Strategy & Planning

How to run competitive research as Small RevOps Teams

Strategy & PlanningFor Small RevOps Teams2 apps10 steps~20 min to set up

Competitive research for a 2-person RevOps team means one of you is manually poking around competitor websites, copy-pasting pricing pages into a Notion doc, and screenshotting feature matrices before the quarterly pipeline review. Meanwhile the other is fielding a Slack from the CRO asking why three deals marked 'at risk' have Gong call notes citing a competitor you've never tracked. You have no repeatable system — just an ad-hoc Google Slides deck someone built eight months ago that's already wrong. You're not a competitive intelligence team. You need the research to run itself so you can spend the hour before forecast prep on something that actually moves the number.

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Strategy & PlanningFor Small RevOps Teams2 apps10 steps~20 min to set up

Outcome

What you'll set up

A recurring competitive research automation that scrapes competitor pricing pages, product update logs, and job postings on a schedule — no API needed, no manual check-ins

A structured competitive summary view your reps can actually use in deal prep, pulled fresh before each weekly forecast call

An alert system that flags when a tracked competitor changes a pricing page, posts a new feature announcement, or starts hiring aggressively in a segment you own

The Starch recipe

Apps, data, and prompts

The combination of Starch apps, the data sources they pull from, and the prompts you use to drive them.

Apps used

Growth Analyst X Mentions Tracker

Data sources & config

Competitor websites are automated through your browser — no API needed, Starch navigates and extracts just like you would. X mentions are tracked daily via browser automation using the X Mentions Tracker app. HubSpot deal data (to cross-reference which competitors appear in lost deals) is pulled through Starch's direct HubSpot sync. Apollo contact and account data is pulled through Starch's direct Apollo sync. Gmail is synced on a schedule so Starch can scan for competitive intel in inbound threads. Salesforce and Pipedrive are reachable from Starch's integration catalog, queried live when you need to pull deal-level competitive tags.

Prompts to copy

Every Monday at 7am, visit the pricing pages for [Competitor A], [Competitor B], and [Competitor C], extract the current plan names, prices, and feature bullets, compare them to last week's snapshot stored in Starch, and Slack me a diff showing anything that changed.

Track mentions of [Competitor A] and [Competitor B] on X daily. Log each mention with the account name, follower count, sentiment, and whether it references a pain point we solve. Email me a weekly digest on Fridays at 8am with the top 10 mentions and a one-line summary of what the market is saying about each competitor.

Build me a competitive battlecard app. For each competitor I add, pull their latest public pricing, their last 5 press releases (scraped from their newsroom), and any X mentions from the past 30 days, and display it as a one-pager my reps can open before a call.

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Walkthrough

Step-by-step

1 Connect HubSpot through Starch's direct sync — this gives you a live feed of deal stages, competitor fields, and lost-reason tags so you can cross-reference research against actual pipeline impact.

2 Connect Apollo through Starch's direct sync — you'll use account and contact data to understand which prospect segments are most exposed to specific competitors.

3 Install the X Mentions Tracker app from the Starch App Store and configure it with each competitor's handle and common product keywords. It runs daily via browser automation and logs every mention with sentiment and account metadata.

4 Build a browser automation that visits each competitor's pricing page on a Monday morning schedule, extracts structured data (plan names, prices, feature lists), and stores a versioned snapshot so you can diff week-over-week. Starch automates this through your browser — no API needed.

5 Tell Starch: 'Every Friday, scan my HubSpot lost deals from the past 30 days, extract the competitor mentioned in the loss reason field, and rank competitors by how many deals they appear in. Slack me the ranked list.' This becomes your recurring loss analysis.

6 Build a competitive battlecard app by describing it in natural language: 'For each competitor I add to a list, show me their current pricing tier, a summary of their last product announcement scraped from their blog, their top 5 X mentions this week, and a count of how many open HubSpot deals have them tagged as competition.' Starch assembles this surface for you.

7 Add a Gmail scan to the automation — Starch syncs your Gmail on a schedule and can flag threads where prospects mention a competitor by name, so your reps know which deals need a battlecard before the next call.

8 Wire an alert: if any competitor's pricing page changes between Monday snapshots, send a Slack message to the #revops channel immediately with the diff. This replaces the manual 'did anyone notice Competitor B dropped their starter tier?' Slack thread.

9 Before each weekly forecast call, trigger a manual 'competitive snapshot' run that pulls the latest battlecard data for every competitor tagged in deals currently in Stage 4 or later, and outputs a one-page summary formatted for the CRO.

10 Publish the battlecard app internally so reps can look up any competitor themselves before a call — no more pinging RevOps for 'can you pull me the Competitor C one-pager real quick.'

See this running on Starch

Connect your tools, describe what you want, and the agent builds it. Closed beta is free.

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Worked example

Q2 2026 Forecast Prep — April Week 2

Sample numbers from a real run

Competitor A pricing page changes detected	3
X mentions tracked across 2 competitors (7-day window)	214
HubSpot lost deals citing Competitor B (last 30 days)	7
Open Stage 4+ deals with competitive tags	11
Hours saved vs. manual research	4

Going into the April 14th forecast call, the RevOps team ran the competitive snapshot automation Monday morning. Starch found that Competitor A had dropped their Growth plan from $299/month to $249/month — a change that had happened the previous Thursday, four days before anyone on the sales team noticed. The X Mentions Tracker had logged 214 mentions across Competitor A and Competitor B in the past 7 days; 31 of those mentioned 'pricing' and 14 mentioned 'switching.' The automated HubSpot loss analysis showed 7 deals lost to Competitor B in 30 days, all in the 50-200 seat segment — a pattern that hadn't been visible until it was pulled programmatically. The CRO walked into the forecast call with a one-page competitive summary for each of the 11 Stage 4+ deals that had a competitor tagged, built by Starch from fresh data. Total prep time for the RevOps team: under 20 minutes, down from roughly 4 hours of manual research the previous quarter.

Measurement

How you'll know it's working

Number of competitive intel updates delivered automatically per week (target: zero manual research hours)

Competitor appearance rate in Stage 4+ deals — tracked from HubSpot deal tags on a weekly cadence

Loss rate to named competitors over rolling 30 and 90 day windows, broken out by deal size and segment

Time from competitor pricing change to rep awareness (target: under 24 hours, measured against Monday snapshot diffs)

Rep self-serve rate on battlecards — what percentage of competitive lookups happen without a RevOps request

Comparison

What this replaces

The other ways teams handle this today, and how the Starch version compares.

Klue or Crayon

Purpose-built competitive intelligence platforms with polished battlecard UIs, but they cost $20k–$50k/year, require a dedicated CI program to maintain, and don't connect to your HubSpot deal data or Apollo sequences — so the insight stays siloed from your actual pipeline.

Manual Notion doc + Slack pings

Zero cost and already in place, but it's only as current as the last time someone remembered to update it, which is never the week before a big deal closes.

Google Alerts

Catches press coverage and some web mentions for free, but misses pricing page changes, X conversation trends, and has no connection to your CRM data — so you still have to manually correlate intel to pipeline.

ChatGPT + manual research workflow

Good for one-off summarization but can't run on a schedule, can't pull live data from your HubSpot or Apollo, and requires a human to kick it off every single time — which means it doesn't happen consistently.

On Starch RECOMMENDED

One platform — growth analyst, x mentions tracker all running on connected data. Setup in plain English; numbers stay current via scheduled syncs and live agent queries.

Try it on Starch →

FAQ

Frequently asked questions

We track 8 competitors. Can Starch handle that many without the automations getting slow or breaking?

Yes. The browser automation worker runs independent sessions per item, so one competitor's page failing to load doesn't block the others. You'd configure a list of competitor URLs and Starch works through them in parallel on each scheduled run. Eight is well within normal range.

Our CRM is Salesforce, not HubSpot. Does the competitive deal tagging still work?

Yes — Salesforce is reachable from Starch's integration catalog and is queried live when your apps run. You won't get the same scheduled background sync you get with HubSpot's direct connection, but for pulling deal-level competitive tags and lost-reason fields on a weekly cadence, live query is fine. Pipedrive works the same way.

Can Starch track a competitor's job postings, not just their pricing page?

Yes. If the job postings are on a public page — their own careers site, Greenhouse, Lever, Wellfound — Starch can automate navigation to that page and extract structured data through browser automation, no API needed. You'd tell Starch exactly what you want: 'visit Competitor B's careers page every Monday, extract all open roles by department, and alert me if they post more than 3 roles in Sales or GTM in a single week.'

Is Starch SOC 2 certified? We need to clear this with our security team before connecting HubSpot.

Starch is not SOC 2 Type II certified today. If your security review requires it, that's worth knowing upfront. It's on the roadmap.

The X Mentions Tracker is one of the pre-built apps — what if we want to track Reddit or LinkedIn mentions too?

Reddit and LinkedIn don't have the same public-facing mention surfaces, but you can build a custom browser automation that visits specific subreddits or LinkedIn search results on a schedule and extracts posts that mention a competitor. Starch automates this through your browser — no API needed. Describe what you want: 'visit r/sales and r/salesops weekly, search for [Competitor A], extract the top 10 posts by upvotes, and log them in a Starch table.' It's not a pre-built template but it's buildable in natural language.

We already have some competitive intel in a Notion doc. Can we connect that so Starch can pull from it?

Yes. Starch connects directly to Notion and syncs your pages and databases on a schedule. You can have Starch read from your existing competitive Notion pages and combine that context with fresh data it pulls — so the manual work you've already done becomes an input, not something you have to re-enter.