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Objection Handling 2.0: Real-Time AI Prompts That Keep Deals Moving

Turn objections into momentum with real-time AI coaching. A Living Playbook converts top-call patterns into in-call guidance that improves consistency and speed.

Emily Bennett, Chief Marketing Officer @ NomiPublished Aug 15, 20254 min read
Objection Handling
Sales Enablement
AI Copilot
Conversation Intelligence
B2B SaaS

Objections do not kill deals; poor responses do. In high-stakes calls, reps need phrasing that fits the moment, not a static paragraph from page 42 of a PDF. The answer is a Living Playbook that learns from your best calls and surfaces the right words inside the conversation.

Key takeaways

  • Buyers use around ten channels in a typical B2B journey, so messaging must stay consistent across contexts. McKinsey research
  • Under pressure, people rely on mental shortcuts that derail complex decisions; real-time prompts reduce this risk. Harvard Business Review
  • Evidence from a large QJE study shows in-flow AI suggestions can raise agent productivity by about 15% in a related domain. Quarterly Journal of Economics

Table of contents

  • Why objections stall deals
  • What real-time objection handling looks like
  • A 30-day rollout plan
  • Metrics that predict revenue impact
  • How this works with Nomi
  • FAQ
  • References

Why objections stall deals

Context switches kill momentum. When reps tab away to hunt for the right answer, the call loses energy. Research also shows buyers switch channels frequently and expect continuity. Your guidance must follow the conversation, not the other way around. McKinsey on omnichannel

Cognitive load is real. Under time pressure, even experienced sellers fall back on biases that lead to suboptimal responses. That is why tested phrasing and questions matter in the moment. HBR on decision traps

Real-time assistance works. In customer support, a peer-reviewed study found that a generative AI assistant providing live suggestions increased agent productivity by roughly 15% on average. While sales is different, the mechanism is similar: in-flow guidance raises consistency and reduces time to a good response. QJE study


What real-time objection handling looks like

A Living Playbook is not a document. It is a system that:

  1. Learns from your best calls
    Capture how top performers frame value, quantify ROI, and handle price, timing, or competitor mentions. Convert those moments into reusable, tagged cards.

  2. Surfaces prompts inside the call
    When a trigger appears, show the best move immediately: a clarifying question, a talk track, or a short customer story. No tab switching or searching.

  3. Improves through feedback
    Track show rate, accept rate, and downstream impact on next steps. Retire weak cards and double down on winners each week.

This approach fits how buyers move across channels and research independently while expecting a consistent experience. McKinsey confirmation


A 30-day rollout plan

Week 1: Map the high-leverage objections
Choose 5 to 7 moments that decide deals in your motion: price, ROI, status quo, security, legal, and one or two named competitors. Pull 20 to 30 clips from won calls per moment and tag phrasing and sequencing.

Week 2: Build and pilot
Turn patterns into two or three in-call suggestion cards per moment. Launch with a champion squad of 4 to 6 reps. Track show rate, accept rate, and time to handle each objection.

Weeks 3 and 4: Iterate and scale
Remove low performers, add variants by persona or industry, and A/B test discovery prompts. Expand to the full team once leading indicators improve.


Metrics that predict revenue impact

  • Leading indicators: suggestion show and accept rates, time to respond to key objections, coverage of critical moments, message consistency by persona.
  • Lagging indicators: stage-to-stage conversion, win rate, cycle time, average deal size, no-decision rate.

The combination of reduced cognitive load and faster, consistent responses is what moves these metrics. See HBR for the cognitive-bias context and QJE for real-time AI assistance effects in adjacent workflows. HBR | QJE


How this works with Nomi

Nomi is a real-time AI copilot for live sales calls. It listens to the conversation, identifies what works for your top reps, and delivers in-call phrase suggestions so every rep benefits from a Living Playbook. This description mirrors the product positioning on the Nomi homepage. The site also states that Nomi helps teams close about 12% more deals. Learn more or book a demo: https://www.nomi.so/.

What you can expect in practice:

  • Live prompts when pricing, ROI, or competitors come up
  • Context-aware phrasing that reduces hesitation and keeps the call moving
  • A feedback loop that improves suggestions each week based on real outcomes

FAQ

What is a Living Playbook for objections?

A continuously updated set of short, context-aware prompts built from your best calls and delivered in real time inside the conversation.

How is this different from a script?

Scripts are static and generic. A Living Playbook adapts to buyer context, persona, and trigger, and it improves with feedback.

Does real-time coaching always increase win rate?

No solution guarantees outcomes. The strongest evidence shows real-time assistance improves speed and consistency, which are leading indicators correlated with conversion. See the QJE productivity study for adjacent proof points. Read the study


References

  • McKinsey. Five fundamental truths: How B2B winners keep growing. Average of ten interaction channels in the buying journey; importance of seamless omnichannel. Read the article
  • Harvard Business Review. The Hidden Traps in Decision Making. Why cognitive load and biases undermine complex conversations. Read on HBR
  • Brynjolfsson, Li, and Raymond. Generative AI at Work. Quarterly Journal of Economics (2025). Real-time prompts increased agent productivity by about 15% in customer support. Read the paper

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Dive deeper into the strategies and integrations revenue teams use with Nomi.

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