Building a €39/mo competitor pricing intelligence tool — the research that convinced me it could work
Hey IH 👋
I'm building JABB Watch, a micro-SaaS that monitors competitor pricing pages and sends weekly AI-interpreted summaries. I want to share the research behind it because I think the process is more interesting than the product right now.
The problem I kept seeing
I work with small SaaS and e-commerce teams. One pattern kept coming up: competitors would change their pricing — raise prices, restructure tiers, kill free plans, launch new bundles — and the team wouldn't notice for weeks. Sometimes months.
When they finally noticed, the conversation was always: "Wait, when did this happen? What does this mean for us?"
The market gap
I spent a week researching every tool in this space. Here's what I found:
Free tools (Distill, Visualping): They tell you "something changed on this page." That's it. No context, no interpretation, no "what does this mean for YOUR business." You get a screenshot diff and an email. For simple monitoring, they work. But going from "a pixel changed" to "your main competitor just raised their enterprise tier by 16%" — that step is entirely on you.
I actually signed up for Visualping's free tier and tested it. Onboarding is fast, but the output is generic. Their premium AI interpretation costs $3,000/year. For a 10-person SaaS company, that's hard to justify for pricing intel alone.
Enterprise tools (Crayon, Klue, Kompyte): Fantastic if you're a 500-person company with a competitive intelligence team and a $20K+ annual budget. But for a 5-50 person company that just wants to know when competitors change pricing? Complete overkill. And the 4-8 week onboarding is a non-starter.
Pricing intelligence (Price2Spy, Prisync): Built for e-commerce catalog tracking — thousands of SKUs, MAP enforcement, dynamic repricing. Different use case entirely.
The gap: Nobody offers AI-interpreted, business-contextualized competitor pricing intelligence at a price point a small team can justify.
What I'm building
JABB Watch fills that gap:
- You tell us about your business, your products, and your top 5 competitors
- We monitor their pricing pages twice a week
- Every Friday, you get one email: what changed, why it matters for YOUR business, and what to consider doing about it
The "for YOUR business" part is the key differentiator. We ask about your business context during onboarding and use it to interpret every change. This isn't "Competitor X changed a number on their page." It's "Competitor X raised their Teams tier by $5/seat, which makes your equivalent plan 22% cheaper — consider whether to close the gap or lean into the price advantage."
The numbers
- Pricing: €39/month
- Target customer: SaaS and e-commerce teams, 5-50 employees
- AWS costs so far: €0.15 total (DynamoDB, CloudFront, S3, Lambda)
- Tech stack: Serverless AWS, Terraform, Next.js. The monitoring engine uses Claude for AI interpretation.
What I'm worried about
Being transparent about risks:
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"Good enough" competition: If a prospect just wants "tell me if anything changes," Visualping's free tier is sufficient. Our pitch has to clearly communicate why AI interpretation is worth €39/mo over free screenshot diffs.
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Weekly cadence: We send reports weekly (Fridays). If a competitor launches a flash sale on Monday, you learn about it Friday. Planning to add daily alerts soon.
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Public pages only: We can't monitor pricing behind login walls or dynamic pricing. For SaaS companies with public pricing pages, this is fine.
What I'd love feedback on
- Does the pricing feel right? €39/mo for 5 competitor pages monitored weekly.
- Would you rather pay more for daily monitoring, or is weekly sufficient for pricing decisions?
- If you're in a SaaS/e-commerce team: how do you currently track competitor pricing?
Happy to answer any questions about the research, the tech, or the business model.
— Jonatan
Great write-up on the market research! Pricing intelligence is such a valuable niche, especially for other SaaS founders. As I'm currently figuring out the pricing tiers for my own tool (AI-powered infra automation), your focus on 'weekly AI-interpreted summaries' really resonates. It moves it from just data to actual insights. One question: how are you handling anti-scraping measures on more complex competitor pages? Rooting for JABB Watch
Thanks @bhwoo48, appreciate that! Good question on anti-scraping. Honestly, for our target use case it's less of an issue than you'd think — most SaaS pricing pages are public, static, and designed to be found by Google. They want people to see their pricing. So we're rarely hitting aggressive bot protection.
That said, we do use headless browsers with realistic request patterns for pages that do client-side rendering. And for the rare case where a page is genuinely blocking automated access, we flag it during onboarding so the customer knows upfront rather than finding out later.
The bigger technical challenge for us is actually interpreting what changed and why it matters — two competitors can both raise prices by 10% but the strategic implications can be completely different depending on the customer's positioning.
Curious about your AI infra automation tool — are you leaning toward usage-based pricing or flat tiers? That's always a tough call with infra products.