The short answer
- → Want the analysis to explain and act: GoMarble
- → If the analysis must rest on independent measurement: Northbeam, Polar Analytics
- → If the context is ecommerce: Triple Whale
At a glance
| Tool | Best for | Meta | TikTok | Shopify | ||
|---|---|---|---|---|---|---|
| GoMarble | AI ad analysis with root-cause diagnosis and in-account execution | ✓ | ✓ | ✓ | ✓ | ✓ |
| Triple Whale | Ecommerce measurement and attribution on the Shopify stack | · | · | · | · | ✓ |
| Northbeam | First-party multi-touch attribution across channels | · | · | · | · | · |
| Supermetrics | Moving marketing data into BI tools and warehouses | ✓ | ✓ | ✓ | ✓ | ✓ |
| NinjaCat | Unified agency reporting with automated QA and pacing | ✓ | ✓ | ✓ | ✓ | ✓ |
| Vaizle | Low-cost multi-channel ad analytics with natural-language querying | ✓ | ✓ | ✓ | ✓ | ✓ |
| Polar Analytics | Ecommerce reporting and attribution on a warehouse backend | ✓ | ✓ | ✓ | · | ✓ |
| AgencyAnalytics | White-label client reporting across many accounts | ✓ | ✓ | ✓ | ✓ | ✓ |
✓ supported · — not supported · · not publicly stated
How we evaluated these tools
We assessed every tool on the same 6 criteria, so the comparison stays like-for-like rather than reflecting whichever feature each vendor leads with.
What the AI reads
One platform, all ad channels, or ads plus store and web data?
Summary vs explanation
Does it restate the numbers in prose, or identify what caused the change?
Question answering
Can you ask it something the dashboard was not built to answer?
Measurement basis
Platform-reported, or an independent attribution model?
Action
Can it act on the conclusion, or does the work return to you?
Delivery
Do you have to go to it, or does it come to you on a schedule?
The tools
Every entry below uses the same structure — best for, platforms, what it does, capabilities, pros, limitations, pricing, ideal customer, verdict — so you can compare like with like.
1. GoMarble
Best for: AI ad analysis with root-cause diagnosis and in-account execution
Platforms: Meta, Google, TikTok, LinkedIn, Shopify
GoMarble is an AI agent for paid media. It connects to your ad accounts, explains why metrics moved rather than only charting that they did, and then acts on that diagnosis — GoMarble AI Agents edit bids, budgets and campaign status directly, and Ad Launch ships new campaigns. Both are gated on human approval.
Key capabilities
- Root-cause analysis — decomposes a ROAS or CPA change into spend, CPM, CTR, CVR and AOV contributions
- GoMarble AI Agents — execute against their own diagnosis: bid and budget changes, pausing and scaling ads
- Ad Launch — analyzes creatives, picks the campaign, drafts brand-voice copy and ships it, gated on approval
- Execution across five channels: Meta, Google, TikTok, LinkedIn and Bing
- Creative analysis — connects hooks, formats and angles to performance, and flags fatigue signals
- Cross-channel analysis — Meta and Google in a single account view
- Conversational reporting — ask for the analysis in chat or Slack instead of building a dashboard
- Scheduled reports and anomaly alerts delivered to Slack or email, with no infrastructure to build
- Reports that carry recommended actions, which Agents can then execute on approval
- AI agents + MCP servers — drive the same analysis from Claude or your own tooling
Pros
- Diagnosis and execution in one place — it acts on its own analysis rather than handing you a list
- Reporting is conversational rather than built — you ask a question and get the answer, instead of designing a dashboard and maintaining it
- Reports arrive where the team already works (Slack or email) and carry actions, not just numbers
- Changes are gated on human approval rather than applied silently
- Meta and Google analysed together instead of in separate silos
- Open MCP servers mean the analysis is reachable from Claude and other AI clients, not locked in a dashboard
Limitations
- Not an attribution platform — no multi-touch modelling or incrementality testing, so it complements rather than replaces Northbeam or Triple Whale for measurement
- Creative tagging taxonomy is less granular than a dedicated creative-ops tool like Motion
- Not a white-label client-reporting platform — no branded client portal or per-client packaging, which agencies reporting to many clients will still need elsewhere
- Fewer prebuilt dashboard templates than the incumbent reporting suites
Pricing: See our pricing page for current plans View GoMarble pricing →
Best suited for: Performance marketers, in-house paid media teams and agencies who want diagnosis and execution in one agent
Verdict: The strongest fit when you want the same system to work out why performance moved and then make the change, across Meta and Google together.
2. Triple Whale
Best for: Ecommerce measurement and attribution on the Shopify stack
Platforms: Shopify
Triple Whale positions itself as a complete intelligence platform for ecommerce, unifying measurement, analytics, AI, creative and automation. It centralises advertising and store data to provide attribution and reporting across the funnel.
Key capabilities
- Attribution via its own pixel, alongside MMM and incrementality in its measurement suite
- Unified ecommerce and ad reporting with a large prebuilt dashboard library
- Creative analytics on higher tiers
- Deep native integration with the Shopify stack
Pros
- Genuinely strong ecommerce measurement — attribution, MMM and incrementality in one place
- Deep Shopify-stack integration and a large library of ready-made dashboards
- Free tier available for basic pixel tracking and first/last-click attribution
Limitations
- Built around ecommerce — weaker fit for lead-gen, B2B or app advertisers
- Attribution depth comes with a setup and data-hygiene burden
Pricing: From $179/mo (Starter); Advanced $259/mo; custom from $539/mo (checked May 2026 — Triple Whale no longer publishes tier prices publicly)
Best suited for: Ecommerce operators, founders and agencies wanting unified funnel measurement
Verdict: The better choice when attribution and store-level measurement matter more than ad-account diagnosis.
3. Northbeam
Best for: First-party multi-touch attribution across channels
Platforms: Not publicly stated
Northbeam is an attribution platform. It provides independent first-party multi-touch attribution across ad channels, omnichannel dashboards, view-through conversion attribution, and optional media mix modelling at the enterprise tier.
Key capabilities
- Independent first-party multi-touch attribution across ad channels
- Customisable omnichannel dashboards covering all channels in one view
- Custom attribution via Northbeam Apex to feed ad delivery algorithms
- View-through conversion attribution
- Media mix modelling as an enterprise add-on
- Dedicated strategist support from the Professional tier
Pros
- Attribution is the core product rather than a feature, and it shows in the depth of the modelling
- Can feed attribution signal back into ad platforms rather than only reporting it
- Strategist support included at higher tiers, which matters because attribution needs interpretation
Limitations
- Priced well above general analytics tools — the Starter tier alone exceeds most tools in this category
- Scales by pageview volume, so cost tracks site traffic rather than ad spend or account count
- An attribution layer, not an account-optimization or creative tool
Pricing: Starter $1,500; Professional $3,500/mo; Growth and Enterprise custom (checked September 2026)
Best suited for: Ecommerce brands at scale that need independent measurement across channels
Verdict: The specialist choice when attribution is the actual question — materially stronger at it than general analytics tools, including ours.
4. Supermetrics
Best for: Moving marketing data into BI tools and warehouses
Platforms: Meta, Google, TikTok, LinkedIn, Shopify
Supermetrics is a marketing data platform that connects, manages and moves data from advertising and marketing sources into BI tools, spreadsheets and warehouses. It is a data layer rather than an analysis layer.
Key capabilities
- Marketing data pipelines across a large connector catalogue
- Destinations including Looker Studio, Google Sheets, BigQuery and Snowflake
- Scheduled refreshes and managed transfers
- Natural-language querying of the data layer via its Claude integration
Pros
- The most mature option for reliable marketing data pipelines
- Best fit when a team already owns its reporting in Looker, Tableau or Power BI
- Broad connector catalogue beyond just ad platforms
Limitations
- Moves and models data — it does not interpret performance or explain why metrics changed
- Requires a BI tool and someone to build the reporting layer on top
Pricing: From $49/mo (Starter); Growth $199/mo; Pro $499/mo (checked September 2026)
Best suited for: Marketing and data teams building custom BI and reporting
Verdict: Choose Supermetrics for the pipeline, not the analysis — it pairs with an analysis layer rather than replacing one.
5. NinjaCat
Best for: Unified agency reporting with automated QA and pacing
Platforms: Meta, Google, TikTok, LinkedIn, Shopify
NinjaCat unifies and normalises marketing data across providers and accounts, then layers client-ready reporting on top. Its AI agents handle recurring reporting, QA, budget pacing and anomaly alerting.
Key capabilities
- Data unification and normalisation across providers and accounts
- 150+ pre-built connectors spanning search, social, retail media and analytics
- AI agents for reporting, QA, pacing and anomaly alerts
- Client-ready automated reporting
- Natural-language querying of unified data
Pros
- Very broad connector coverage, including retail media and DSPs that most agency tools omit
- Automated QA and pacing address failure modes that pure reporting tools ignore
- Absorbed Shape's PPC budget-management capability into the platform
Limitations
- No public pricing — evaluation requires a sales conversation
- Platform-scale implementation, which is heavy for a small team
Pricing: Not publicly listed — pricing available on request (checked September 2026)
Best suited for: Mid-size and larger agencies managing many accounts across channels
Verdict: A platform-level answer to agency reporting, priced and scoped accordingly.
6. Vaizle
Best for: Low-cost multi-channel ad analytics with natural-language querying
Platforms: Meta, Google, TikTok, LinkedIn, Shopify
Vaizle provides ad, social, web and ecommerce analytics across Meta, Google, LinkedIn and TikTok, with a natural-language interface for querying account data and a competitor analytics module.
Key capabilities
- Ad analytics across Meta, Google, LinkedIn and TikTok
- Competitor analytics on Meta, Google and LinkedIn ads
- Social, web (GA, Search Console) and Shopify analytics in one place
- Natural-language querying of account data
Pros
- Among the least expensive multi-channel analytics options, starting at $9/mo
- Competitor ad analytics included rather than sold separately
- Covers paid, social, web and ecommerce in a single tool
Limitations
- Credit-based pricing means heavy querying consumes the allowance quickly
- Breadth over depth — less rigorous than specialist tools on any single channel
Pricing: AI Lite $9/mo; AI Starter $59/mo; AI Pro $119/mo (checked September 2026)
Best suited for: Small teams and agencies wanting broad coverage at low cost
Verdict: The budget option for multi-channel visibility, with the trade-offs that implies.
7. Polar Analytics
Best for: Ecommerce reporting and attribution on a warehouse backend
Platforms: Meta, Google, TikTok, Shopify
Polar Analytics combines ecommerce reporting with multi-touch attribution on a dedicated warehouse backend. It offers a dashboard library, custom reporting, alerts and scheduled reports, plus lift testing across Meta, Google, TikTok and TV.
Key capabilities
- Multi-touch attribution with its own pixel
- Dashboard library and custom reporting over 400+ pre-built ecommerce metrics
- Google Ads and Meta Ads CAPI integrations
- Lift testing across Meta, Google, TikTok and TV campaigns
- Goal tracking, alerts and scheduled reports
- Dedicated Snowflake warehouse
Pros
- Warehouse-backed, so the data stays queryable beyond the vendor's own interface
- Combines attribution, reporting and incrementality testing rather than forcing separate tools
- Large library of pre-built ecommerce metrics reduces setup effort
Limitations
- Prices are not rendered on the public pricing page — evaluation requires a quote
- Scales by annual gross merchandise value, which suits ecommerce and fits lead-gen poorly
- Ecommerce-shaped throughout — a weak fit for B2B or app advertisers
Pricing: Core and Custom plans; prices not rendered on the public pricing page (checked September 2026)
Best suited for: Ecommerce brands wanting attribution and reporting on a warehouse backend
Verdict: A strong ecommerce measurement stack when the warehouse backend is genuinely useful to you.
8. AgencyAnalytics
Best for: White-label client reporting across many accounts
Platforms: Meta, Google, TikTok, LinkedIn, Shopify
AgencyAnalytics is a reporting platform built for agencies. It pulls from 85+ marketing data sources into white-labelled dashboards and automated client reports, with a client portal, goals and anomaly detection.
Key capabilities
- Automated client reporting with scheduled delivery
- White-label branding and a client portal
- 85+ data sources spanning ads, analytics, SEO and ecommerce
- Goals, alerts and anomaly detection
- AI insights and analysis
- Benchmarks and forecasting
Pros
- Per-client pricing maps cleanly onto how agencies actually bill
- Very broad connector coverage beyond paid media — SEO, email and ecommerce in the same report
- White-labelling and the client portal are core features, not add-ons
Limitations
- A reporting layer rather than an analysis or optimization tool — it presents data, it does not diagnose performance or act on accounts
- Per-client pricing scales linearly, so cost grows directly with roster size
Pricing: Core from $20 per client / month (billed annually); Enterprise custom for 25+ clients (checked September 2026)
Best suited for: Agencies reporting to multiple clients across several channels
Verdict: The strongest fit when the job is client reporting rather than performance analysis.
Full capability comparison
The capability matrix, so you can answer questions like "which of these do both Meta and Google, with creative analysis?" without rereading the list.
| Tool | AI analysis | Root-cause analysis | Executes changes | Creative analysis | Attribution | Reporting | Automation | AI agents | Budget recommendations | Multi-account | Starting price |
|---|---|---|---|---|---|---|---|---|---|---|---|
| GoMarble | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ | ✓ | ✓ | ✓ | See pricing |
| Triple Whale | ✓ | · | · | ✓ | ✓ | ✓ | ✓ | · | · | ✓ | $179/mo |
| Northbeam | · | · | · | · | ✓ | ✓ | · | · | · | · | $1500/mo |
| Supermetrics | · | — | — | — | · | ✓ | ✓ | · | — | ✓ | $49/mo |
| NinjaCat | ✓ | · | · | · | · | ✓ | ✓ | ✓ | ✓ | ✓ | Custom |
| Vaizle | ✓ | · | · | · | · | ✓ | · | · | · | ✓ | $9/mo |
| Polar Analytics | ✓ | · | · | · | ✓ | ✓ | ✓ | · | · | ✓ | Custom |
| AgencyAnalytics | ✓ | · | — | · | · | ✓ | ✓ | · | · | ✓ | $20/mo |
✓ supported · — not supported · · not publicly stated. Pricing as published on each vendor's site; see the methodology note for dates.
How the tools differ
The list above tells you what each tool does. This section answers the decision question — which one fits the job you actually have.
If you want the analysis to explain and act
GoMarble
Root-cause decomposition across Meta, Google, TikTok and Shopify, delivered conversationally or scheduled into Slack, with Agents executing the response on approval.
If the analysis must rest on independent measurement
Northbeam, Polar Analytics
Analysis built on platform-reported numbers inherits their double-counting. Both model attribution independently, which is the stronger foundation for channel-level conclusions.
If the context is ecommerce
Triple Whale
Ads against store revenue, cohorts and repeat behaviour — the numbers a DTC business is actually run on.
If you have analysts and a warehouse
Supermetrics
Delivers the data; the analysis is yours. Cheapest in licence terms, most expensive in analyst time.
If AI should summarise for clients
AgencyAnalytics, NinjaCat, Vaizle
AI-generated commentary attached to reporting. Useful for communication, not for diagnosis.
Best tool by use case
Not a ranking — a mapping. Most teams need one of these jobs done well rather than the highest overall score.
| Use case | Recommended tools |
|---|---|
| Explain why performance changed | GoMarble |
| Ask questions in natural language | GoMarble, Vaizle, NinjaCat |
| Independent attribution basis | Northbeam, Polar Analytics |
| Ads plus store data | Triple Whale, Polar Analytics |
| Feed your own analysts | Supermetrics |
| Client-facing AI commentary | AgencyAnalytics, NinjaCat |
| Act on the analysis | GoMarble |
What to consider before choosing a AI performance analysis tool
Summarising is not analysing
A model restating that CPA rose 22% has added presentation, not insight. The test is whether it identifies a cause you could act on.
Analysis inherits its inputs
An AI layer on platform-reported numbers reproduces their double-counting, confidently and in fluent prose. Check the measurement basis before trusting the conclusion.
Fluency reads as confidence
Generated commentary sounds equally assured whether the underlying finding is solid or spurious. Prefer tools that show the decomposition rather than only the narrative.
Ask where the analysis lands
Insight that requires someone to open a tool competes with everything else in their week. Pushed summaries get read; dashboards get forgotten.
Analysis without action is half a loop
A correct diagnosis that waits in a queue costs the same as no diagnosis. Whether the tool can act, or hands off cleanly to something that can, matters more than analysis quality alone.
Check the question surface
Some tools answer only what their schema anticipated. The useful ones answer questions nobody built a chart for.
FAQ
What is the best AI tool for marketing performance analysis?
Can AI actually analyse marketing performance, or just summarise it?
What data should a performance analysis tool see?
How do I know whether to trust an AI-generated insight?
Does this replace an analyst?
How much do AI performance analysis tools cost?
Methodology & sources
Product capabilities and pricing were reviewed from publicly available product documentation and pricing pages, with the check date shown against each tool above. Features and pricing change — verify details with the vendor before purchasing. Capability marks reflect what each vendor states publicly; where a capability is not publicly documented we mark it "·" rather than assuming it is absent.
- GoMarble: https://www.gomarble.ai/pricing
- Triple Whale: https://www.triplewhale.com/pricing
- Northbeam: https://www.northbeam.io/pricing
- Supermetrics: https://www.supermetrics.com/pricing
- NinjaCat: https://www.ninjacat.io/pricing
- Vaizle: https://vaizle.com/pricing
- Polar Analytics: https://www.polaranalytics.com/pricing
- AgencyAnalytics: https://agencyanalytics.com/pricing
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