Most discovery guides assume a linear funnel. Real discovery is messy. Buying groups loop through jobs like problem identification, solution exploration, and consensus building. If your questions do not match the job the buyer is actually doing, the call stalls. A Living Playbook fixes this by turning proven discovery patterns from your best calls into real-time prompts during conversations.
Key takeaways
- B2B buying is nonlinear. Teams loop across critical buying jobs. Your discovery must align with those jobs. Gartner on buyer enablement
- Buyers operate across many channels. Your questions and language must stay consistent from email to video to chat. McKinsey on omnichannel B2B sales
- High performers guide the conversation with insight-led questions. HBR’s “The End of Solution Sales” explains the shift from diagnosing needs to teaching and reframing. HBR article
- Under pressure, cognitive traps derail thinking. Short, proven prompts maintain quality in the moment. HBR classic
- Real-time AI assistants have improved productivity in adjacent domains by about 15%. This supports in-flow prompting for sales. Quarterly Journal of Economics
Table of contents
- Why discovery breaks down
- A job-to-be-done question set
- A 30-day implementation plan
- Metrics that predict revenue impact
- How Nomi fits
- FAQ
- References
Why discovery breaks down
Most teams train a linear script. Buyers do not move linearly. They revisit requirements, loop back to solution exploration, and rebuild consensus as new stakeholders join. When reps ask the wrong question for the moment, the call loses momentum.
Human limits compound the problem. Under time pressure, even experienced sellers default to shortcuts that do not fit complex conversations. This is why short, context-aware prompts matter during the call, not after it. Read HBR
A job-to-be-done question set
Below is an example mapping of discovery questions to common buying jobs. Use this as a starter and customize to your motion.
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Problem identification
- “What changes in your metrics tell you this problem is urgent?”
- “Who is most impacted if this is not fixed this quarter?”
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Solution exploration
- “When this worked at your peers, what did they measure first?”
- “What would make a pilot a clear yes or a clear no in 30 days?”
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Requirements building
- “What security or data constraints will block approval later if we ignore them now?”
- “Which teams must approve the rollout for this to go live on schedule?”
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Supplier selection
- “What criteria will matter most when you narrow the shortlist?”
- “Who has veto power and what evidence will they want?”
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Validation
- “If we validated this with one proof point next week, which one would earn immediate confidence?”
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Consensus creation
- “How will you explain the tradeoffs to the CFO in one slide?”
- “What is the simplest story that aligns IT and the business on timing?”
This framework acknowledges nonlinear movement across jobs and focuses your questions on progress instead of small talk. Gartner overview
A 30-day implementation plan
Week 1: Harvest what already works
Pull 20 to 30 clips from won discovery calls that led to next steps. Tag the exact questions that unlocked momentum and the buyer job present at that moment.
Week 2: Build and pilot
Turn the patterns into two or three in-call prompts per job. Launch with a champion squad of 4 to 6 reps. Track show rate, accept rate, and time to next step.
Weeks 3 and 4: Iterate and scale
Retire weak prompts. Add persona and industry variants. A/B test two versions of your most used prompts: one insight-led and one diagnostic. Use the winner org-wide.
Metrics that predict revenue impact
- Leading indicators: prompt show rate, prompt accept rate, time to confirm next step, coverage of buying jobs per call.
- Lagging indicators: stage conversion, win rate, cycle time, average deal size, no-decision rate.
Research shows that in-flow assistance can raise productivity for complex conversations, particularly for less experienced team members. That mechanism supports faster, more consistent discovery. Read the QJE paper
How Nomi fits
Nomi is a real-time AI copilot for live sales calls. It listens to your conversations, identifies what works for top performers, and delivers in-call phrase suggestions so every rep benefits from a Living Playbook. This mirrors the product positioning on the Nomi homepage, which states that Nomi helps teams close about 12% more deals. Learn more or request a demo: https://www.nomi.so/.
What you can expect in practice:
- Live prompts tailored to the buying job present in the call
- Consistent discovery questions that keep momentum and reduce hesitation
- A feedback loop that improves prompts each week based on real outcomes
FAQ
How is this different from a static discovery script?
Scripts are generic and assume a linear path. A Living Playbook adapts to context, persona, and the buying job, then surfaces prompts in the moment.
Do we still need post-call analysis?
Yes. Post-call analysis informs the prompts that power your Living Playbook. Real-time coaching operationalizes those insights during the meeting.
Will this guarantee higher win rates?
No solution can guarantee outcomes. The strongest evidence shows that timely prompts improve speed and consistency, two leading indicators correlated with conversion. See the QJE study for adjacent proof. Read the study
References
- Gartner. Marketing’s Role in Buyer Enablement. Buying jobs are nonlinear and loop throughout the journey. Read the article
- McKinsey. B2B sales: Omnichannel everywhere, every time. Buyers operate across many channels and expect consistency. Read the article
- Harvard Business Review. The End of Solution Sales. Why insight-led discovery beats traditional diagnosis. Read on HBR
- Harvard Business Review. The Hidden Traps in Decision Making. Decision biases under pressure. Read on HBR
- Brynjolfsson, Li, and Raymond. Generative AI at Work. Quarterly Journal of Economics (2025). Real-time suggestions increased agent productivity by about 15% in customer support. Read the paper