How We Research Every IdeaStack Opportunity (Our Full Process)
Key Takeaways
- Every IdeaStack report follows a 7-step pipeline: keyword research, SERP analysis, competitor deep dive, Reddit sentiment, framework scoring, revenue modelling, and builder prompts
- We use DataForSEO for keyword volumes — not estimates, not ranges, actual monthly search data for the UK market
- Competitor analysis goes beyond listing names — we check funding data, pricing, tech stacks, backlink profiles, and product gaps
- Our scoring uses three frameworks: Hormozi Value Equation, Brunson Value Ladder potential, and our own ACP (Audience-Competition-Potential) score
- Builder prompts let you go from 'this is a good idea' to 'here's how to start building it this weekend' in one step
How we research every IdeaStack opportunity (our full process)
Every Thursday, we publish one deeply researched UK business opportunity. Not a listicle. Not a vibe check. A proper report with real keyword data, competitor analysis, revenue projections, and a build plan.
People ask us how we do it. This post walks through the entire pipeline — every step, every tool, every decision — using our AI Garmin Coach report as a worked example.
Step 1: Keyword research
Everything starts with search demand. If people aren't searching for it, the idea might still be valid — but the acquisition model is fundamentally different, and we need to know that up front.
What we actually do
We pull keyword data from DataForSEO, which gives us the same underlying data that powers tools like Ahrefs and SEMrush. For each idea, we research 15-30 related keywords and pull:
- Monthly UK search volume — not an estimate, not a range. The actual number.
- Competition level — low, medium, or high, based on how many advertisers are bidding.
- CPC (cost per click) — what advertisers pay to show ads against this keyword. Higher CPC usually means higher commercial intent.
- Monthly trend data — 12 months of search volume so we can see seasonality and growth direction.
Worked example: AI Garmin Coach
For the AI Garmin Coach report, we researched keywords across the fitness-tech space. Here's what we found:
| Keyword | Monthly UK Searches | Competition | CPC |
|---|---|---|---|
| ai personal trainer | 480 | Medium | £3.64 |
| garmin data analysis | 10 | Low | — |
| garmin training analysis | — | — | — |
| wearable data insights | — | — | — |
The "ai personal trainer" keyword was the standout: 480 monthly UK searches, medium competition, and a CPC of £3.64 that signals genuine commercial intent. The January 2026 spike to 1,000 searches suggested growing interest — likely driven by Garmin's Connect+ launch and the new year fitness rush.
The low-volume keywords ("garmin data analysis" at just 10/month) told us something equally important: the niche terms are too small to build a content strategy around. You'd need to target the broader "ai personal trainer" and "ai fitness coach" terms and work your way down.
What this tells us
Keyword research doesn't just validate demand — it shapes the entire business strategy. A keyword like "ai personal trainer" at 480/month with £3.64 CPC tells us:
- There's meaningful search demand (not massive, not tiny)
- Advertisers are willing to pay £3.64 per click, so there's money in this market
- Competition is medium, which means the door isn't wide open but it's not locked either
Step 2: SERP analysis
Knowing the search volume is only half the picture. The other half is: who's already winning?
What we actually do
We analyse the top 10-20 Google results for the primary keyword. For each result, we look at:
- Domain authority — how powerful is the site overall?
- Backlink profile — how many sites link to this specific page?
- Content quality — is it thin content or a genuine resource?
- Content type — blog post, product page, comparison site, forum thread?
- Age — how long has this page been ranking?
Worked example: AI Garmin Coach
For "ai personal trainer," the SERP revealed a mixed landscape:
- High-authority editorial content: Sites like TechRound and The5kRunner publishing "best of" lists with strong domain authority but relatively thin content
- Product pages: AI Endurance, TrainAsONE, and RunningCoachAI ranking with their own product pages
- Forum discussions: Medium posts and Reddit threads appearing in results — a signal that Google doesn't have enough quality content to fill the page
The key insight: when forums and personal blog posts rank for a keyword with 480 monthly searches and £3.64 CPC, that's a content gap. Google is struggling to find quality results. That's opportunity.
What this tells us
A SERP dominated by indie tools and thin content is a fundamentally different competitive environment from one dominated by venture-backed companies with 50-person SEO teams. The SERP analysis tells you whether this is a fight you can actually win.
Step 3: Competitor deep dive
Listicle articles say "competitors exist." We tell you exactly who they are, what they charge, and where their weaknesses are.
What we actually do
For the top 5-8 competitors in the space, we research:
- Pricing and revenue model — free, freemium, subscription, one-time purchase?
- Funding — bootstrapped or venture-backed? How much have they raised?
- Tech stack — what are they built on? (This affects how quickly you could build something competitive)
- User reviews — what do customers love and hate?
- Product gaps — what features are missing or poorly executed?
Worked example: AI Garmin Coach
| Competitor | Pricing | Model | Key Weakness |
|---|---|---|---|
| Garmin Coach | Free (with watch) | Built into Garmin Connect | Limited to 5K/10K/half marathon; rigid plans |
| Garmin Connect+ | £6.99/month | Premium subscription tier | New (launched 2026); AI features are basic |
| TrainAsONE | £9.99/month | AI-generated plans from training history | Dated UI; limited device support beyond Garmin |
| AI Endurance | Free tier + premium | AI training plans for running/cycling/triathlon | Generic; not deeply personalised |
| Runna | £9.99/month | Structured training plans by level | Not AI-native; human-designed plans with some adaptation |
The gap we identified: Garmin Coach is free but inflexible. Garmin Connect+ is new and underdeveloped. TrainAsONE has the right idea but a poor user experience. There's space for a tool that combines deep Garmin data integration with genuinely adaptive AI coaching — and charges somewhere between free and £9.99/month.
What this tells us
Competitor analysis reveals whether there's actually room for a new entrant. If every competitor is well-funded, well-executed, and well-loved by users, that's a hard market. If competitors are underfunded, have dated products, or leave obvious gaps, that's where opportunity lives.
Step 4: Reddit sentiment
Search data tells you what people are looking for. Reddit tells you what they're frustrated about.
What we actually do
We search relevant subreddits (r/running, r/Garmin, r/fitness, etc.) for discussions about the problem space. We're looking for:
- Unmet needs — what do people wish existed?
- Complaints about existing tools — where are the gaps?
- Willingness to pay — do people say "I'd pay for this" or "this should be free"?
- Language — what words do real users use to describe the problem?
Worked example: AI Garmin Coach
Reddit discussions in r/Garmin and r/running revealed consistent themes:
- Frustration with rigid Garmin Coach plans that don't adapt to missed runs
- Scepticism about Connect+ pricing for features that feel incremental
- Strong interest in AI-powered coaching that uses existing wearable data
- Several threads asking for "something between free Garmin Coach and paying £50/month for a human coach"
That last point was gold. It validated the pricing gap we'd identified in the competitor analysis and gave us the exact language potential customers use.
What this tells us
Reddit sentiment turns market data into human insight. Keyword volumes tell you people search for "ai personal trainer." Reddit tells you why — they're tired of rigid training plans that don't adapt when life gets in the way.
Step 5: Framework scoring
Data without structure is just noise. We use three scoring frameworks to turn research into a comparable score.
Hormozi Value Equation
Alex Hormozi's Value Equation measures an opportunity on four dimensions:
- Dream outcome — how desirable is the end result?
- Perceived likelihood of achievement — how confident is the customer it'll work?
- Time delay — how quickly do they see results?
- Effort and sacrifice — how much work does the customer have to put in?
For the AI Garmin Coach opportunity, the dream outcome scores high (better race times, fewer injuries), perceived likelihood is medium (AI coaching is still new), time delay is low (you'd see a personalised plan immediately), and effort is low (the watch does the data collection).
Brunson Value Ladder
Russell Brunson's Value Ladder maps out how you can increase customer value over time:
- Free tier: Basic plan generation from Garmin data
- Low-cost subscription (£5-10/month): Adaptive plans, recovery guidance, race predictions
- Premium tier (£15-25/month): Human coach review, video analysis, nutrition integration
- High-ticket: Corporate wellness programmes, running club partnerships
ACP Score (our proprietary framework)
ACP stands for Audience-Competition-Potential. We score each dimension 1-10:
- Audience (7/10): 480 monthly UK searches, growing trend, strong Reddit engagement
- Competition (7/10): Existing competitors have gaps; no dominant well-funded player
- Potential (8/10): Clear value ladder, strong retention model, multiple revenue streams
Overall ACP: 7.3/10 — a solid opportunity with manageable competition and clear upside.
What this tells us
Framework scoring lets you compare opportunities on a consistent basis. An ACP of 7.3 means something — it tells you this opportunity scores well on audience and potential, with competition that's beatable but not trivial. When you've scored 20 ideas, you can rank them and focus on the best ones.
Step 6: Revenue modelling
Dreams are free. Revenue projections cost nothing to calculate and can save you months of wasted effort.
What we actually do
We build three scenarios — conservative, moderate, and optimistic — based on realistic assumptions about traffic, conversion, and pricing:
Worked example: AI Garmin Coach
Conservative (Year 1):
- 200 monthly visitors from SEO (capturing ~40% of the 480/month search volume)
- 3% conversion to free tier → 6 free users/month
- 10% free-to-paid conversion → ~7 paying users by month 12
- Average revenue per user: £8/month
- Year 1 MRR: ~£56/month
Moderate (Year 1):
- 500 monthly visitors (SEO + content marketing + Reddit)
- 5% conversion to free tier → 25 free users/month
- 15% free-to-paid → ~45 paying users by month 12
- Average revenue per user: £10/month
- Year 1 MRR: ~£450/month
Optimistic (Year 1):
- 1,200 monthly visitors (SEO + partnerships + PR)
- 7% conversion to free tier → 84 free users/month
- 20% free-to-paid → ~200 paying users by month 12
- Average revenue per user: £12/month
- Year 1 MRR: ~£2,400/month
What this tells us
Revenue modelling forces you to be honest about scale. Even the optimistic scenario shows £2,400/month MRR in year one — that's a solid side income but not a salary replacement. This is critical context that no listicle provides. "Start a fitness app" sounds exciting. "You'll probably earn £450/month in year one" is the reality check you need.
Step 7: Builder prompts
Research is worthless if you can't act on it. The final section of every report is a set of builder prompts — copy-paste instructions for AI tools to help you start building.
What we actually do
We write specific prompts for:
- Technical architecture — "Build a Next.js app that connects to the Garmin API, pulls training data, and generates a weekly plan using Claude"
- Landing page copy — "Write a landing page for a Garmin coaching tool targeting UK runners who find Garmin Coach too rigid"
- MVP feature set — "Build a minimum viable product that does three things: imports Garmin data, generates a weekly plan, and sends it to the user's phone"
- Content strategy — "Write 5 blog posts targeting 'ai running coach' keywords for the UK market"
These aren't generic prompts. They're informed by everything in the report — the keyword data, the competitive gaps, the pricing model, the user language from Reddit.
What this tells us
Builder prompts close the loop between "this is a good idea" and "here's how to start building it." For technical founders especially, the gap between validation and execution is often smaller than they think. A weekend with the right prompts and tools can produce a working prototype.
Why we do this
We built this pipeline because we were tired of reading "67 Business Ideas for 2026" articles that told us nothing. Every idea in those articles sounds equally good because none of them include data. When you add data, the picture changes dramatically. Some ideas are genuine opportunities. Most aren't.
Our job is to tell you which is which — with evidence, not opinions.
See it in action
The AI Garmin Coach report is available now on IdeaStack and walks through all seven steps for a real opportunity in the fitness-tech space.
Every Thursday, we publish a new report following this exact process. One idea. Properly researched. With the data you need to decide whether it's worth your time.
Subscribe to IdeaStack — data-backed UK business opportunities, every Thursday. Free to start.
Frequently Asked Questions
What tools do you use for keyword research?
We use DataForSEO for UK-specific keyword volumes, CPC data, competition levels, and monthly search trends. It gives us the same data that powers tools like Ahrefs and SEMrush, but via API so we can process it programmatically across dozens of related keywords per report.
How do you decide which ideas to research?
We look for ideas at the intersection of three things: growing search demand in the UK, a competitive landscape that isn't locked up by well-funded incumbents, and a viable software-based business model that doesn't require more than £1,000 to start. Ideas come from trend monitoring, Reddit communities, keyword gap analysis, and subscriber requests.
How long does each report take to produce?
The full research pipeline takes 6-8 hours per report. Keyword research and SERP analysis take about 2 hours, the competitor deep dive takes 2-3 hours, and the scoring, revenue modelling, and write-up take another 2-3 hours. We publish every Thursday.
What is the ACP score?
ACP stands for Audience-Competition-Potential. It's our proprietary scoring framework that rates each idea on three dimensions: how large and accessible the audience is (search volume, growth trend), how strong the competition is (number of competitors, funding, backlink strength), and the revenue potential (pricing power, retention, scalability). Each dimension is scored 1-10 and weighted to produce an overall score.
Can I request a specific idea to be researched?
Yes — Builder tier subscribers (£29/month) get 2 custom idea requests per month. We'll run the full research pipeline on any software-based UK business opportunity you're considering.