Competitor price-tracking agent service for enterprise back offices
Deploy a browser-using agent that answers a recurring business question (e.g. 'what does a pizza cost at the competitor down the street, on their website with and without promos, and in their delivery app?'), fills a spreadsheet with the lowest verified price per item, and flags anything it cannot verify. Accuracy is raised not with a new model but by iterating on instructions, rules and playbooks — version one at 41% accuracy, version eleven at 97%, cost per source halved from $2 to $1, run time cut from 129 to 71 minutes.
online B2B Service / Consulting / Agency
From AI Engineer — How We Took an AI Agent From 41% to 97% Accurate - Milind Sunil Shah, Brainbase Labs at 00:19
Problem: An analyst spends hours daily opening competitor websites, picking the right store, comparing delivery vs takeaway, applying promo math and writing a spreadsheet — one wrong step yields a cell that looks finished but is wrong. The agent replicates the workflow, stores the evidence, and hands off with flags instead of guesses.
For: Enterprises with analysts doing slow, error-prone manual web research; started with a single region via the CMO's office before expanding.
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Examples
- Domino's competitor pizza-price tracking: agent went from 41% accuracy at version 1 to 97% at version 11, cost per source from $2 to $1, run time from 129 to 71 minutes, using only instruction, skill and playbook changes; now runs daily and is expanding to more markets.
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