Supermetrics alternative

The three meters — data sources, users, AI credits — and what a different shape costs instead.

Supermetrics is a data-pipe company: it moves marketing data into a destination you already use — Google Sheets, Looker Studio, a warehouse — and prices on how many data sources, users and AI credits you need. Starter is €39 a month billed yearly for three data sources, one user and one core destination; Growth is €159 for seven sources and two users; Pro is €399 for ten sources and three users. Refresh frequency is itself a tier: weekly on Starter, daily on Growth, hourly on Pro.

People search for an alternative for one of two reasons. Either the source count has become the binding constraint — you keep paying a tier up to add one more account — or the destination is the problem, because the data lands in a spreadsheet that still needs a human to turn it into an answer. TableBI is not a cheaper pipe. It is the destination and the query layer in one, with no seat count and no AI credits, and with far fewer connectors. Which of those trades is worth it is what the rest of this page is for.

Side by side

Supermetrics figures read from the Supermetrics pricing page on September 5, 2026; vendors change pricing, so check before deciding. TableBI figures come from its own pricing page and docs.

The source count is the meter that actually bites

Three sources sounds generous until you count properly. Google Ads, Meta and GA4 is three, and you have not added Search Console, and the second Meta ad account may count against a separate per-source account limit. The common path is Starter to Growth not because you needed seven platforms, but because you needed five.

The honest counter-argument: Supermetrics has connectors TableBI will not have for a long time — TikTok, LinkedIn, Shopify, Klaviyo, HubSpot and the rest of the long tail. TableBI ships four connectors and a CSV upload that tags rows with a free-text platform label. If your reporting depends on a platform outside those four, no amount of pricing arithmetic makes this a substitution.

Refresh frequency as a pricing tier

Weekly refreshes on the entry plan is the detail worth reading twice. It means the Starter tier answers questions about last week, and moving to daily costs four times the money.

TableBI does not tier freshness. Each source has a cooldown set by what the upstream API tolerates — three hours for Google Ads, six for Meta, twelve for GA4, twenty-four for Search Console — and it is the same whether you pay nothing or $29. Every answer also carries the freshness it was computed at, including an explicit note that Search Console runs two to three days behind and applies a privacy threshold to low-frequency queries. Knowing the number is two days old beats a fresher-looking number that quietly is not.

Pipe plus destination against one place

The Supermetrics shape is deliberate: you already have Sheets or Looker Studio, so it fills them. That is a real advantage when the people reading the output live in those tools.

It becomes a cost when the question outgrows the destination. A blended ROAS across four platforms in a spreadsheet is a set of formulas somebody maintains; in Looker Studio it is a blend with a documented join limit. TableBI collapses the two layers — one tablebi ask with roas(SUM(revenue), SUM(cost)) across platforms, then tablebi pin to publish it as a URL that refreshes itself. Fewer connectors, fewer moving parts, and no spreadsheet whose logic lives in one person's head.

What TableBI actually is, and is not

TableBI is a marketing-data backend for coding agents: it connects Search Console, GA4, Google Ads and Meta Ads (beta) into one queryable store, answers in read-only SQL over both a unified cross-channel view and the lossless per-platform raw tables, and pins any answer to a live public dashboard URL that refreshes itself.

The shortest way to see whether that shape fits is to connect one source on the free tier and ask it something:

# install, connect one source, ask
npm i -g @tablebi/cli
tablebi login
tablebi install          # plants a skill so Claude Code knows the commands
tablebi connect google_ads

tablebi ask "WITH w AS (SELECT MAX(date) AS anchor FROM metrics)
   SELECT platform,
          roas(SUM(revenue), SUM(cost)) AS roas,
          cpa(SUM(cost), SUM(conversions))       AS cpa
   FROM metrics, w WHERE date > w.anchor - 30
   GROUP BY platform ORDER BY roas DESC"

# pin the answer to a URL that refreshes itself
tablebi pin --title "Cross-channel efficiency"
→ https://you.tablebi.com/d/dsh_…

Every answer carries a trust block: per-source freshness, the rows it scanned, and explicit caveats — Search Console runs two to three days behind and applies a privacy threshold to rare queries; GA4 backfills for a day or two; GSC clicks and GA4 sessions are different populations and are not supposed to match. Here is a pinned dashboard running on real data.

Which to pick

Questions people ask

Other comparisons

Working the numbers rather than the tools? The free marketing calculators do ROAS, CPA, CTR and the rest in the browser, and the report templates are widget sets you can pin.