How EvalyMe Backtests Startup Valuations Using Real-World Data

In a world full of hype, vanity metrics, and inflated numbers, it’s easy to become cynical about startup valuations. That’s why we built EvalyMe — to help founders get a directional, data-informed valuation estimate for their project or business, grounded in reality, not fluff.

But that only works if our engine is accurate enough to be trusted.

So how do we make sure EvalyMe's valuation scores aren't just feel-good numbers?We backtest them — constantly.

Here's how we do it.

What Is Valuation Backtesting?

Backtesting is a simple but powerful idea: We take real-world startup data — companies that have publicly announced funding rounds, been acquired, or disclosed revenue — and plug their info into EvalyMe. Then, we compare our predicted valuation to what actually happened.

This helps us:

• Measure the accuracy of our valuation algorithm
• Identify over/underestimations
• Fine-tune the model for different stages and categories

Where Our Test Data Comes From

We gather startup info from a variety of public and credible sources:

• Funding databases like Crunchbase, Dealroom, and YC Demo Day launches
• Open startups that share MRR, user growth, and metrics (like Buffer, Fathom, Plausible)
• Acquisitions listed on sites like MicroAcquire / Acquire.com
• Indie hackers and solo founders who publicly share exit stories

From each, we extract or approximate:

• Monthly recurring revenue (MRR)
• Team size
• Category (SaaS, Marketplace, B2B, B2C, etc.)
• Stage (MVP, launched, growing)
• Growth rate
• Known or estimated valuation

How We Run the Backtests

Our valuation engine uses a combination of traction, team, and product signals to estimate startup worth. To test it:

• We gather a dataset of real-world startups
• We plug their info into EvalyMe
• We compare EvalyMe’s estimated valuation to the actual public valuation
• We calculate the % error and determine if it was an overestimate or underestimate
• We log results and compute metrics like:
• Mean Absolute Percentage Error (MAPE)
• Median error
• Accuracy by category or stage

We do this using a custom backtesting script built into the EvalyMe codebase that automatically processes historical cases and outputs a report.

What We’ve Learned So Far

Here’s what our backtests have revealed:

• EvalyMe valuations are within ±25–30% of real-world valuations in most early-stage cases (pre-seed, seed, bootstrapped)
• We tend to slightly underestimate solo founders with high revenue but no team (we’re adjusting for that)
• Marketplace businesses with low MRR but strong growth often get undervalued — so we’re boosting growth weighting in those models
• We’re most accurate when:
• MRR is entered
• The startup has a clearly defined market category
• The founder profile is complete

Transparency Over Vanity

We believe valuation shouldn’t be a black box.

That’s why we’re:

• Publishing our testing methodology publicly
• Letting users opt in to share **verified valuations** post-funding or post-exit
• Using real data to **continuously improve the algorithm**, not inflate egos

What This Means for You

If you’re using EvalyMe to evaluate your MVP, pitch to investors, or benchmark growth:

• You can trust that the valuation isn’t pulled from thin air
• You’ll get directionally reliable feedback
• You can *grow your valuation* over time with tangible actions, not guesses

And soon, we’ll be adding public “backtest transparency badges” to our platform — so you can see how EvalyMe performs in your startup category.

Build with Confidence

Startup valuations will never be perfect — even VCs get it wrong. But by backtesting rigorously, we can build a smarter, fairer system for early-stage founders to understand where they stand and where to go next.

That’s our promise. And we’ll keep publishing results as we go.

Want to help us improve EvalyMe?

Submit your real-world valuation data or exit story anonymously here.

Or... run your own startup through EvalyMe now and see how you stack up:Launch EvalyMe →