Free CRO Cheat Sheet

What's the difference between a weighted forecast and a bottom-up forecast, and which should I start with?

A weighted forecast multiplies deal amount by stage probability — low effort, low accuracy, good for getting something on the board fast. A bottom-up forecast has reps and managers submit explicit calls that roll up the org — higher accuracy, but it requires process discipline and pipeline hygiene to work. Start with weighted, get one team running a weekly bottom-up cadence, then layer in AI as a third data point once your data is clean enough to trust it.

Which GTM motion from the cheat sheet should I keep fully human-led versus hand off to AI?

Late-stage deal management — multithreading, executive alignment, negotiation — should stay human-led; AI can flag risk and surface missing stakeholders, but a rep or manager needs to own the response. Top-of-funnel tasks like ICP scoring, lead routing, email personalization, and intent signal aggregation are the right places to let AI do the heavy lifting. The cheat sheet's core principle applies here: AI proposes, humans approve, especially on high-impact or low-confidence decisions.

What data do I need in place before the pipeline dashboards in this cheat sheet are actually useful?

You need consistent stage exit criteria enforced in your CRM, a next step date and activity on every open opportunity, and close dates that reps actually maintain — not placeholders. Without those three inputs, Stage Conversion, Average Time in Stage, and Pipeline Waterfall will show you noise, not signal. The cheat sheet flags this directly: automate CRM data capture and implement strict qualification criteria before you try to run meaningful pipeline reviews.

How do I know if my win rate is actually good or just looks fine because my pipeline is poorly qualified?

Cross-reference win rate against SQL Conversion Rate and Average Deal Size — if win rate looks healthy but deal size is shrinking and cycle length is growing, you're likely closing the easy deals and losing the ones that matter. The cheat sheet benchmarks B2B SaaS win rate at 20–30% overall, with top performers above 35%; if you're hitting those numbers but NRR is below 100%, the quality problem is showing up post-close instead. Run a cohort of recent wins and check whether they actually followed your sales stages or closed in ways your playbook doesn't support.

How often should I run forecast reviews, and what should I actually be doing in them?

The cheat sheet recommends a weekly cadence for bottom-up forecasts — that's the right default for most teams. In the review itself, start with deltas from last week's snapshot, not the total number: what moved in, what slipped, what changed in amount or close date. Use it as a coaching moment on specific deals — qualification gaps, missing stakeholders, stalled stages — not a roll-up recitation.

The cheat sheet covers five GTM strategies — how do I know which one fits where my company is right now?

Match the motion to your ACV and sales cycle first: if you're closing deals above $100K with 6-month cycles, you're in Enterprise territory regardless of what your website says; if you're seeing rapid self-serve adoption with expansion potential, PLG deserves real investment. Most companies above $10M ARR are running a hybrid whether they've designed it that way or not — the risk is that the motions conflict rather than complement. The cheat sheet's Hybrid Strategy row is worth reading carefully: the failure mode is usually poor attribution and team coordination, not the strategy itself.