B2B GTM Cheat Sheet: From $1M to $100M in ARR

What's the difference between the GTM motions covered here — when does a company actually need to run more than one at the same time?

The cheat sheet covers five motions: Enterprise, Mid-Market, PLG, Partner-Led, and Hybrid. Most companies between $1M and $20M ARR should be running one primary motion cleanly before layering in a second — trying to run Enterprise and PLG simultaneously with a small team usually means doing both poorly. The Hybrid model only makes sense once you have distinct segment teams, separate metrics tracking, and the systems integration to attribute revenue correctly across motions.

Which investor metrics in this cheat sheet should I be tracking before we hit $10M ARR, and which ones only matter later?

Below $10M ARR, focus on Magic Number, CAC Payback Period, and NRR — these tell you whether your GTM engine is efficient and whether customers are staying. Rule of 40 and EBITDA Margin are largely irrelevant at that stage since you're expected to be burning to grow. Burn Multiple (target under 1.5x) is the one efficiency metric that matters early because it directly connects spend to new ARR generation.

Do I need a dedicated forecasting tool to apply the sales process and forecasting guidance here, or can this work in a standard CRM?

The cheat sheet recommends combining multiple forecast methodologies and running a weekly cadence — you can do that in a CRM like Salesforce with disciplined stage exit criteria and required fields, but you'll hit the ceiling fast as pipeline complexity grows. A dedicated forecasting tool (Clari, Aviso, or similar) becomes worth the investment around $10M–$20M ARR when you have enough reps and deal volume that manual pipeline reviews stop being reliable. The more important prerequisite is clean CRM data — no tool fixes bad inputs.

How do I know if my pipeline coverage ratio is actually healthy, or just a number that looks fine on paper?

The cheat sheet benchmarks 3–4x for enterprise and 5–6x for mid-market, but coverage is only meaningful if the underlying opportunities are qualified against strict criteria. A pipeline full of stale deals or poorly qualified MQLs will show healthy coverage and still miss the number — which is why the cheat sheet pairs coverage with stage exit criteria and regular pipeline inspections. Check what percentage of your pipeline is moving: if more than 20% of deals are stagnant, your coverage ratio is overstated.

What data do I need to have in place before the ICP framework in this cheat sheet is actually useful?

You need at minimum: a clean list of your highest-NRR customers, time-to-value data by segment, and win/loss data broken out by firmographic attributes like company size and industry. Without those inputs, you're building ICP on gut feel rather than pattern recognition from your actual customer base. The cheat sheet's internal discovery step specifically calls out identifying customers with the highest NRR and fastest time-to-value — if that data isn't in your CRM or CS platform, start there before running the full ICP exercise.

How often should I revisit the GTM strategy and channel mix as we scale through the $1M to $100M ARR range?

A full GTM strategy review makes sense at each major funding or ARR milestone — roughly $1M, $5M, $20M, and $50M — because your ICP, competitive position, and channel efficiency all shift materially at those inflection points. Channel mix specifically should be reviewed quarterly using pipeline contribution and CAC payback by source, since what works at $5M ARR (often outbound-heavy) frequently stops being efficient by $30M. The cheat sheet's challenge-solution table flags "shift investment in pipeline generation" and "test new channels" as responses to low pipeline coverage — treat those as triggers for an off-cycle review, not just annual planning inputs.