Matomo for WordPress stores tracked data in its own tables (prefixed matomo_log_visit, matomo_log_action, matomo_log_conversion) and exposes aggregated reports through the Matomo Reporting API embedded in the plugin. SleekAI can be wired to either layer, so the chatbot's system message has named variables for top pages, traffic sources, country breakdowns, goal completions, and visit counts over a date range.

That turns the analytics dashboard into a conversation. A site owner asks which post pulled the most traffic last week, the bot answers with a real URL and a real number. A marketer asks how the newsletter campaign converted, the bot pulls the matching goal report and compares against the previous period. The Matomo UI is still there for deep dives, but daily check-ins move into chat, where the question and the answer live next to each other.

Display conditions lock the analytics bot to administrators or a custom marketing role, so visitors never see internal numbers. Conversation logging captures every question and answer in WordPress with model name and token usage, useful when teams want to audit what was asked and feed common patterns back into saved presets.

Self-hosted analytics solves the data ownership problem, but it does not solve the friction problem. Most teams running Matomo for WordPress still open the same three or four reports every morning: top pages, top sources, goal completions, and whatever campaign is in flight. Each of those is a click into a sub-report, a date picker, and a comparison toggle.

The data is right there, but the path to the answer is repetitive enough that people skip it on busy days, and on quiet days they over-index on whichever number happens to be on screen. A plain-English layer over Matomo's existing reports collapses that loop. The team asks for the answer, and the bot returns the same number the dashboard would have shown, with the same date scoping.

Nothing is invented, nothing is exported, nothing leaves the WordPress install. The Matomo UI is still the right place for deep dives and weird funnels, but daily standups, content reviews, and post-launch checks move into chat. That changes how often people actually look at their numbers, and how quickly they spot something off.

SleekAI does the wiring with point-and-click data sources, locks the widget to staff via display conditions, and stores every question in a WordPress-native conversation log, so the team can see exactly what was asked and how the model answered.