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AI agent for market research managers

Pricing Research Analysis Agent

A validated set of price scenarios from research data

Pricing Research Analysis Agent: what goes in, what the agent does and what you get

What it does

Price research guides pricing decisions, but results are often misread and data problems ignored. This agent loads the study data and removes inconsistent answers, such as someone calling a price both too cheap and too expensive. It runs the planned analysis to find acceptable price ranges and demand at each price. It checks results for sense: demand should fall as price rises, and segments should be large enough. If results break these checks, it looks for data or setup problems and reruns. A segment with a flat curve is reported as price insensitive with a sample size caution. It drafts price scenarios with expected revenue. The product or research lead approves recommendations.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Study data delivered 2 USES A TOOL Load data and remove inconsistent answers 3 DOES Run the planned price analysis by segment 4 CHECKS THE RESULT Do demand curves fall with price and bases exceedthe minimum? If not: look for data or design errors, fix and rerun.Back to step 2. 5 USES A TOOL Calculate revenue and margin for each price scenario 6 DOES Draft scenario summary with cautions 7 YOU APPROVE Lead approves recommended price range 8 RESULT Pricing readout delivered
Read the steps as a list
  1. Study data delivered
  2. Load data and remove inconsistent answers
  3. Run the planned price analysis by segment
  4. Do demand curves fall with price and bases exceed the minimum?If not: look for data or design errors, fix and rerun. Back to step 2.
  5. Calculate revenue and margin for each price scenario
  6. Draft scenario summary with cautions
  7. Lead approves recommended price rangeThe agent waits here for your OK.
  8. Pricing readout delivered

How it decides

It accepts the model only when demand falls with price and segment bases are large enough, then compares revenue across scenarios.

  • Minimum base of 150 per segment
  • Inconsistent answers removed before analysis
  • Scenarios shown with margin, not just revenue

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Analysis method
  • Minimum base size
  • Price points to test
  • Margin assumptions

What keeps you in control

It always asks you first

  • Any price change recommendation

Hard limits

  • Does not change live prices
  • Shows uncertainty for small bases

It stops when

  • Done: readout delivered
  • Stop: study design does not support the question

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensThe first run showed demand rising from 29 to 35 dollars for small firms. The sense check failed, so the agent searched for setup problems and found price levels coded in the wrong order for one survey version. After fixing and rerunning, demand fell as expected and the acceptable range was 24 to 33 dollars. The research lead approved three scenarios.

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