Prepare for client calls with answers from your connected Data Blend data. Use Catchr MCP in ChatGPT or Claude to explore available columns, choose what matters for the client, and ask focused reporting questions.
Start with the blend’s actual fields, then compare periods or investigate selected values without preparing another export for each question.
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Each blend determines what you can report on. Discover its available columns before choosing measures or breakdowns, and use supported date dimensions to organize the results.
Start by identifying the columns exposed by the connected blend. Select the fields that answer your client’s question instead of assuming every blend includes the same measures or categories.
Before calculating totals or averages, confirm what the selected columns represent and how they should be summarized.
Use Date, Year week, or Year month to organize selected values across reporting periods where those dimensions are available. Year Quarter also supports a broader review for client planning.
Keep the selected columns and aggregation consistent between periods so the comparison is useful in a client discussion.
For blends with sufficiently detailed timestamps, explore Hour of the day or date dimensions that include hours, minutes, or seconds. These can help locate when a change occurred within a reporting period.
Check the underlying time detail first. A blend containing daily values cannot support a meaningful hourly breakdown simply because an hourly dimension is listed.
A focused analysis, a recurring report, and a question through Catchr MCP serve different client needs. Choose the method that fits the deliverable and the columns available in your blend.
Use Looker Studio when clients need a repeatable Data Blend report. Use Catchr MCP when you need to explore the same connected blend through specific questions, with columns and reporting periods made explicit.
Connect Data Blend in Catchr using API-key authorization, select the relevant connected blend, and connect your AI destination through Catchr MCP. In ChatGPT or Claude, begin by asking which columns are available before requesting a client summary or period comparison.
Begin with column discovery. For the remaining prompts, replace the column placeholders with fields found in your blend and choose the client’s reporting dates.
Using Catchr, inspect the available columns in [connected blend] for [client account]. Which columns could support [reporting question]? List the available date dimensions and any field information returned, then ask me to confirm the columns and aggregation before calculating results.
Copy promptUsing Catchr, compare [selected numeric column] in [connected blend] for [client account] between [first date range] and [second date range], using [confirmed aggregation] and Date. Show both period values, the absolute difference, and the percentage change where the baseline permits it. Note missing dates or incompatible time detail that would limit the comparison.
Copy promptUsing Catchr, examine [selected numeric column] in [connected blend] for [client account] from [start date] to [end date]. Using [confirmed aggregation], group by Date and [selected grouping column], and return the groups above [threshold]. Show the values and dates so I can decide what to investigate before the client call.
Copy promptUsing Catchr, summarize [selected columns] from [connected blend] for [client account] between [start date] and [end date], grouped by Year month. Apply [confirmed aggregation for each column], produce a monthly table, and draft three client talking points based on the observed changes. Identify questions the available columns cannot answer and avoid inferring causes from the totals alone.
Copy promptThe available measures depend on the columns in your connected blend. Discover those columns first, then select the values and aggregation needed for your report. Do not assume a measure exists across every blend.
Connect Data Blend in Catchr using API-key authorization, choose the relevant blend, and connect ChatGPT or Claude through Catchr MCP. Make your first question a request to inspect the available columns and date dimensions.
Data Blend includes date dimensions such as Year week and Year month. Use them where available for your blend, with consistent columns and aggregation across periods. The comparison depends on the dates and detail present in the data.
Active Data Blends can connect to Looker Studio for reporting, while Catchr MCP lets you ask questions about connected data in ChatGPT or Claude. Use matching columns, date ranges, and aggregation when checking an answer against a report.
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