Who This Helps
This is for you, junior analyst. You have data, you have ideas, but you freeze when asked, "Which experiment do we run next?" You want to ship clean analysis with clear recommendations. The GTM Strategy & Messaging course shows you how to prioritize like a pro.
Mini Case
Meet Noor. She's a junior analyst at a B2B SaaS company. The team has three experiment ideas: a new pricing page, a LinkedIn ad test, and a sales email sequence. Noor's analysis shows the pricing page could lift conversion by 12%, the ad test by 5%, and the email by 3%. She also knows the pricing page takes 7 days to build, the ad test takes 3 days, and the email takes 1 day. Using a simple impact-effort score, Noor recommends the pricing page first. The team agrees. She ships her analysis with a clear recommendation. Noor just focused effort on the highest-impact move.
Do This Now (5 Steps)
- List all experiment ideas. Write them down. No judgment.
- Estimate impact for each. Use a simple scale: low, medium, high. Or use a number like 12% lift.
- Estimate effort for each. How many days? How many people? Be honest.
- Score each idea. Divide impact by effort. Higher score wins.
- Pick the top score. That's your next experiment. Ship your analysis with that recommendation.
Avoid These Traps
- Don't pick the easiest experiment first. Easy is not always high impact.
- Don't overthink the scoring. A rough estimate beats no estimate.
- Don't forget to share your reasoning. Your team needs to see why you chose that experiment.
- Don't wait for perfect data. Use what you have now.
- Don't ignore stakeholder input. Ask them what matters most.
Your Win by Friday
By Friday, you will have one clear experiment recommendation. Your analysis will be clean. Your team will know exactly what to do next. And you will feel like a prioritization ninja. (Okay, maybe just a really smart analyst.)