Price Benchmarking

What is Price Benchmarking?

Written by Arnon Shimoni

✓ Expert

Last updated on:

Price benchmarking is the process of comparing your pricing against external reference points: competitors, market averages, customer willingness to pay, and industry norms. The goal is to understand whether you're priced too high (leaving growth on the table), too low (leaving revenue on the table), or misaligned with how your market perceives value.

For SaaS and AI companies, benchmarking is how you answer the question every founder, CFO, and pricing committee asks: "Are we priced right?"

What gets benchmarked

Price benchmarking covers more than just the number on the pricing page.

Dimension

What you're comparing

Why it matters

Headline price

Your list price vs. competitors for comparable tiers

The most visible comparison. Where most benchmarking starts and, unfortunately, often stops

Pricing model

How you charge (per seat, per usage, per outcome, hybrid) vs. how competitors charge

A lower headline price on a usage model can cost more than a higher seat price at scale

Packaging

What's included at each tier vs. what competitors include

A feature gated behind your Enterprise tier might be in a competitor's mid-tier

Discounting

Your average discount depth and frequency vs. market norms

If you're discounting 30% on every deal and the market average is 15%, your list price is fiction

Value metrics

What unit you charge on vs. what competitors charge on

Charging per seat when the market has moved to per-usage puts you on the wrong side of the trend

Contract structure

Annual vs. monthly, commitment levels, ramp schedules

Competitors offering monthly billing when you require annual commits affects close rates

Expansion mechanics

How customers grow their spend over time vs. alternatives

Net revenue retention depends on how natural the expansion motion is

Benchmarking only headline price is the most common mistake. Two products at $50/user/month can have wildly different total cost of ownership based on what's included, how overages work, and what happens at scale.

Where benchmarking data comes from

Source

What it tells you

Limitations

Public pricing pages

Competitor list prices and packaging at each tier

Enterprise pricing is almost always "contact us." List prices don't reflect actual deal prices

Win/loss analysis

What competitors quoted in deals you won or lost

Requires disciplined sales process. Data is anecdotal and subject to buyer framing

Industry reports

Market-wide pricing trends and model adoption rates

PricingSaaS, OpenView, ICONIQ, Bain publish annual data. Broad trends, not company-specific

Customer conversations

What customers are willing to pay and what alternatives they've evaluated

The most valuable source, and the most underused. Requires structured WTP interviews

Third-party databases

Aggregated SaaS pricing data from tools like Vendr, Spendflo, Vertice

Shows actual contract prices, not list prices. Coverage varies by market segment

Sales team feedback

Which objections relate to pricing and where deals stall

High signal, but often conflated with "they said it was too expensive" when the real issue was value perception

The best benchmarking combines public data (what competitors show) with private data (what customers actually pay and what they'd be willing to pay). Neither source alone gives you the full picture.

How to run a pricing benchmark

A useful benchmark follows a structured process, not a one-off Google search of competitor pricing pages.

Step

What to do

Output

1. Define the comparison set

Identify 5-8 direct competitors and 2-3 adjacent alternatives (including "do nothing" and "build in-house")

Competitor list with pricing page screenshots and model descriptions

2. Normalize for model differences

Convert different pricing models to a common unit (e.g., total annual cost for a company with 50 users processing X volume)

Apples-to-apples cost comparison at 2-3 customer scenarios

3. Map packaging differences

Document what's included at each tier across competitors

Feature comparison matrix showing where you over-index or under-index

4. Gather internal data

Pull win/loss data, discount frequency, average deal size, expansion rates

Quantified view of how your pricing performs in market

5. Run WTP conversations

Interview 10-15 customers and prospects using a structured willingness-to-pay framework

Direct signal on perceived value, price sensitivity, and competitive positioning

6. Identify gaps

Compare your pricing to the benchmarks across all dimensions

Specific, actionable findings: "We're 40% above market on entry tier but 20% below on enterprise"

7. Decide what to change

Prioritize adjustments based on revenue impact and implementation feasibility

Pricing roadmap with clear actions, owners, and timelines

Benchmarking for AI and hybrid pricing

AI products face a specific benchmarking challenge: the pricing models are so varied that comparing on price alone is misleading.

Company A

Company B

Same product?

$99/user/month, includes 1,000 AI credits

$49/user/month + $0.05 per AI action

Depends entirely on usage volume

500 credits/month, $0.10 per extra credit

Unlimited AI features, $149/user/month

Company A is cheaper below 1,500 actions, more expensive above

$0.99 per resolved ticket

$199/month flat for AI support bot

Company A costs less at low volume, more at high volume

When pricing models differ, benchmarking requires scenario analysis: model the total cost for a customer at 3-4 different usage levels to see where each competitor is cheaper and where they're more expensive. A single comparison at one usage level can be completely misleading.

Common benchmarking mistakes

Mistake

What goes wrong

Comparing list prices only

Enterprise deals are discounted 15-40%. List price benchmarks overstate what competitors actually charge

Ignoring model differences

A $30/seat competitor with usage caps may cost more than a $50/seat competitor with unlimited usage

Benchmarking once

Pricing changes constantly. PricingSaaS tracked 8,394 pricing events across 498 companies in 2025. Annual benchmarking misses the moves

Copying competitor pricing

Competitors may be wrong. Their pricing reflects their cost structure and strategy, not yours

Skipping customer input

Benchmarks tell you what the market charges. Customers tell you what the market values. These aren't the same thing

Not acting on findings

The most common failure. Companies run benchmarks, produce a report, and change nothing because their billing system can't support the recommended changes

That last point is where most benchmarking exercises die. You discover your entry tier is overpriced, your enterprise tier is underpriced, and your credit conversion rates don't reflect current AI costs. But changing any of it requires engineering work because your pricing logic is hardcoded. The benchmark insight is usable only if your billing infrastructure can execute the change.

Have questions about your pricing?

Solvimon has worked with hundreds of companies navigating the transition from simple subscriptions to hybrid, usage-based, and AI-driven pricing models. We've seen how companies at every stage benchmark, where the biggest pricing gaps hide, and what it takes to close them.

If you're unsure whether your pricing is competitive, whether your packaging reflects how customers buy, or whether your billing infrastructure can support the changes you need to make, we can help you diagnose it.

Talk to a pricing expert

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Built for companies that outgrew simple billing

If you're monetizing AI features, running multiple entities, or moving upmarket with enterprise contracts—Solvimon handles the complexity.

From billing v1 to billing v2

Built for companies that outgrew simple billing

If you're monetizing AI features, running multiple entities, or moving upmarket with enterprise contracts—Solvimon handles the complexity.

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Helping businesses reach the next level

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I was skeptical if there was any solution out there that could relieve the team from an eternity of manual billing. Solvimon impressed me with their flexibility and user-friendliness.

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