Weekly voice-of-customer report from surveys and support

Every Monday at 8am, gather all of the customer feedback from the past seven days and turn it into one consolidated voice-of-customer report. This is aggregate theme synthesis for product and CX leadership, not routing of individual items, so nothing here should act on a single response by itself.

Before analyzing anything, load last week's report so the theme taxonomy stays consistent. Use Notion Search by Title to find the most recent voice-of-customer report page, then Notion Retrieve Page as Markdown to read its contents. Extract the existing theme names and their volumes, and reuse those names wherever this week's feedback matches an existing theme. Only invent a new theme name when the feedback genuinely does not fit anything from last week. This step is what makes the week-over-week trend meaningful rather than cosmetic, since the analysis has no memory of past runs on its own. If no previous report is found, treat this as the first run and establish the taxonomy fresh.

Then collect the raw feedback from both sources. Use Typeform Retrieve Responses to pull survey and NPS submissions, filtered to the last seven days. Use Intercom Search Conversations to pull support conversations from the same seven-day window. Keep track of which source each piece of feedback came from, and for NPS submissions keep the numeric score attached to the verbatim so promoters, passives and detractors can be separated later.

Send the combined feedback to Claude using Anthropic Create Message for analysis. Structure the instruction in three blocks: context covering the product, the customer profile, the time period and which sources the feedback came from; method covering the analytical passes to run; and output format specifying the exact structure to return. Ask it to cluster the feedback into 8 to 15 recurring themes with a frequency count for each, using last week's theme names wherever they apply.

Tag every theme on two axes. The first is sentiment. The second is intent, meaning feature request, bug report, churn signal, praise, or question. Cluster NPS verbatims into three separate buckets for promoters, passives and detractors, and analyze each bucket on its own rather than as one pool, because the themes that drive a 10 are almost never the inverse of what drives a 2. Attach two or three representative customer quotes to every theme, along with a week-over-week direction showing whether the theme is rising, falling, flat, or new this week compared with last week's report.

Cap each analysis pass at 500 responses. Theme quality degrades badly past that point, with themes collapsing into each other and consistency dropping, so if the week's volume exceeds the cap, split the feedback into several passes and merge the results afterwards rather than sending everything at once. Tell Claude explicitly that if it is uncertain about a theme's grouping or a quote's intent, it should say so rather than forcing a confident label, and surface those uncertainty flags in the finished report so a human knows which groupings to check.

Write the finished report to a new Notion page using Notion Create a Page, titled with the week ending date so it is easy to find next Monday. Structure it as a table with named columns covering theme name, frequency count, sentiment, intent, week-over-week direction, and representative quotes, with the promoter, passive and detractor breakdowns in their own clearly labelled sections and any uncertain groupings called out at the end.

Finally, post a summary to Slack using Slack Bot Send a Message. Include the top five themes by volume, plus anything newly rising this week that was not present or was significantly smaller last week, and link through to the full Notion page so anyone who wants the detail can open it. Keep the Slack message short and scannable, since it is a pointer to the report rather than a replacement for it.