The standard B2B SaaS playbook says: charge a monthly subscription, lock in LTV, optimize for retention. ZoomInfo did this and became a $14B company. Apollo, Lusha, Cognism all followed.
When we built DatabaseLists — natural-language AI search for business leads — we tried the same playbook. $99/mo, $299/mo, $999/mo. It bombed. Conversion was 0.4%. We almost shut it down.
Then we tried something the playbook says not to do: kill subscriptions entirely, charge per search. Conversion went to 7.8%. LTV dropped, but volume went up so much that revenue tripled in three months.
Here is the math, the counter-intuitive lesson, and why this only works in specific markets.
The frequency problem
The fundamental issue with subscription pricing for lead-gen tools is frequency mismatch.
A salesperson at a tech company might pull lead lists daily — fine, $99/mo is cheap.
But the actual SMB market — the consultant, the agency, the local SaaS, the marketing freelancer — they need leads in bursts. Three days a month, maybe. Then nothing for six weeks until the next campaign.
For these users, $99/mo means they're paying $33/search for the 3 searches they actually run. Their brain does that math and unsubscribes within the first month.
We were burning cash on Stripe fees and a churn-funnel of users who never got value before they bailed.
What pay-per-search actually looks like
$0.10 per search, 10 free searches on signup
Top-up packs: $5 (50), $25 (300), $50 (700), $200 (3,500)
No subscription. Credits never expire.
What changed in user behavior, measured over the first 90 days:
| Metric | Subscription model | Pay-per-search |
|---|---|---|
| Signup → first search | 38% | 91% |
| Conversion to paid | 0.4% | 7.8% |
| Avg revenue per paying user | $204 | $34 |
| Refund/chargeback rate | 8.1% | 0.3% |
| Word-of-mouth signups | 4% | 23% |
| Net revenue / month | 1.0x | 3.1x |
The headline: ARPU dropped 6x. Total revenue tripled.
Why this is counter-intuitive
The SaaS playbook is built on LTV math: acquire customers, lock them in, milk LTV. CAC payback periods of 9–18 months are normal.
But that math assumes:
- The product has frequent enough use that monthly billing feels worth it
- Users have budget authority to commit to a recurring expense
- Switching costs are high enough to prevent churn
For SMB lead-gen, all three of those are false:
- Use is bursty, not constant
- The user IS the budget owner, and a $99 recurring charge is a real psychological cost
- Switching is trivial — they can just go to Google Maps + Hunter.io
When the playbook assumptions break, the playbook breaks. Pay-per-search restores the value-pricing alignment: you pay for what you get, when you get it.
The chargeback effect we didn't expect
The 8.1% chargeback rate on subscriptions was killing us. Most weren't fraud — they were "I forgot I subscribed and just noticed on my Amex statement six months later" disputes. Stripe sided with the customer ~70% of the time, and the chargeback fees themselves cost us $15 per dispute on top of the refund.
Pay-per-search chargebacks dropped to 0.3% because:
- The charge is tied to an action they took today
- The amount is small enough not to flag on bank statements
- The credits never expire, so there's no "I'm not using it anymore" frustration
This effect alone added ~$2,800/mo in retained revenue. We didn't model it. It was a surprise.
The word-of-mouth multiplier
Pay-per-search turned out to be inherently shareable in a way subscriptions aren't.
"Hey, try this thing, you get 10 free searches" is a sentence a user will actually send to a colleague. "Hey, try this thing, you'll need to pay $99/mo" is not.
23% of new signups came from explicit referrals in the pay-per-search era, vs 4% during the subscription era. We didn't change the referral program — the product structure did the work.
When this DOESN'T work
I want to be careful here — pay-per-search worked for us because of specific market conditions. It would have been a disaster in other contexts:
Don't do pay-per-use if:
- Your product has high daily engagement (e.g. Slack, Notion). Subscription captures more value here.
- Your fixed costs per user are high (e.g. you provision dedicated compute). You need predictable revenue.
- Your CAC is over $300. You need the LTV math to work.
- Your competitors are entrenched on subscriptions and have switching costs locked in. You'll need to differentiate on something other than pricing.
Do consider pay-per-use if:
- Use is bursty (lead gen, image generation, transcription, data pulls)
- Your user is the budget owner (solo, SMB, freelancer)
- The unit of value is clearly countable (1 search, 1 image, 1 minute of audio)
- Your variable cost per call is low enough that small per-unit prices still make margin
The unexpected upside: better data
The other thing that happened — users started using us in new ways we hadn't designed for.
A real estate agent in Dubai ran 240 searches in one weekend, scoping a market entry. Under subscription pricing, he never would have signed up. Under pay-per-search, he spent $24 and gave us a feature request list that led to our entire UAE expansion.
When pricing aligns with usage moments, you learn what users actually want to do — not what they're rationing themselves to within a monthly cap.
The Stripe implementation
Practical note for builders: pay-per-use is harder to implement than subscriptions. You need:
const session = await stripe.checkout.sessions.create({
mode: 'payment',
payment_method_types: ['card'],
line_items: [{ price: 'price_credit_pack_300', quantity: 1 }],
metadata: { user_id: userId, credits: '300' },
});
Two gotchas:
- Webhooks must be idempotent. Stripe retries on 5xx. Use the event ID as a uniqueness key on credit increments.
- Credit balance must be transactional. Use a row lock on the user when decrementing, or you'll oversell credits to concurrent searches.
TL;DR
Subscriptions are the default SaaS pricing model because they work for ~70% of products. For the other 30% — bursty-usage tools serving budget-owning SMBs — pay-per-use is structurally better. Lower ARPU, higher conversion, lower churn, higher referral rate. Run the math on your own market before defaulting to monthly.
If you want to see pay-per-search in action: 10 free searches at DatabaseLists. Type "Italian restaurants in Dubai with 4+ stars". The data is real.
Top comments (1)
Killing the tiers, not just the price, is what hit me. We ran three tiers expecting the middle to carry conversions, but it mostly made people overthink whether they'd use enough. What we charged for mattered more than the points. Was your lift the lower price, or people not predicting usage?
Sorry if my English sounds weird!!