Why I reverse-engineer competitor go-to-market (GTM)
When I audit a market, I don't start by guessing. I start by reverse-engineering the strongest players. That process turns vague intuition into concrete opportunities: missing customer segments, weak onboarding flows, replicable channel plays. Over the years I've used the same framework with startups and mid-market teams to identify 3 exploitable gaps that can be turned into fast experiments.
The goal: find gaps you can act on in 30–90 days
My objective isn't to build a perfect, exhaustive dossier on every competitor. It's to surface a small set of high-leverage gaps that meet three criteria:
Framework: the 6-layer GTM scan
I map the competitor GTM across six layers. For each layer I ask specific questions and collect signals from public sources, product experience and customers.
The point is not to be perfect — it's to create a repeatable map you can compare across competitors and against your own GTM.
How I collect evidence (practical sources)
Here are the specific signals I pull from public and semi-public sources. You can scale this with junior teammates or use tools like SimilarWeb, BuiltWith, G2, and LinkedIn Sales Navigator.
Translating evidence into hypotheses
Once you have the data, write concise hypotheses that pair a gap with an expected business impact and a test you can run. I use this template:
"Because [evidence], we believe [gap]. If we [experiment], we expect [metric uplift] in [timeframe]."
Example:
"Because competitor X's onboarding requires three manual configuration steps and they have low 'first-week active' scores in reviews, we believe they lose mid-market customers during setup. If we build a 1-click template for typical mid-market configurations and test with a landing page and walkthrough, we expect a 20% increase in trial-to-paid conversion within 60 days."
How I pick the 3 exploitable gaps
From the pool of hypotheses, I score each against three dimensions and pick the top three that pass the threshold.
Prioritize high-impact, low-to-medium-effort items with fast time-to-result. Those are your quick wins.
Common exploitable gaps I find—and how I exploit them
These are the patterns I spot most often and the specific plays I use to exploit them.
Play: Reframe your messaging to lead with the outcome, create a landing page targeting the neglected persona, and run a paid test (LinkedIn or search) to measure CTR and MQL quality. KPI: lead-to-opportunity conversion and CAC for that persona.
Play: Ship a 'mid-market quickstart' template and an onboarding concierge pilot (2-week free setup). Measure trial activation rate and time-to-first-value. KPI: trial-to-paid conversion lift and churn at 90 days.
Play: Build a lightweight integration or co-marketing asset with a popular platform (e.g., Slack, Shopify, Salesforce AppExchange). Launch a referral landing page and run partner-led webinars. KPI: new ARR attributable to the channel and cost per lead.
Play: Introduce transparent tiered pricing with clear outcomes per tier and a self-serve upgrade path. A/B test messaging and monitor conversion for each tier. KPI: ARPA (average revenue per account) and booking velocity.
Play: Produce a short, targeted case study + ROI calculator for a high-value segment and gate it behind a quick qualification form to feed inside sales. KPI: SQL conversion rate and deal size uplift.
Simple template: Gap analysis table
| Competitor | Evidence | Gap | Impact (0–5) | Effort (0–5) | Experiment |
|---|---|---|---|---|---|
| Competitor A | Opaque pricing page; many negotiation reviews on G2 | Pricing friction for mid-market | 4 | 2 | Transparent tier + self-serve free trial test |
| Competitor B | No Shopify integration; high search volume for Shopify+solution | Missing channel via Shopify | 3 | 3 | Build basic integration + partner webinar |
How I measure success and iterate
Each experiment has a primary KPI and two secondary KPIs. Keep tests short and binary: win, lose, or iterate. I typically run three-week sprints for marketing experiments and 4–8 week pilots for product/partner plays. If a test meets the success threshold, we scale; if not, we document the learnings and move to the next hypothesis.
Primary KPIs I use most:
One last pragmatic tip
Don't try to match every feature or channel. Use competitive reverse-engineering to find asymmetries — places where a small product tweak, a clearer promise or a channel push can change perception and economics. In practice, those three exploitable gaps will often include one product change, one GTM/channel move, and one messaging/pricing play. Ship all three in parallel and you’ll have both short-term wins and a foundation for sustainable differentiation.
