Copy-paste formulas for competitor customer research in Google Sheets
Paste a formula into row 2, test it on a few rows, then drag down to run the workflow across your spreadsheet.
Competitor-fit research
A: company · B: source notes · C: competitor
=GPT("Research whether this company likely uses " & C2 & ". Company: " & A2 & ". Source notes: " & B2 & ". Return evidence for/against, confidence, and one displacement angle. If evidence is weak, say Needs manual research.")
Switching-signal score 1-5
A: company · B: source text · C: our offer
=GPT("Score 1-5 how likely this company is to switch from a competitor. Company: " & A2 & ". Source text: " & B2 & ". Our offer: " & C2 & ". Return score, the strongest switching trigger, confidence, and what to verify.")
Displacement opener
A: contact/role · B: switching trigger · C: offer · D: tone
=GPT("Write an outreach opener for " & A2 & " referencing this switching trigger: " & B2 & ". Offer: " & C2 & ". Tone: " & D2 & ". Stay factual, no negative claims about competitors, under 70 words.")
QA missing-data flag
A: AI output · B: source text · C: required fields
=GPT("QA this output: " & A2 & ". Source text: " & B2 & ". Required fields: " & C2 & ". Flag missing data, risky assumptions, and any unsupported claim about a competitor. Return pass/review/fail.")
Short answer
Competitor Customer Research in Google Sheets means using AI formulas to research a competitor’s likely customers and build displacement angles without leaving the spreadsheet. GPT for Sheets runs prompts across your rows to produce research summaries, fit scores, and personalized next steps in adjacent columns, so the whole workflow stays reviewable.
Fastest path: Install GPT for Sheets → add your source columns → paste a formula from the formula section → review 10 rows → fill down the sheet.
This page is for B2B sales and marketing teams running displacement plays who keep their lists in spreadsheets and want faster, reviewable AI research at scale.
Workflow
A practical sheet for this workflow usually has these columns:
| Column | What to put there | Why it matters |
|---|---|---|
| A | Company | Stable row anchor for each record |
| B | Source notes: website copy, export, CRM fields, form data | Keeps AI grounded in inspectable evidence |
| C | Offer or product | Sharpens relevance and scoring |
| D | Target signals (competitor mentions, tech stack hints, reviews, case studies, switching signals) | Defines what the AI should look for |
| E | AI research summary | First useful interpretation of the row |
| F | Fit score and label | Sorts the list for routing |
| G | Outreach opener or next action | Turns research into execution |
| H | QA flag | Stops unsupported claims before outreach |
Step-by-step setup
- Start with 10 representative rows before filling down hundreds.
- Keep raw source fields unchanged so you can audit the AI output.
- Run one formula to create a research summary, then inspect weak rows.
- Add constraints: max length, required format, and what to do when data is missing.
- Add a QA formula that flags missing facts and unsupported assumptions.
- Fill down once the prompt works on your sample rows.
Why run this workflow in Google Sheets
Heavier GTM platforms can do this, but many B2B sales and marketing teams running displacement plays would rather not move every list into a separate workspace. GPT for Sheets keeps research a competitor’s likely customers and build displacement angles in the spreadsheet your team already shares, so source data, AI output, and QA labels live side by side and stay auditable. Named third-party products are trademarks of their owners; any comparison here is factual and non-defamatory.
Use cases
- Displacement lists: turn a list of suspected competitor users into researched, prioritized rows.
- Switching triggers: surface renewal, pricing, outage, or review signals worth referencing.
- Personalization: draft factual openers that lead with the prospect’s situation, not competitor bashing.
- Win-back overlap: combine with churned-customer research to prioritize re-engagement.
- QA: flag any unsupported or negative claim about a named competitor before sending.
Best for / not best for
Best for: B2B teams that already track suspected competitor users in a sheet and want reviewable AI research and factual displacement angles.
Not best for: teams expecting confirmed, licensed customer lists of a competitor; treat all inferences as directional and verify before outreach.
The strongest use case is when you already have a list and need structured, reviewable AI output. GPT for Sheets supplies the research and QA layer; you supply lawful, sourced data.
Internal links and next workflows
- GPT for Sheets product page
- GPT for Sheets pricing
- Upgrade GPT for Sheets
- Account research automation in Sheets
- AI lead scoring formulas for Google Sheets
- B2B sales account research in Sheets
Safety, compliance, and data quality
AI output should be treated as a draft. Use lawful public and business data only, keep source columns visible, store source URLs or dates when relevant, and verify contact details before outreach. Do not infer sensitive attributes. Follow consent, deliverability, and local compliance rules.
Frequently Asked Questions
How does it know which companies use a competitor?
It does not know for certain. It weighs public signals you paste in (reviews, case studies, tech mentions, job posts) and returns evidence with a confidence level. Treat it as a lead, not a fact.
Is competitor research like this allowed?
Researching publicly available business information is common in B2B sales. Keep claims factual and non-defamatory, avoid disparaging competitors in outreach, and respect trademarks and terms of service.
Can it avoid trash-talking competitors in openers?
Yes. The opener prompt instructs the model to stay factual and avoid negative claims; still review drafts, because the prospect’s experience, not the competitor, should be the hook.
Should I trust every AI output automatically?
No. Use the QA column to flag unsupported claims and missing evidence, and verify high-value accounts manually before reps engage.
Start competitor customer research in Google Sheets
If your team already works in spreadsheets, install GPT for Sheets and run these formulas where your companies that may use a competitor already live.