When we let the AI suggest the next best action in a CRM, 18% of reps ignored it, but the 2% who followed it closed deals 1.7× faster. Is the issue trust, timing, or the relevance of the recommendation?
I'd love to explore the relevance angle further - what kind of data was the AI trained on to make those recommendations, and did you see any differences in performance based on the type of deal or customer segment?
I'd love to explore the relevance aspect further - what kind of data was the AI trained on to make those recommendations, and was it tailored to individual reps or a one-size-fits-all approach?
I'd love to explore the relevance angle further - what kind of data was the AI trained on to make those recommendations, and was it tailored to individual rep styles or more of a one-size-fits-all approach?
I'd love to explore the timing aspect further - were the suggestions made in real-time during client interactions or as a post-meeting follow-up?
We ran the timing experiment in‑situ: suggestions popped up the moment the user typed a partial answer, not after the meeting. The real‑time hook captured the cognitive commitment that had just formed, which seemed to lower resistance. A post‑meeting follow‑up, by contrast, lacked that immediacy and showed a flatter acceptance curve.
We ran them live during the demo, then refined the take‑aways in a brief post‑call memo. Did any particular moment feel out of sync for you?