Reforge · AI product · Mid · 45 to 60 minutes

Raise Repeat Use of the Reforge Extension

Reforge is a professional education company that offers programs and tools for product, growth, and marketing leaders. Answer this product management case and get it graded line by line against a weighted rubric.

Prioritization
AI product judgment
Experiment design
Metrics
User insight synthesis

The situation

Your manager, Reforge's new products lead, asks you to propose the next quarter plan for the company's AI browser extension. The extension has launched, people are trying it, and the team believes it could become a meaningful layer on top of Reforge's educational content and member workflows. But repeat usage is not yet strong enough to justify continued investment, and emails meant to bring users back to the extension are underperforming. Assume four week retention for new extension users is 18 percent and click through rate on extension emails is 2 percent. You have signals that the current experience is sometimes helpful, but the team does not yet know whether the main problem is content relevance, how AI reasoning is presented, where suggestions appear, or how the product is explained and marketed. You need to recommend where to focus first, how to measure impact, and what not to do. The tension is that AI improvements are costly and hard to evaluate, while simple messaging changes may lift acquisition or reactivation without fixing core value.

What to produce

A 1 to 2 page product strategy memo.

Your answer must

State your diagnosis of the most likely causes of weak repeat usage and low email response, separating product value, AI quality, UX placement, and messaging issues.
Recommend 2 to 3 prioritized experiments for the next quarter, with a hypothesis, target user moment, and primary success metric for each.
Define the metric framework, including one north star and leading indicators that connect AI changes to retention or conversion.
Explain tradeoffs and sequencing, including why you would do these experiments before other plausible ideas.
Describe how you would gather evidence quickly, using both product data and direct user feedback, and how you would decide to continue, change, or stop each experiment.

Constraints

Work within the existing browser extension and current email or lifecycle channels, no new standalone product.
The team can support at most 3 meaningful experiments this quarter because engineering, design, and AI resources are shared.
You must protect user trust in an AI product, so avoid approaches that depend on low quality output or confusing reasoning in the browser context.

Format

Use 5 short sections with bullets, plus one simple prioritization table.

How Reforge actually played it

Reforge's new products lead shares improvements to its AI browser extension: better content mapping, chain-of-thought changes, in-line suggestions and an AI-driven marketing test that quadrupled click through rate. The retention change is tied to specific product moves. A candid look at iterating on an AI product.

Tie each AI change to a retention or conversion metric
In-line suggestions can raise usefulness where users already work
Test new marketing approaches with clear before and after numbers

Built from How We Built The Reforge Extension Part 2: Doubling Retention & Quadrupling Email CTRs by Reforge.