Design a Smarter Experimentation Calendar

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Wednesday Deep Dive

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The Wednesday Deep Dive takes a detailed look at what's new in AI. Each week, we share in-depth insights on new tools, proven prompts, and significant developments - helping tech professionals work smarter and stay ahead.

This week’s challenge: Running a high-output growth engine without drowning in scattered tests and gut-feel decisions.

Every growth team wants to experiment more. But without structure, it’s easy to fall into a cycle of random A/Bs, half-finished tests, and weeks of wait time between insights.

These prompts give your team a way to break the cycle, with an AI-powered experimentation calendar that surfaces high-impact tests, automates prioritization, and tracks results continuously.

What they deliver:

• A quarterly experimentation roadmap with AI-curated test ideas

• A sprint-ready backlog of experiments ranked by impact/effort

• A system for ongoing learning and iteration

Let’s dive in.

Set the Stage

In high-growth companies, velocity wins. But that doesn’t mean running more tests; it means running the right ones.

Growth teams already have mountains of data: past experiments, funnel metrics, user behavior, campaign performance. The challenge is connecting those dots and knowing what to test next.

That’s where AI can take the lead.

Tools like GrowthBook, Airtable AI, and Mutiny now let you:

✅ Analyze past test results for patterns and signals
✅ Auto-generate new experiment ideas by audience or funnel stage
✅ Prioritize by predicted ROI and execution complexity
✅ Track outcomes and feed results back into the next cycle

Instead of starting from scratch every quarter, you’re building a compounding engine of validated growth learnings.

Here’s the Prompt to Get Started

Design a Quarterly Growth Experimentation Calendar

Use this prompt to analyze past results and generate a structured testing roadmap.

<prompt>
  <role>You are a growth lead planning a quarterly testing roadmap for a SaaS product.</role>

  <task>
    Using the following inputs:
    <ul>
      <li>Past test results (landing page variants, CTAs, email subject lines)</li>
      <li>Key metrics by funnel stage (conversion rates, CAC, retention, LTV)</li>
      <li>Target segments or personas for Q3</li>
    </ul>

    Generate:
    <ol>
      <li>A list of 10+ experiment ideas organized by funnel stage (Awareness, Activation, Retention)</li>
      <li>Effort vs. impact scoring for each test</li>
      <li>A sprint calendar assigning tests across 12 weeks</li>
      <li>Instructions for tracking outcomes and feeding insights into next-quarter planning</li>
    </ol>
  </task>

  <context>Focus on sustainable velocity—run fewer, better experiments and capture learnings in a repeatable system.</context>
</prompt>

What This Prompt Can Deliver

Input Provided:

• Past tests: 20 email subject line A/Bs, 3 onboarding flows, 2 landing page variants

• Key metrics: 3.2% homepage conversion, 19% email CTR, 12% 30-day retention

• Segments: Mid-market PMs, agency partners, self-serve founders

Output Given:

Funnel-Organized Test Ideas:

• Awareness: LinkedIn ad copy test with agency-specific pain points

• Activation: AI-driven onboarding sequence vs. static checklist

• Retention: Triggered feature drop emails at day 7 and 14

Effort/Impact Score:

• Landing Page CTA: Low effort / high impact

• Onboarding Wizard Redesign: High effort / medium impact

Sprint Calendar:

• Week 1–2: Activation flow test

• Week 3–5: New pricing page variant

• Week 6–8: Retargeting subject line test

• Week 9–12: Referral program relaunch

Tracking Workflow:

• All experiments logged in Airtable

• Outcome review every 2 weeks

• Successful tests added to growth playbook

Another Practical Prompt: Unlock the Real Drivers of Retention

Use this prompt to turn raw user activity data into a full-funnel retention strategy.

<prompt>
<role>
You are a growth strategist designing a retention strategy using behavioral cohort analysis.
</role>

<task>
Using the following inputs:
- User activity logs: session counts, feature engagement, login streaks, in-app purchases
- Account metadata: plan type, signup source, customer segment
- Churn history: timestamps, cancellation reasons (if available)

Generate:
1. Behavioral cohorts based on retention likelihood (e.g., power users, churn-risk users, high-potential new signups)
2. Key behaviors that correlate with long-term retention for each group
3. Messaging and lifecycle strategies tailored to each cohort (emails, nudges, feature prompts)
4. A retention playbook including timing, messaging cadence, and measurement KPIs
</task>

<context>
Design the output so a growth or product team can use it to build segmented retention workflows inside tools like Customer.io, Amplitude, or Mixpanel.
</context>
<prompt>

What This Prompt Can Deliver

Here’s an example of what this prompt could generate:

Cohort: Power Users
Behavioral Traits: Log in >5x/week, use 3+ core features, high NPS

Strategy:

• Celebrate milestones (e.g., 50 sessions, feature unlocks)

• Offer referral incentives and early access to beta features

• Use in-app messaging to deepen product mastery

Sample Messaging:
"You’ve unlocked advanced workflows used by our top 5%, want to test what’s next?"

Cohort: Dormant Users
Behavioral Traits: Last active >30 days ago, low feature usage, no support tickets

Strategy:

• Send reactivation emails with product improvements or use-case inspiration

• Offer personalized onboarding tips based on their past behavior

• Use FOMO-based messaging tied to industry benchmarks or missed outcomes

Sample Messaging:
"Teams like yours have increased productivity by 40% using [Feature]. Ready to jump back in?"

Cohort: New Activations
Behavioral Traits: Signed up in the last 7 days, used onboarding flow, but minimal feature usage

Strategy:

• Drip campaign walking through 1 core feature per day

• Trigger in-app nudges based on friction points (e.g., skipped tutorial)

• Personalized check-in from Customer Success after day 3

Sample Messaging:
"Still getting set up? Start here, most teams see results after their second workflow is live."

Running experiments is easy. Learning from them is hard.

This AI-powered calendar doesn’t just surface ideas, it helps teams:
✅ Work from data, not instinct
✅ Prioritize what moves the needle
✅ Build momentum by compounding wins over time

Instead of chasing one-off tactics, your team gets a system. And the system gets smarter with every test.

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