Prepare your next client call with answers from Piano Analytics. Connect your account through Catchr, then use ChatGPT or Claude to explore audience engagement, conversion results and media experience.
For freelancers and agencies, start with the available fields, choose the measures that matter to your client and ask focused reporting questions.
“Compare paid media performance across my client accounts and flag the biggest changes.”
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Piano Analytics uses a dynamic schema. Discover the columns available for your connected account before choosing metrics and breakdowns. Confirm that your selected fields can be queried together and that the requested date range is supported.
Explore Users, Visits Per User and Time Spent Per User to give client conversations more context than audience size alone. Action Clicks, Download Clicks and Navigation Clicks can add detail about recorded interactions.
Discover whether Source Medium and Source Campaign are available alongside your chosen metrics, then use supported combinations to compare engagement across acquisition sources.
Use available columns such as Conversions, Purchased, Sales and Page To Purchase Rate to build a focused outcomes report. Sales Per User and Sales Per Visitor offer additional measures to examine when exposed by the account.
Select compatible breakdowns such as Source Campaign or Source Campaign Group. Keep the source metric names visible and confirm their definitions before presenting totals or interpreting rates.
Review Sessions, Sessions Buffering, Sessions Rebuffering and Average Bufferings to investigate the recorded media experience. These measures can help identify where a client should look more closely at playback conditions.
Discover available breakdowns such as AV Broadcaster and AV Broadcasting Type, then select a compatible combination to compare results. Treat differences as points for investigation, not proof of their cause.
A focused analysis, a recurring report and a conversational query serve different client needs. Choose the approach that fits the question, using the Piano Analytics fields available to your account.
Use source-focused analysis to investigate a specific result, a report to maintain a consistent client view, and Catchr MCP to ask follow-up questions. In each workflow, check field availability and definitions before comparing results.
Connect Piano Analytics to Catchr using API-key authentication and select the relevant account. Choose ChatGPT or Claude through Catchr MCP as your AI destination.
Start by asking which columns are available. Select your metrics and breakdowns, confirm the supported date options and submit your first reporting question.
Replace the bracketed values with your client details. Each prompt starts with field discovery so you can choose columns supported by the connected account before running the analysis.
Using Catchr, which acquisition sources show stronger audience engagement for [account] during [start date] to [end date]? First discover available columns and date options. Offer Users, Visits Per User, Time Spent Per User and Source Medium if available, and ask me to select a compatible set. Query the selected columns, show the results by source and flag rows below [minimum users] so small audiences are visible in the comparison.
Copy promptUsing Catchr, how do purchase and conversion outcomes compare across campaigns for [account] during [start date] to [end date]? Discover available columns, including Conversions, Purchased, Sales, Page To Purchase Rate and Source Campaign where exposed. Ask me to choose compatible metrics and a campaign breakdown, then query them for the supported date range. Show a comparison table and identify questions to raise with the client, keeping each metric separate and stating any definition that needs confirmation.
Copy promptUsing Catchr, where should we investigate media buffering for [account] during [start date] to [end date]? Discover the available columns and offer Sessions, Sessions Buffering, Sessions Rebuffering, Average Bufferings, AV Broadcaster and AV Broadcasting Type where supported. Ask me to select compatible metrics and one breakdown, then query the results. If Sessions Buffering is selected, flag rows above [buffering session threshold]. Summarize the observed differences without claiming a cause.
Copy promptUsing Catchr, how did recorded interactions change for [account] between [first period start] to [first period end] and [second period start] to [second period end]? Discover available columns and supported date options, then ask me to select from Action Clicks, Download Clicks, Exit Clicks and Navigation Clicks where available. Query the selected metrics for both periods, show absolute and percentage changes where calculable, and flag changes beyond [percentage change threshold]. Keep the interaction types separate and note any difference in period length.
Copy promptConnect Piano Analytics in Catchr using API-key authentication and select the relevant account. Then choose ChatGPT or Claude through Catchr MCP and begin by discovering the columns available for your reporting question.
The schema is dynamic, so discover your account’s columns first. Available fields may include Users, Conversions, Sales and media buffering metrics, with breakdowns such as Source Medium or AV Broadcaster. Select a compatible combination from the discovered fields.
Where available, query Sessions Buffering, Sessions Rebuffering and Average Bufferings alongside compatible AV breakdowns. Use the results to identify differences worth investigating; those differences alone do not establish why buffering occurred.
Confirm the date options supported by the connected account before requesting a comparison. Use the same selected metrics and compatible breakdowns for both periods, and account for differences in period length. Check available history and time grouping before promising a particular reporting view.
Connect your sources to Catchr, add the MCP server to your AI assistant, and ask about the work that matters now.
