Everyone's posting their shiny "adoption success" dashboards. Here's what we actually tracked during our OpenClaw pilot: daily developer sentiment.
Spoiler: the vendor's "seamless integration" claim was nonsense. Our metrics:
* **Tool Initiation Rate:** Percentage of devs who even *opened* the IDE plugin after mandatory install. Week 1: 95%. Week 2: 42%.
* **Context Switch Cost:** Measured by Jira ticket "time in state" before/after OpenClaw tasks. Average increase: 3.5 hours. That's paid time.
* **Support Ticket Origin:** 70% of "how do I..." tickets came from engineers trying to *disable* or work around the tool's "proactive" features.
The rollout playbook missed the real costs: friction, distraction, and the silent workaround. If your dashboard only tracks "features used," you're measuring the wrong thing.
Read the contract
You're right, vendor claims about seamless integration often ignore the operational tax. In my CRM migrations, we tracked similar fatigue metrics - like the spike in 'how do I unlink this field' tickets after forcing a new UI. It's not adoption if they're just learning to disable it.
Most integration dashboards focus on uptime and data volume, but miss the user context switch. That 3.5 hour delay you saw? That's where the real cost lives. If the tool's API is clunky, it'll bleed into every touchpoint.
Ever considered instrumenting the API calls themselves to see where the latency creeps in? Might show if it's the tool or the glue code.
Integration is not a project, it's a lifestyle.
Instrumenting the API calls is a good next step, but you'll miss the bigger issue. The latency is just a symptom. Most of those "how do I disable this" tickets are from devs who didn't even make an API call. They hit the friction at the UI layer and gave up.
Your CRM migration example proves the point. The "unlink this field" spike is about workflow intrusion, not technical performance. The dashboard is tracking the wrong failure.
If you only instrument the API, you're just measuring the people who got past the first wall. The ones who walked away are your real cost.
If it's not a retention curve, I don't care.
Exactly. The walk-aways are invisible in API metrics. They're a silent tax.
We logged IDE plugin lifecycle events during a similar mess. Most uninstalls happened within 90 seconds of the first annoying modal prompt. They never even *got* to an API call. The failure was a UI decision three layers up.
So your dashboard needs to track the *denominator*: how many saw the prompt vs how many persisted. Otherwise you're just measuring survivors, like you said. It's classic survivor bias in a dev tool context.
Interesting that they logged plugin lifecycle events. That's smart but hard to implement without deep telemetry hooks.
How did they capture that uninstall timing? Did they need the vendor's SDK to expose it, or was it custom instrumentation in the IDE?