Why your Clay credits disappear faster than you planned

It is not that it is expensive

Clay is a genuinely good product and the price on the page is defensible. The complaint is not the price. It is that you cannot predict the price, and the reason is structural rather than a matter of tuning your usage.

In a survey of 500 GTM professionals, 42% of complaints concerned uncontrollable consumption of credits. The learning curve is the most-cited issue on G2. Users describe spending $500 before they had produced anything, simply working out what the tool does.

The mechanism

Credits are deducted per action, not per result. A waterfall that tries six providers and finds nothing has charged you six times for the discovery that this person is not findable.

That is not a bug and it is not greed. It is the only model that works when you are reselling providers who charge *you* per attempt. The cost is real whether or not the data arrives, and somebody has to carry it.

The question is who.

Why the waterfall makes it worse

The waterfall is Clay's best feature and it is also where credits go. It is built for coverage: keep trying providers until one answers. Every attempt on the way to an answer is billed, and every attempt on the way to no answer is billed too.

For a list where coverage genuinely matters, that trade is correct. For exploratory work, where you are finding out whether a segment is worth pursuing at all, you are paying full price to learn that it is not.

The March 2026 change

Mid-tier prices rose roughly 28% while credit allowances fell about 40%. Whatever the reasoning, the effect on anyone who had built a monthly budget around the old numbers was a bill that roughly doubled per credit.

If you sized your plan before that, it is worth re-checking what you are now paying per usable record rather than per credit.

What to actually measure

Stop comparing credit prices. Compare cost per populated record:

credits spent ÷ records that came back with the fields you needed

A tool at half the credit price with a third of the hit rate is more expensive. That comparison is the only one that survives contact with an invoice, and almost nobody runs it because the second number is hard to get out of most tools.

The alternative model

There is another way to structure this, which is to charge only for lookups that returned something and absorb the misses.

It sounds like a giveaway. It is affordable under exactly one condition: you have to know, before you call it, which supplier is likely to miss. That means recording what every endpoint *yields* and not only what it *charges*, across every customer, and letting that record decide what gets called.

That data is the entire reason the model works. Without it you are absorbing an unknown, unbounded cost. With it, the misses shrink every month.