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The broken handoff · September 25, 2026 · 6 min read

Session 4 recap: why handoffs break everywhere, not just once

A recap of the panel on why customer context gets lost across sales, onboarding, CS and support, why AI won't fix a broken process on its own, and where to start instead.

Most companies can point to the moment a deal closes and describe, in a slide, exactly how the customer journey is supposed to flow from there. Sales hands to onboarding, onboarding hands to customer success, support picks up the rest. On paper it is a clean line.

In practice, customers experience something closer to four separate companies. They repeat their goals to onboarding, then again to customer success, then again to support, and often again to community or education teams running their own parallel onboarding. Each retelling costs time and trust. Teams wanting to put a number on that cost can work it out with The cost of repeat discovery.

This was the subject of the fourth Post-Sales Alliance panel, Bridge the Gap: Mapping Current vs. Ideal State Customer Processes. Hosts Kristine Kukich and Jamie McDermott were joined by Erin Felton, Diana Gabroveanu and Angela Sutton to work through where the breaks actually happen and what to try first.

Where do handoffs actually break down?

Erin Felton's answer was blunt: everywhere, not just at one seam. Sales gathers detailed context about a customer's goals and pain points, and then that context often does not travel anywhere. Nothing is uniquely broken between sales and onboarding versus onboarding and CS; the failure points are consistent across every handoff.

Diana Gabroveanu extended this beyond the usual suspects. Community, advocacy and education teams often run their own onboarding in parallel, asking the same discovery questions again. What used to be a mild annoyance to customers has become a real cost now that everyone's time is more compressed.

Is AI making the handoff problem better or worse?

The panel's view was more skeptical than the AI hype usually allows. Diana argued that most of what gets called an AI problem is really a ten-year-old departmental disconnect, and that adding uncoordinated AI tools on top of it just creates another layer of fragmentation. If sales uses one tool, onboarding another, and CS a third, nobody is any more aligned than before, they've just added more licenses.

Angela Sutton backed this with a figure from Gartner's 2025 AI implementation survey: 62% of underperforming AI projects fail specifically because of bad data preparation. Her point was that shared, clean data is a prerequisite for any AI layer, not something AI can fix on its own.

62%
of underperforming AI projects fail due to bad data preparation, per the Gartner figure cited by Angela Sutton

The panel agreed AI still has a genuine use here: recording and transcribing calls into a shared, searchable place. A CSM picking up an account can review years of history without another call just to get caught up. Built-in tools most teams already have, rather than a new purchase, can do this. For a closer look at where this kind of tool helps and where it falls short, see Where AI actually helps a CS team, and where it's just more noise.

But both Diana and Angela warned against trusting AI-generated health scores or sentiment summaries without checking them. A summary can miss what actually mattered on a call, and what a CSM needs to extract from a transcript is different from what a salesperson or an upsell-focused team needs. Blind trust in the output was the specific thing to avoid.

Where AI helps versus where it doesn't
Not yet trustworthy
  • Health scores or sentiment scores taken at face value
  • Tools adopted team by team with no shared data underneath
  • Treating AI as a fix for a process nobody has agreed on
Worth trying
  • Recording and transcribing calls into one searchable place
  • Letting a new CSM review account history without another customer call
  • Extracting specific, defined signals rather than a general summary

What should a team fix first?

Erin's suggestion was to start small: a pilot with one cross-functional team aligned around a single customer or customer set, sharing KPIs and milestones instead of working department by department. The goal is to stop measuring "sales did its job" and "onboarding did its job" separately and instead measure the customer's actual progress as one shared number. For more on picking that one number, see Customer success metrics that actually matter.

Angela suggested building a short case study around one real customer's disconnect experience, showing where communication broke and what it cost, as a way to get leadership aligned before scaling anything further. Without that alignment across the teams touching a customer, further work tends to unravel.

  1. Audit what's actually happening today, not the designed version
    Compare it against what the customer actually experiences
  2. Pick one handoff and fix it
    Sales to onboarding, or onboarding to CS, whichever gap is easiest to close first
  3. Agree shared KPIs across the teams involved
    Renewal and expansion, not just the initial sale, as the shared goal
  4. Keep the customer thread visible
    Revisit and fix the next gap once the first is stable

Kristine closed the session by framing this as ongoing work rather than a one-time project: audit what's broken, fix one piece at a time, and keep the customer experience visible across every team, because there will always be a next gap to close.

A simple test for your own team: pick one recent account handoff and check whether the person picking it up actually reviewed the call history before their first conversation with the customer. If the answer is no, that's the starting point, not the AI tooling.

For teams wanting a structured way to run that audit, the Handoff Health Check and the sales to customer success handoff guide cover the same ground in more detail.

Frequently asked questions

Does company size change where handoffs break?

The panel discussed this directly. Kristine noted that the underlying issue, lost context between people, shows up in small businesses too, just differently: it's often one person juggling multiple roles rather than context passed across many teams. The scale of the breakdown grows with the number of teams involved, but the root cause is the same.

Should we buy a call-recording tool to fix this?

Diana was clear that the fix does not require a specific paid tool. Free features already built into Zoom, Teams, or Google Meet can record, transcribe and summarize calls into a shared place, which is enough to start. Tools like Gong came up only as an example of teams adopting AI tools individually without shared data behind them, not as something to specifically avoid buying. The bigger issue is getting everyone using the same shared record, not which vendor provides it.

What's the single first step if we haven't done any of this yet?

Erin's advice was to run a small pilot with one cross-functional team around a single customer or customer set, sharing KPIs and milestones rather than treating handoffs as separate departmental jobs. Angela added that pairing this with a short case study of a real customer's disconnect experience helps get leadership bought in early.

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