Bastle vs ChartMogul

This is the hardest comparison on the site

ChartMogul is the product we most often lose to on capability, and pretending otherwise would be silly. It does the things people complain that other analytics tools do not: metric rules you can configure, underlying data you can edit with an audit trail behind it, warehouse export, webhooks, a real custom import API, multi-source ingestion, and segmentation deeper than anything else in the category. It also ships — Scenarios forecasting and HubSpot metric sync landed recently — which is not true of every incumbent here.

So the comparison is not "we have features they lack." On a straight feature count for analytics, ChartMogul wins. The comparison is about two specific differences.

Difference one: the question, not the filter builder

ChartMogul's answer to "why did MRR drop" is a very good set of tools for constructing that answer yourself. Stack the filters, pick the date ranges, read the movement chart, form a hypothesis, filter again. When you are fluent in the product and the question is one you ask weekly, that is fast and precise.

Bastle's answer is to do the assembly and then show the parts. Ask takes the question as you would say it to a colleague, decomposes the movement into new, expansion, reactivation, contraction and churn, and cites the specific customers, subscriptions and invoices behind each. The arithmetic comes from the metrics engine rather than the model, so the numbers cannot drift from your charts, and every claim links to the records it used. For an occasional question from someone who is not fluent in the tool, that is a meaningfully different experience. For a daily analyst who already knows exactly which filters they want, it is less of an advantage than we would like to claim.

Difference two: ChartMogul does not do retention

ChartMogul is analytics. It will tell you precisely how much revenue you lost to failed payments and to voluntary cancellation; it will not chase the failed payment or intercept the cancellation. Both of those are separate purchases, and the retention vendors in this market are not cheap.

Bastle includes both. Recover runs delinquency, card-expiry and annual-renewal campaigns across email, SMS and an in-app banner, with a hosted card-update page that writes the new card back to your payment processor. Cancellation Insights captures the reason at the moment of cancellation and responds with an offer matched to that reason. Whether that consolidation matters depends on whether you were going to buy a retention tool anyway.

Where they are simply ahead

Segmentation depth. Warehouse destinations, which Bastle does not have and will not claim. Data editing with a full audit trail — Bastle supports manual corrections and excludes, but ChartMogul's editing surface is broader. A built-in CRM, which we do not have at all. Stage-specific benchmarks, where ours are on the roadmap and stay there until enough workspaces have opted in for a cohort to mean something. And years of production use, a support organisation and an installed base, none of which a beta product has.

The honest summary

If your evaluation is "which product lets me slice subscription data most precisely and get it into my warehouse", the answer is ChartMogul and it is not close. If it is "which product answers revenue questions without me building the query, and stops customers leaving without a second vendor", that is the case for Bastle. Both are defensible; they are different questions.

Who wrote this page

Bastle did, and Bastle benefits if you choose Bastle. That is a bias no amount of good intent removes, so the useful thing is to make it checkable rather than to claim it away. Every capability claim above is specific enough to disprove in an afternoon, the case for the other product gets the same room as the case for ours, and anything that works differently rather than not at all is marked partial.

Read this alongside the other vendor's own documentation, not instead of it. If something here is wrong about their product, tell us: corrections are treated as bugs rather than as debate, the page gets fixed and its research date is reset so you can see it was revised. That applies whether the correction makes them look better or us look worse.