and maintain Teams with engineering time Second Nature AI roleplay modules delivered through the LMS Sales and service teams Hyperbound Sales practice, learning paths, and scorecards SDR and AE teams Mindtickle Revenue enablement suite covering training, content, and roleplay Revenue teams consolidating on one suite Avarra Avatar-based AI roleplay that runs on Zoom Sales teams Gong Conversation intelligence with courses and AI roleplay in Gong Enable Revenue teams that record calls in Gong Sales Enablement AI Tools Comparison Table
A check means the vendor documents the capability on its public product pages or help center. Partial means it documents part of the capability. A blank cell means we could not find it there as of October 2026. DIY means a team would build it on Claude.
Capability Yoodli Outdoo Claude (DIY) Second Nature Hyperbound Mindtickle Avarra Gong AI roleplays scored on your methodology ✓ DIY Builds full training programs from your content ✓ ✓ DIY ✓ Partial ✓ ✓ ✓ AI teaches from your launch deck inside the roleplay ✓ AI tool and software training ✓ ✓ ✓ Ready-made AI tool training templates ✓ Embeds in your LMS (SCORM or LTI) ✓ ✓ ✓ ✓ Embeds full programs on your own site, portal, or intranet ✓ DIY Partial Runs inside Salesforce and Highspot ✓ Partial Partial Connects to other AI tools through MCP ✓ ✓ ✓ Supports partner enablement programs ✓ DIY ✓ Published enterprise program certifying 10,000+ employees ✓ Yoodli
Built for: Sales, partner, support, and L&D enablement at enterprise scale.
G2 rating: 4.8 out of 5. In October 2026, G2 listed Yoodli as the top trending product in its AI Sales Roleplay Tools category, with the largest rating increase that month.
Yoodli is the AI Platform for Human Skills, built for sales enablement teams that run onboarding, launches, certification, and partner programs at enterprise scale.
From launch deck to certification path
Yoodli Create turns a prompt and your launch materials into a learning journey with AI roleplays, tutoring sessions, and knowledge checks. Reps learn the new pitch from an AI tutor that presents your slides, then practice it against AI buyers scored on your rubric, whether that is MEDDPICC or a framework you created. Enablement watches readiness build by team before the launch date.
AI tool training for the tools you just bought
Enablement now owns AI adoption too. Yoodli’s expanded template library includes ready-made tool training programs for certifying reps on Copilot, Salesforce, and the other platforms they already use. Everboarding templates keep GTM and partner teams current after every release.
Fits the stack you already own
Yoodli roleplays embed in your LMS through SCORM or LTI, inside Salesforce, and inside Highspot, so reps practice without opening another tool. An MCP connection lets content, conversations, and context from the systems your team works in flow into Yoodli to generate roleplays, personas, and programs.
Customer results
ServiceNow certified 8,000+ sellers in six weeks on a program that used to take a full quarter. Loopio cut demo certification attempts by 67% and certified 60 reps. Intuit’s Global Sales Enablement team won four 2026 Brandon Hall Group awards for programs where Yoodli AI roleplays power the practice.
“What I liked about the Tutor is you’re doing learning and practice in tandem. The Tutor teaches them bit by bit, then they have a chance to roleplay at the same time and get direct feedback in that same conversation.”
Bety Garcia, Senior Enablement Program Manager, LoopioPros
- Yoodli Create turns a launch deck into a certification path with roleplays, tutoring, and knowledge checks.
- Ready-made AI tool training templates certify reps on Copilot, Salesforce, and other platforms.
- Practice embeds in your LMS, Salesforce, and Highspot, and connects to other tools through MCP.
- ServiceNow certified more than 8,000 sellers in six weeks on Yoodli.
- The platform runs at scale, with more than 1 million users and more than 3 million minutes of AI roleplay every day.
Cons
- Yoodli is built for company-wide programs, with SSO, SCIM, LMS integration, and enterprise security review. A team buying a quick practice tool for a handful of reps may not need that depth.
Outdoo
Built for: Sales and customer-facing teams.
Outdoo, formerly MeetRecord, combines AI-tutored lessons, AI roleplays, software workflow practice, and conversation intelligence. Courses can run in an LMS through SCORM or xAPI.
Pros
- Reviewers call it easy to implement and navigate.
- Reviewers value its call recordings and AI call summaries.
Cons
- G2 reviewers report inconsistent or unfair grading on calls.
- Reviewers flag accuracy issues in AI call ratings and missed inputs.
- Reviewers mention limited dashboard customization and limited CRM integration.
- Reviewers report recording issues, including delayed analysis and inaccurate transcripts.
Good to know
Outdoo’s value depends on standardizing on its call recorder, which overlaps with Gong or any recorder you already run.
Build It Yourself on Claude
Built for: Teams with engineering time to run a pilot.
Enablement teams use Claude to draft talk tracks, battlecards, and quiz questions, and a Claude Project loaded with a playbook can play a buyer for quick practice.
Pros
- A pilot takes an afternoon to set up.
- Prompts and scenarios are fully flexible.
Cons
- Consistent rubric scoring, assignments, and progress tracking are yours to build.
- LMS packaging, security review, and stable voice sessions at scale are yours to maintain.
- Practice in a general-purpose tool never shows up in readiness reporting.
Second Nature
Built for: Sales and service teams.
Second Nature is an AI roleplay platform. Enablement teams build roleplays from uploaded decks or scripts with an AI assistant, then publish them to an LMS such as Workday, Cornerstone, or Adobe Learning Manager through SCORM or LTI.
Pros
- Reps practice with video avatars.
- Modules plug into an LMS such as Workday or Cornerstone.
Cons
- G2 reviewers report AI responses that misinterpret questions or give irrelevant or inaccurate answers.
- Reviewers say some conversations feel less interactive or disconnected.
- Reviewers flag language issues that limit use for non-English speakers.
- Reviewers mention a steep learning curve for beginners.
Good to know
Second Nature delivers roleplay modules, and the rest of the program lives in your other tools. Its public materials do not cover AI tool training templates or practice inside Highspot.
Hyperbound
Built for: SDR and AE teams.
Hyperbound is a sales practice and scorecard platform. Enablement can group AI roleplay bots into learning paths, track rep progress, and run team competitions.
Pros
- Reviewers call the interface easy to use.
- Reps get a high volume of cold-call practice.
Cons
- G2 reviewers report call lag and delays in AI responses that break the flow of a conversation.
- Reviewers describe some bot calls as inaccurate or less realistic than live buyers.
- Reviewers mention a steep learning curve with the more complex features.
Good to know
Hyperbound is built for sellers, so partner, support, and L&D enablement would run on a separate platform.
Mindtickle
Built for: Revenue teams that consolidate enablement on one suite.
Mindtickle is a revenue enablement suite covering training paths, a content hub, AI roleplays, call recording, digital sales rooms, and a readiness index. An AI copilot drafts roleplay scenarios and grades submissions.
Pros
- Training, coaching, and readiness tracking live in one suite.
- Reviewers praise its interactive training content.
Cons
- G2 reviewers report slow loading and slow performance, especially with heavy content and large modules.
- Reviewers say integration with other management tools and LMSs is limited.
- Reviewers mention a learning curve and navigation issues during training.
- G2 users report an average implementation time of about two months.
Good to know
Mindtickle is designed to be the whole enablement stack. Teams keeping their current LMS and content platform should ask how the pieces fit together.
Avarra
Built for: Sales teams that practice on Zoom.
Avarra is an avatar-based AI roleplay platform that runs on Zoom. Enablement teams can turn recorded sales conversations into training modules, and reps practice new pitches with 3D avatars.
Pros
- Reps practice with realistic 3D avatars that look like a video call.
- Practice runs inside Zoom, where many reps already meet buyers.
Cons
- There are too few public reviews to judge how it performs at enterprise scale.
- Its public materials do not cover LMS delivery, language support, or programs outside sales.
Gong
Built for: Revenue teams that record calls in Gong.
Gong is a conversation intelligence platform. Gong Enable uses AI to spot skill gaps in recorded calls, build courses and short lessons, run AI roleplay through AI Trainer, and track whether new behaviors show up on live calls. Gong also supports MCP.
Pros
- Practice scenarios come from your own recorded calls.
- Reviewers praise its call recording, AI notes, and call search.
Cons
- G2 reviewers report recording and call-tracking issues, including missed recordings and trouble finding past calls.
- Reviewers flag AI inaccuracy in summaries and insights.
- Reviewers list missing features, including real-time AI coaching and better search filters.
- Some reviewers cite high cost and a complex onboarding process.
Good to know
Gong Enable assumes Gong records your calls. Partner programs and teams outside revenue fall outside its focus.
How to Build Your Sales Enablement AI Stack
Start from the readiness metric leadership cares about, such as time to first deal or certification before a launch. Pick the tool that moves that metric, then confirm it fits where reps already work. Our list of sales enablement metrics covers which numbers to report.
Keep the stack small. One practice and certification platform, one content system, and one call recorder covers most enterprise programs. Each extra tool adds another login, another security review, and another place where data goes stale.
Then test with a real launch. Give each vendor your next launch deck and see how quickly it becomes a certification path your reps can pass.
FAQ
What are AI tools for sales enablement?
AI tools for sales enablement help enablement teams build training, certify reps, and measure readiness with less manual work. The category includes AI roleplay and coaching platforms, content platforms with AI search, conversation intelligence, and general-purpose assistants. Yoodli covers practice, certification, and readiness, and it embeds in the LMS and CRM teams already use.
How do enablement teams use AI roleplay?
Enablement teams use AI roleplay so reps can rehearse new pitches, objection handling, demos, and discovery before live calls. Each session is scored against the team’s methodology, and the results feed certification and readiness reports. Gartner covered the category in its 2026 Market Overview for B2B Sales AI Role-Play Applications, which named Yoodli.
Can AI tools replace an LMS?
Most enterprises keep their LMS as the system of record and add AI tools for the skills an LMS cannot test, such as live conversations. Yoodli delivers LMS outcomes like content generation, assignment, and tracking, and it also embeds inside an LMS through SCORM or LTI so completions and scores flow back.
What should enablement leaders look for in AI training tools?
Look for scoring on your own methodology, realistic buyer personas, fast program building, and embedding in your LMS and CRM. Then check proof, meaning published results for certification and ramp at companies your size. Ask about security, languages, and how the platform performs when thousands of reps practice in the same week.
The right AI tools for sales enablement shorten the time between a new message and a rep who can deliver it. To see Yoodli run your next launch, talk to our team.
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Strategic Account Planning: How Sales Teams Build Plans Reps Can Execute
Strategic account planning is how sales teams decide where to invest in their most important customers and prospects, and how to grow those relationships over time. A good account plan maps the buying group, connects your product to the account’s business priorities, and lays out the sequence of conversations that will move the relationship forward.
The plan only creates value when reps can carry it into those conversations. Quota pressure makes that execution matter. RepVue’s Cloud Sales Index reported 43.24% quota attainment for Q3 2025, which means most reps in the index finished the quarter below target. For many teams, the most reliable path to the number runs through deeper relationships in a focused set of accounts.
This guide covers what account planning at this level involves and what a strong plan includes. It also walks through how to run the planning process and how to prepare reps to execute the plan in front of executives and buying committees.
What Is Strategic Account Planning?
Strategic account planning is the process of building a documented plan for a high-value account. The plan covers the account’s business goals, the people involved in buying, your current footprint, and the opportunities to expand. The plan sets objectives for the next two to four quarters and assigns the actions that will get there.
It differs from territory planning, which decides how to divide accounts across reps. It also differs from day-to-day account management, which focuses on keeping current customers successful. Account planning at this level sits between the two. It picks a small number of accounts with the most potential and gives each one a deliberate growth strategy.
Many teams apply it to the small share of accounts with the most revenue potential. That usually includes large current customers with room to expand and target accounts that closely fit the ideal customer profile.
What Goes Into a Strategic Account Plan
Account plan templates vary, but the strongest plans share the same core sections. Keep the whole plan short enough that a rep can review it in a few minutes before a meeting.
Section What it covers 1. Snapshot and priorities Strategy, recent news, financial position and the priorities leadership has stated 2. Buying group map Each stakeholder’s role, priorities and relationship strength, including economic buyer and champion 3. Whitespace and expansion Teams, regions or use cases that share the problem current users solved 4. Value hypotheses A different value story for each key stakeholder’s priorities 5. Conversations, milestones, risks The meetings you need, who owns each, what each achieves, and risks Strong account plans share the same core sections Account snapshot and business priorities
Summarize the account’s strategy, recent news, financial position, and the two or three priorities leadership has stated publicly. Every later section should connect back to these priorities.
Buying group map
List every stakeholder who influences a decision, with their role, priorities, and current relationship strength. Identify the economic buyer who signs, and the champion who sells internally on your behalf. Mark the relationship gaps, because those gaps usually become the first actions in the plan.
Whitespace and expansion opportunities
Map where your product is used today and where it could be used next. Whitespace analysis shows teams, regions, or use cases that share the same problem your current users already solved.
Value hypotheses by stakeholder
Write a short value hypothesis for each key stakeholder. A CFO cares about cost and risk. A VP of operations cares about throughput and consistency. The same product needs a different story for each person.
Conversation plan, milestones, and risks
Sequence the meetings you need over the next quarters, who owns each one, and what each meeting should accomplish. Note the risks, such as a champion changing roles or a competitor already in the account.
These conversations have to count. Gartner reports that 67% of B2B buyers prefer a rep-free experience, so every meeting a buyer agrees to needs to deliver clear value for that person’s role.
How to Run a Strategic Account Planning Process
A repeatable planning process keeps plans consistent across reps and makes them easy for managers to review.
- Select the accounts. Use revenue potential, fit with your ideal customer profile, and existing relationships to choose a focused list.
- Research the account. Read annual reports, earnings calls, and leadership interviews. Talk to current users about what they see inside the account.
- Map the buying group. B2B buyers move across many channels, and McKinsey found that B2B customers use an average of ten interaction channels in their buying journey. Track where each stakeholder gets information, as well as who they are.
- Write the value hypotheses. Connect each stakeholder’s priorities to a specific outcome your product supports.
- Plan the conversations. Decide which meetings come first, what each one should achieve, and who from your team attends.
- Review with the manager. Walk through the plan, pressure-test the assumptions, and agree on the first 30 days of actions.
- Update every quarter. Revisit the plan after major meetings, organizational changes, or new opportunities.
Qualification frameworks fit naturally into this process. Teams that use MEDDPICC often use it to check each opportunity inside the plan for gaps in metrics, decision criteria, and paper process.
Turning the Account Plan Into Conversations Reps Can Deliver
An account plan identifies the meetings that matter. The next step is making sure the rep is ready for each one. A first meeting with a CFO or a renewal conversation with a skeptical VP is too important to be the rep’s first time saying the pitch out loud.
With Yoodli, managers and enablement teams can turn the account plan into practice. A manager can set up an AI persona with Yoodli Personas, choosing the appearance, voice, and context, to play the account’s VP of operations with the priorities captured in the plan. The rep then runs the meeting in an AI roleplay. The persona asks hard questions, raises the concerns the plan flagged, and responds to how the rep frames value.
The roleplay is scored against a rubric the team defines. For an executive meeting, the rubric might check whether the rep connected the product to a stated priority, quantified the impact, and asked for a clear next step. Teams use AI sales roleplay the same way for each stakeholder in the buying group. The guide to practicing multi-stakeholder deals covers how to rehearse meetings where several buyers are in the room.
After the real meeting, coaching continues. Yoodli Coach provides post-call coaching on real calls, and the Gong integration turns recorded customer calls into personalized feedback and suggested practice.
Making Account Plan Reviews Faster for Sales Managers
Account reviews take a lot of manager time. Managers review the plan, then often roleplay key meetings with each rep to check readiness. Scored practice gives managers a head start. They can review rubric scores and recordings before the account review and spend the meeting on strategy.
The time savings can be large. Harness cut sales training review time by 75% with Yoodli, as described in the Harness case study. Managers who spend less time grading practice have more time for the coaching conversations that move strategic accounts forward. Yoodli’s sales coaching solution shows how managers fit this into their weekly rhythm.
How to Measure Account Plan Results
Track whether plans turn into progress, as well as whether they were completed. Useful metrics include:
- Buying group coverage: the share of mapped stakeholders the team has engaged in the last quarter.
- Executive meetings held: planned versus completed meetings with senior stakeholders.
- Expansion pipeline: new opportunities created from whitespace in planned accounts.
- Win rate and deal size in planned accounts: compared with accounts that have no plan.
- Readiness scores: practice scores for the high-stakes meetings in each plan.
Revenue leaders can see how these pieces connect across teams on Yoodli’s page for revenue teams.
To see how your team could prepare reps for the high-stakes meetings in every account plan, talk to the Yoodli team.
FAQ
What is strategic account planning?
Strategic account planning is the process of building a documented growth plan for a high-value account. The plan covers the account’s business priorities, the buying group, your current footprint, expansion opportunities, and the sequence of conversations needed to grow the relationship. Sales teams usually apply it to a focused set of accounts with the most revenue potential.
What should a strategic account plan include?
A strategic account plan should include an account snapshot and the account’s business priorities. It also needs a buying group map, whitespace and expansion opportunities, value hypotheses for each key stakeholder, and a conversation plan with milestones and risks. Each section should connect back to the priorities leadership at the account has stated, so every action supports a goal the buyer cares about.
How often should account plans be updated?
Account plans should be updated at least once a quarter and after any major change in the account. Triggers include a new executive, a reorganization, a lost or won opportunity, or a competitor entering the account. Quarterly reviews with the sales manager keep the plan current and make sure the next quarter’s conversations are planned and prepared.
How is strategic account planning different from key account management?
Strategic account planning is the work of building a documented strategy for growing an account. Key account management is the ongoing ownership of the relationship, carrying out that strategy day to day through meetings, service, and expansion. Most teams run both together, with the plan guiding how the account team spends its time and each quarter’s review updating the plan.