Looker Studio vs Power BI
Two general-purpose BI tools, one marketing problem neither was designed for.
Looker Studio is free and lives inside Google's ecosystem; Power BI is $14 per user per month for Pro and $24 for Premium Per User, and lives inside Microsoft's. For marketing reporting the choice usually comes down to which ecosystem your data and your colleagues are already in — Looker Studio if that is GA4, Google Ads and Sheets, Power BI if it is Excel, Azure and a finance team that already has licences.
The comparison that matters, though, is not between the two. Both are presentation layers that assume somebody has already solved the data problem: getting four ad platforms into one table with one definition of cost and revenue, kept current. In Looker Studio that gap is filled by paid third-party connectors and blends with documented limits; in Power BI it is filled by Power Query work or a warehouse. This page covers the honest differences between them, and then names the layer that sits underneath both.
Side by side
| Looker Studio and Power BI | TableBI | |
|---|---|---|
| Price | Looker Studio: free. Looker Studio Pro adds team management and support at a per-user price. | Power BI: free account for personal use; Pro $14/user/mo paid yearly; Premium Per User $24/user/mo. |
| Marketing connectors | A few Google-native ones free; everything else is a paid third-party connector, billed per source per month. | Some native, most via Power Query work or a warehouse in between. |
| Multi-source joins | Blends, with documented limits on how many sources and what kinds of joins. | The full data model — genuinely more capable, and correspondingly more work. |
| Refresh | Live queries against the source, which is where the slowness comes from. | Scheduled refresh; frequency depends on licence tier. |
| Learning curve | Low. A marketer can build a report in an afternoon. | Steeper — DAX and the data model are a real skill. |
| Where TableBI sits | Underneath both. It is not a chart builder — it is the connected, unified, queryable store the chart builder assumes you already have, with a pinned dashboard URL if you do not want a chart builder at all. |
Looker Studio and Power BI figures read from the Microsoft Power BI pricing page on September 5, 2026; vendors change pricing, so check before deciding. TableBI figures come from its own pricing page and docs.
The honest split between the two
Looker Studio wins when your data is already Google's — GA4, Google Ads, Search Console, Sheets — when the audience needs a link rather than a licence, and when speed of assembly matters more than modelling power. It is free, and sharing is a URL.
Power BI wins when the model is complicated, when the same numbers must reconcile with finance, when row-level security or a real semantic layer matters, or when your organisation already pays for Microsoft 365 and the licence is effectively free. DAX is harder than anything in Looker Studio and it buys you correspondingly more.
Neither answer changes much for marketing specifically, which is the tell: the marketing-specific pain is upstream of both.
Where both of them hurt on marketing data
Three failure modes recur regardless of which you picked:
- The connector tax. Getting Meta, TikTok or LinkedIn into either tool means a paid third-party connector, priced per source per month, on top of the BI tool.
- Definition drift. Each platform names cost and revenue differently. Whoever built the report decided how to reconcile them, and that decision lives in the report rather than anywhere inspectable.
- Rebuild per report. The next report starts from the connectors again, because the unified table was never a thing that existed — it was assembled inside a chart.
These are data-layer problems wearing presentation-layer clothes, which is why switching between Looker Studio and Power BI rarely fixes them.
The third shape
TableBI is not a competitor to either — it has no chart builder, no drag-and-drop and no semantic modelling. It is the layer both of them assume: connect Search Console, GA4, Google Ads and Meta (beta) once, get one unified cross-channel view with roas(), cpc(), cpa() computed identically across platforms, keep the lossless raw underneath, and query it in read-only SQL from your own Claude Code.
If you want a chart, keep Looker Studio or Power BI on top. If what you actually wanted was the answer and a link to share it, tablebi pin gives you a public URL that refreshes itself — here is one running — and you can skip the BI tool.
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.
What it does not do. TableBI has no white-label branding, no scheduled PDF or email delivery, no client login portal, no alerting and no rank tracking. It connects four sources today — Search Console, GA4 and Google Ads live, Meta Ads in beta — plus CSV upload, against the 85 to 130 integrations the reporting platforms list.
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
Choose Looker Studio if
Your data is Google-native, your audience needs a shareable link rather than a licence, and free matters. It is the fastest path from GA4 to a chart somebody can read.
Choose Power BI if
The model is complex, the numbers must reconcile with finance, or your organisation already has Microsoft 365 licences that include it. More capable, more work.
Add TableBI underneath if
The pain is the connector tax, definitions drifting between reports, or rebuilding the same joins every time. It is the unified queryable store, not another chart builder — and a pinned URL if the chart was never the point.
Questions people ask
Is Looker Studio or Power BI better for marketing reporting?
Looker Studio is usually better when your data is Google-native — GA4, Google Ads, Search Console — and the audience needs a link rather than a licence. Power BI is better when the data model is complex, the numbers must reconcile with finance, or your organisation already pays for Microsoft 365. Neither solves the multi-platform data problem itself.
How much does Power BI cost?
Microsoft lists a free account, Power BI Pro at $14 per user per month paid yearly, and Power BI Premium Per User at $24 per user per month paid yearly, with Power BI Embedded priced variably. Read from the Microsoft pricing page on 5 September 2026.
Is Looker Studio really free?
The standard product is free to use and to share. Costs arrive from two directions: paid third-party connectors for non-Google sources, billed per source per month, and Looker Studio Pro if you want team content management and support.
Do I need a data layer under Looker Studio or Power BI?
You need one as soon as you report on more than one ad platform. Both tools assume a table already exists where cost and revenue mean the same thing across sources; without it, the reconciliation logic ends up inside individual reports and drifts between them.
Other comparisons
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The three meters — data sources, users, AI credits — and what a different shape costs instead.
Databox alternative
Databox has the more generous free tier. Here is the axis where that stops being the question.
AgencyAnalytics alternative
What the per-client price actually buys — and the case where you want a different layer entirely.
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.