Prepare your next client review with a clearer view of TV spot performance. Use Catchr MCP to ask Claude or ChatGPT about connected Adalyser data, from client cost and attributed sales to broadcast channels and device response.
For freelancers and agencies, these questions can turn spot-analysis data into focused talking points about where costs and sales outcomes differ.
“Compare paid media performance across my client accounts and flag the biggest changes.”
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Build your Adalyser analysis around the client, broadcast period and business question. Use channel, product, market and break position to give cost and sales figures useful context.
Bring Client Cost, Sales Count and Sales Value into the same review to understand spending alongside revenue attributed to TV spots. Use Cost per Lead, Cost per Appointment and Cost per Sale to answer different efficiency questions.
Lead Sale Conv Rate and Avg Sales Value add context to the sales results. Keep these measures distinct: Adalyser's CPA represents cost per appointment.
Break down spot-analysis results by Channel and Position to examine differences between broadcasters and break positions. Product, Ad Group, Market and Platform provide additional ways to focus a client review.
Use Week Start to compare broadcast weeks, with Client Id and Client Name keeping the analysis tied to the selected client.
Compare desktop and mobile attributed sales, sales value and cost per lead. These breakdowns help you discuss how response to TV spots differs by device.
Review sales and sales value credited to direct traffic, organic search and paid search. You can also compare sales value from new-user and returning-user actions, keeping attribution categories separate rather than treating them as additional revenue.
A focused TV analysis, an assembled client report and a Catchr MCP conversation serve different parts of the same review. Choose the approach that fits whether you need to investigate spot results, present selected measures or ask follow-up questions.
Use a focused analysis to investigate a TV question and a report to present the selected results. Catchr MCP supports questions about connected Adalyser data, such as which channels have higher sales value or how device response differs within a chosen period.
Adalyser connection credentials are a username and password. Start by checking that the intended client and campaign scope can be selected in Catchr, then connect your AI destination through Catchr MCP.
Campaign ID selection remains an unresolved setup limitation: the Adalyser contract needed to populate that selection has not been confirmed. Verify the available scope before relying on a campaign-level query.
Replace the bracketed values with your client's scope, dates and review thresholds. Each prompt requests a specific analysis of Adalyser data and asks for checks that help keep the results interpretable.
Using Catchr, for Adalyser client [client ID] from [start date] to [end date], which broadcast channels have a cost per sale above [cost-per-sale threshold]? Group Client Cost, Sales Count and Sales Value by Channel. Calculate grouped cost per sale as total Client Cost divided by total Sales Count, identify channels with no attributed sales separately, and rank the remaining channels by cost per sale.
Copy promptUsing Catchr, for Adalyser client [client ID] from [start date] to [end date], how do desktop and mobile attributed sales and sales value compare by Product? Show Sale Sources Desktop, Sale Sources Mobile, Sale Value Sources Desktop and Sale Value Sources Mobile. Calculate sales value per attributed sale for each device where the sales count is positive, and flag products with fewer than [minimum sales] on either device.
Copy promptUsing Catchr, for Adalyser client [client ID] from [start date] to [end date], how does attributed sales value from direct traffic, organic search and paid search vary by Week Start? Show the sales count and sales value for each origin, calculate each origin's share of the combined sales value of those three origins, and identify the largest week-to-week changes. Keep overall Sales Value separate and do not assume these origins cover every attributed sale.
Copy promptUsing Catchr, for Adalyser client [client ID] in [market] from [start date] to [end date], how do break positions compare within each Channel? Group Client Cost, Sales Count and Sales Value by Channel and Position. Show cost per sale calculated from grouped cost and sales totals, flag groups below [minimum sales], and summarize the differences worth discussing with the client without claiming that break position caused them.
Copy promptYou can ask about TV spot costs, attributed sales and sales value by dimensions such as channel, product, market and break position. Device and traffic-origin breakdowns support more focused questions about the response attributed to those spots.
Adalyser uses a username and password for the connection. Check that your intended client and campaign scope is selectable in Catchr before querying it through MCP. Campaign ID selection is still an unresolved setup limitation, so complete campaign selection should not be assumed.
In this Adalyser schema, CPA means cost per appointment. Use CPL for cost per lead and CPS for cost per sale. When combining rows, calculate cost per sale from total Client Cost and total Sales Count rather than taking a simple average of row-level rates.
Reporting queries do not modify Adalyser campaigns or source data.
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