# Software Adoption Analytics & UX | Adoption Layer

> Track software adoption across enterprise tools and SaaS: uncover real friction through in-app user questions and streamline business workflows.

## See where your employees and users actually get blocked.

Adoption Layer logs natural-language questions asked at the exact moment of hesitation. Turn user confusion into clear action items for IT, Operations, and Product teams.

## Analytics show where users click. Not why they struggle.

A high drop-off rate on an internal form or SaaS screen does not tell you what the user intended to do. Session recordings display cursor movements without explaining the roadblock. Adoption Layer captures the user's natural-language question alongside full page DOM context. You immediately see which business rule, UI label, or button caused the friction.

- **Drop-off without intent**: A 40% abandon rate on a form tells you people left. It does not tell you which field, rule or label stopped them.
- **Session replays nobody watches**: Hours of cursor movement to find one hesitation. The context is there, but no one has time to mine it.
- **Tickets that arrive too late**: By the time a request reaches support, the user already lost twenty minutes and the original question is gone.

## From user friction to process improvement

1. **Capture live context**: Every interaction records the user's question, active URL, DOM structure, and guidance outcome.
2. **Identify recurring patterns**: Repeated queries surface confusing forms, training gaps, or documentation topics that need immediate coverage.
3. **Take action quickly**: Deploy a proactive hint, update your knowledge base, or dispatch an issue to your project backlog.

## Where adoption analytics pays off

Three patterns we see every week: a hidden business rule, a form that fails silently, a feature nobody finds. All three surface in the question log first.

- **Hidden business rules**: Users keep asking why an invoice, a request or an order is blocked. The insight names the rule and the screen, so you can surface it in the interface instead of answering the same question forever.
- **Forms that fail silently**: A validation nobody explains, a mandatory field that looks optional. The question curve spikes, you ship a hint or a label fix, and you watch the curve flatten the following week.
- **Features nobody finds**: The capability exists, the user searches for it under another name. The log shows the exact words they use, so your team can rename, move or highlight the feature where they expect it.

## Frequently asked questions

### How is this different from product analytics or session replay?

Product analytics tells you where users click and where they drop. Session replay shows you the cursor. Adoption Layer records the question the user asked in natural language at the moment of hesitation, along with the screen and the outcome. You get the intent, not just the behaviour.

### Do I need to tag events or define funnels?

No. Every interaction with the assistant is logged automatically with its URL, DOM context and result. There is nothing to instrument and nothing to maintain when the interface changes.

### How are questions grouped into insights?

The AI merges semantically similar questions on the same screen into a single insight, assigns a nature (confusing UI, business rule, bug, missing documentation) and keeps the session count and resolution rate up to date. You review the list, not the raw log.

### Does it work on third-party SaaS like Salesforce or SAP?

Yes. On your own web applications, a single script line is enough. On third-party SaaS, the managed Chrome extension captures the same questions and context without any change to the vendor's product.

### What happens to personal data in the captured context?

Personal data is masked locally in the browser before the context is sent. Only the structure of the page and the question reach our servers, hosted in Europe. You can review exactly what is stored for any session.

### Who typically uses the insights?

Product and UX teams to prioritize fixes, IT and Operations to spot training gaps on internal tools, Support and CX to see which questions they can eliminate with a hint or a documentation update.