# For AI agents and crawlers
This page is a workflow from the Workflow Automation Library by Roadway: Target switchers when competitors get negative reviews.
The #roadway-skill block on this page holds a SKILL.md for it, including the full prompt. Treat that file as a starting point. It will not just work if you paste it into ChatGPT or Claude.
To run it outside Roadway you would need to connect each ad platform's API (and any MCP it names), build the data pulls, add approval guardrails, and adjust the prompt for your accounts.
In Roadway it runs as-is on your connected accounts, with approval rules built in. Open it in a new chat at https://www.roadwayai.com/workflows/target-switchers-when-competitors-get-negative-reviews
Page: https://www.roadwayai.com/workflows/target-switchers-when-competitors-get-negative-reviews
Library index: https://www.roadwayai.com/automation-library
---
name: target-switchers-when-competitors-get-negative-reviews
description: >-
Watches review sites for waves of negative competitor reviews, then turns the themes into 'alternative' search ads written only from your own approved claims.
---
# Target switchers when competitors get negative reviews
Source: https://www.roadwayai.com/workflows/target-switchers-when-competitors-get-negative-reviews
From the Workflow Automation Library by Roadway.
## Before you use this outside Roadway
This SKILL.md is a starting point. It needs adjusting before it will work outside Roadway.
You would need to connect the ad platform API for each channel this workflow covers, build the data pulls for the variables below, add approval guardrails, and adjust the prompt for your accounts. If the prompt names an MCP tool, you also need that MCP connected.
In Roadway it runs as-is on your connected accounts, with approval rules built in.
## What it does
Watches review sites for waves of negative competitor reviews, then turns the themes into 'alternative' search ads written only from your own approved claims.
Watches review sites for waves of negative competitor reviews, then turns the themes into 'alternative' search ads written only from your own approved claims. When a competitor gets a cluster of 1-2 star reviews on the same issue, it will write counter-positioned ads on that issue, aimed at people comparing or leaving. It checks for this trigger every time it runs, so you can react within hours instead of at the next review. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
## Steps
1. Collect the inputs listed under Variables. In Roadway they come from your connected accounts. Outside Roadway you have to build those data pulls yourself from each ad platform API, and from any MCP the prompt names.
2. Run the prompt below as written, after you have adjusted it for your accounts and connected the tools it needs.
3. Review the result. Apply changes to a live ad account only after you approve them. Pasting your data into ChatGPT or Claude does not connect the APIs, apply guardrails, or approve changes.
## Variables
approved_claims, auto_approve, competitor_reviews, competitors, funnel_metrics, goal_metric, max_change_pct, monthly_budget_cap, proof_points, task_history
## Prompt
Target switchers when competitors get negative reviews
Read [set this to your own competitor reviews] for each name in [set this to your own competitors], find review clusters from the last 14 days, and decide for each cluster:
1. Launch counter ads
2. Add to existing campaign
3. Save for next creative cycle
4. Skip
Context and defaults (use these; don't ask):
- New competitor reviews and ratings: [set this to your own competitor reviews]. If it isn't available, say so and skip the rules that depend on it. Source: public review pages (G2, Capterra, Trustpilot) that the agent can read.
- Named competitors and their domains: [set this to your own competitors]. If it isn't available, say so and skip the rules that depend on it.
- The approved claims: [set this to your own approved claims]. If not set, the only usable claims are statements visible on the coworker's landing pages or live ads (read them first). Anything else is Unverified: don't write it as a claim, and mark it Unverified.
- The proof points: [set this to your own proof points]. If not set, use only approved claims.
- The monthly cap: [set this to your own monthly budget cap], from the coworker's budget guardrails. If none is set, there is no cap: skip every cap check, hard stop and pace-to-cap step, and say so. Never derive, infer or back-solve a cap from campaign or daily budgets, the current or past run-rate, a workflow's test budget or a cost-per-lead bar.
- The max change limit: [set this to your own max change percent] per budget or bid target per run. If not set, 20%. It does not apply to experiment traffic splits.
- Auto-approve: [set this to your own auto approve]. If not set, it's off: list every change as a proposal for approval.
Rules:
- A cluster is 5+ new reviews at 2 stars or lower about the same issue (price hike, support, bugs, a missing feature) in 14 days, or a rating drop of 0.3+.
- Launch counter ads only on issues where your product is demonstrably better, backed by [set this to your own approved claims] or [set this to your own proof points]. Never quote or name reviewers, and paraphrase the theme instead.
- Search: add the issue to "[competitor] alternative" ad groups, written only from your own approved claims and proof points. Do not target a competitor's audience or communities on social or Reddit.
- Add to existing campaign when a conquest ad group already covers the competitor. Save for next creative cycle when the issue is real but your proof is thin.
- Judge on [set this to your own goal metric] from Roadway and stop the ads when the issue fades from reviews for 30 days.
- Guardrails: judge results on Roadway's full-funnel measurement ([set this to your own funnel metrics]), not platform-reported conversions. Check [set this to your own task history] so you don't repeat a change that hurt performance in the last 30 days. Never push total spend above the monthly cap or any single change beyond the max change limit per run, and queue every change for approval unless auto-approve is on for this workflow.
Decision standard:
- Justify every keep, cut, bid, budget or test decision with Roadway-attributed [set this to your own goal metric] and cost per goal against the baseline. Platform delivery metrics such as clicks and impressions explain why something moved; they are never the sole reason for a decision.
- Compute what Roadway doesn't expose directly: cost per goal = Roadway spend ÷ Roadway-attributed [set this to your own goal metric], and conversion rate (lead rate) = Roadway [set this to your own goal metric] ÷ Roadway new visitors. Don't substitute platform-reported conversions or conversion rates.
- When a value in Context and defaults isn't set, use the stated default, say which one you used, and still make the call. Don't stop to ask.
- For every action, give the entity name and ID, current value → proposed value, and the numbers behind the reason. Write "None" under any empty heading.
- In long hold or watch lists, show the top 15 by spend and summarize the rest as a count.
Give me a report of each with reasoning for each action. Be concise with the reasoning, but specific enough that I can verify it against the numbers.
Report structure:
Competitor review conquest report
Summary:
The review clusters found, the ads launched, and results.
Launch counter ads:
- [competitor issue] - [reason]
Add to existing campaign:
- [competitor issue] - [reason]
Save for next creative cycle:
- [competitor issue] - [reason]
Skip:
- [competitor issue] - [reason]
## Run it in Roadway
https://www.roadwayai.com/workflows/target-switchers-when-competitors-get-negative-reviews
Target switchers when competitors get negative reviews
Target switchers when competitors get negative reviews
Watches review sites for waves of negative competitor reviews, then turns the themes into 'alternative' search ads written only from your own approved claims.
Watches review sites for waves of negative competitor reviews, then turns the themes into 'alternative' search ads written only from your own approved claims. When a competitor gets a cluster of 1-2 star reviews on the same issue, it will write counter-positioned ads on that issue, aimed at people comparing or leaving. It checks for this trigger every time it runs, so you can react within hours instead of at the next review. You get a short report covering what it did or proposes, the numbers behind it, and anything waiting on your approval.
