Show of hands: Are you considering using AI to analyze reps’ sales calls to surface the key interaction sequences that most frequently lead to a sale. Maybe other relevant insights?
If no – why not?
If yes – what’s the biggest barrier?
If you’ve already done it – what was the result?
Yes, and will continue to evolve it. 1st iteration: basic sales process: how to run a meeting. I use Winning by Design methodology, so build a call scorecard that shows do they use ACE opening, engage and close meeting properly w next steps. Second iteration call quality: Engagement levels Are they asking the right questions, will be programming those in.
KC ensuring the insights are actionable and tied directly to revenue impact (easy to generate a ton of call data but unless the output clearly shows which behaviors correlate with higher win rate... and reps can quickly adapt based on that...it risks becoming just another dashboard no one uses (classic). I’d want to see the analysis layered with rep-specific coaching points, trend tracking over time, and integration into our existing enablement process so adoption is baked in (not optional). Make sense?
Yes, that makes sense. Mike C., Chris D. you sparked an idea. Instead of auditing calls against a static checklist, imagine auditing them as cause-and-effect sequences of rep→client interactions that actually lead to wins. With the right structuring and a pool of successful calls, you could surface the highest-performing interaction sequence for your business with branches that handle common forks. For example, a winning flow might look like: ACE in <60 sec → surface 2 concrete pain points → get the client to put a number on the impact → ask “What’s the cost of inaction?” → lock a hard next step. This could be stress-tested against lost calls to see what’s missing when deals fall apart. I think this has the potential to generate greater results than any model because the sequence would be model-agnostic, behavior-based, outcome-tied, and business-specific. Just by repeating the 2–3 motifs that most often precede wins, one could expect significant sales lift from the bottom of the funnel. What do you think. Does it make sense or am I talkking crazy?
KC that makes sense, you can use AI and keywords to measure best practices. For example, in the WbD framework a discovery call looks like: ACE Agenda, What else would you like to cover? Situation question Pain question dig deeper, mirroring, confirm the pain storytelling If you are going to scorecard the call (as we built out in Gong) you use the transcript to trigger sentiment and identify skills. For example: storytelling begins with “that reminds me” or “we had a customer with a similar problem and they…” certain phrases For mirroring, did the customer repeat a keyword in the follow up question for confirmation, how many times did custoemr say ‘that’s right’ or the equivalent For demo call you would do the same did the sales engineer stop after each provlem and confirm ‘will this solve your problem’ ‘how will you use this’ or did they show up and throw up. BUT, there are cool solutions that are also measuring this in real time with prompts, like aircover, use this story now So you can almost get a realtime score, e.g. practically gamifying the call. e.g.: you are at 60% because you have not confirmed pain or told a story when you can get to that point and the motion is so clear, an AI sales agent would be appropriate
