The Business Case: Forecasting the Revenue Impact of Fixing ThredUp's Leakiest Stage
Objective: Given ThredUp's current stage conversion rates, traffic volume, and average order value, forecast the revenue impact of closing the gap between the worst-performing stage and a realistic industry benchmark, and build the business case for prioritizing that fix.
You're a growth analyst at ThredUp building the Q3 roadmap pitch. Three teams each want dev resources for a different funnel fix, and you have to make the revenue case for the one that matters most.
Calculate the overall funnel conversion rate, compare the worst stage to a realistic benchmark, then translate the gap into a dollar forecast.
Before you start
What you'll need
Free path (everything below is enough to finish)
Free, transparent formulas a stakeholder can audit line by line
Free, source of the funnel data being forecast against
Paid upgrades (optional, faster/deeper)
Cleaner stakeholder presentation than a raw spreadsheet, though not required to complete the forecast
No access? Google Sheets charts cover the same before/after visual
The process
3 steps
Step 01 of 03
The lesson defines overall funnel conversion rate as the percentage of users at the top of the funnel who complete the final goal, noting the 2025 industry average was 3.1%, with top performers reaching 9.2%.
ThredUp's funnel shows 500,000 monthly visitors and 9,500 completed orders. What's the overall funnel conversion rate, and how does it compare to the 3.1% industry average?
Procedure
- Divide 9,500 completed orders by 500,000 visitors, multiply by 100
- Compare the result against the 3.1% industry average and 9.2% top-performer benchmark cited in the lesson
- Note whether ThredUp is below, at, or above the industry average
Overall funnel conversion rate: 9,500 / 500,000 x 100 = 1.9% Industry average: 3.1% Top 10%: 9.2% ThredUp is below the industry average
Healthy
The 1.9% figure becomes the baseline for the forecast, anchored against a real published benchmark instead of an arbitrary target.
Unhealthy
The team picks an aspirational target like 'let's hit 5%' with no benchmark backing it, and the forecast has no credible anchor when finance pushes back.
What this means
1.9% against a 3.1% published average means there's a real, sourceable gap, not just an internal opinion that the funnel 'feels slow.'
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| Roadmap pitches get rejected for lacking a credible target number | Anchor every funnel-fix pitch to a published industry benchmark, not an internal guess | 5 min |
Step 02 of 03
The lesson notes a healthy e-commerce cart-to-checkout rate is typically 40-60%, and that B2C funnels often reach 5-15% overall, giving a realistic comparison point instead of a generic global average.
ThredUp's cart-to-checkout stage converts at 22%. The lesson's healthy range for this exact stage is 40-60%. Is this the stage worth fixing first, or is 1.9% overall too low to pin on one stage?
Procedure
- List every stage's actual conversion rate next to the lesson's cited benchmark range
- Identify which stage has the largest gap below its benchmark, not just the lowest raw number
- Confirm cart-to-checkout at 22% (versus a 40-60% healthy range) is the largest gap in the funnel
STAGE vs BENCHMARK browse -> product page: 58% (no strong published benchmark) add to cart -> checkout: 22% vs 40-60% healthy <- largest gap checkout -> order: 71% vs no major benchmark concern
Healthy
Cart-to-checkout gets prioritized because it's the stage furthest below its own benchmark, not just the stage with the smallest raw number.
Unhealthy
The team fixes the top-of-funnel browse stage because its raw traffic loss looks biggest in absolute terms, while the benchmark-relative gap at cart-to-checkout goes unaddressed.
What this means
A stage-specific benchmark, not a top-of-funnel volume number, is what tells you which gap is actually abnormal.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| Roadmap debates stall over which stage 'feels' most broken | Replace the debate with a benchmark-gap table ranked by percentage points below range | 30 min |
Step 03 of 03
The lesson's one-line takeaway is to find the single step where most people leave, fix that one thing first. The revenue case is what makes that priority visible to non-analytics stakeholders.
If cart-to-checkout moves from 22% to the low end of the healthy range (40%), and average order value is $65, how much additional monthly revenue does that represent, using the same top-of-funnel traffic?
Procedure
- Hold add-to-cart volume constant and apply the current 22% and target 40% checkout rates
- Multiply the difference in checkout completions by average order value ($65)
- Present the forecast as a monthly revenue range, not a single overstated point estimate
Add to cart volume: 28,000/month Current checkout completions (22%): 6,160 x $65 = $400,400 Target checkout completions (40%): 11,200 x $65 = $728,000 Forecasted monthly lift: ~$327,600
Healthy
The forecast ships as a range with the calculation shown, so finance can sanity-check the assumption instead of taking the number on faith.
Unhealthy
The team presents a single flashy number ($327,600/month!) with no visible math, and it gets torn apart in the first roadmap review.
What this means
A forecast is only as credible as the assumptions a stakeholder can see and challenge.
So what do I do about it?
| Symptom | Action | Effort |
|---|---|---|
| Previous funnel-fix pitches got cut from the roadmap for lacking a dollar figure | Attach a shown-math revenue forecast to every future funnel-fix proposal | 30 min |
Final deliverable
A one-page revenue forecast memo with a before/after funnel model, a shown-math dollar estimate, and a prioritization recommendation for the Q3 roadmap.
See a reference example
Instacart, revenue forecast memo (excerpt) TARGET STAGE: browse -> item page, 41% vs a realistic 55-60% benchmark FORECAST: closing the gap at current traffic volume adds an estimated $184,000-$210,000 in monthly order value RECOMMENDATION: prioritize this over the checkout-page redesign, which has a smaller benchmark gap
Success criteria
You're done when you can:
- Correctly calculates overall funnel conversion rate and compares it to the cited industry benchmark
- Identifies the stage with the largest benchmark-relative gap, not just the largest raw drop
- Produces a shown-math revenue forecast, not an unexplained point estimate