The short answer
- → The cross-channel picture explained and acted on: GoMarble
- → If the question is attribution itself: 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 | ✓ | ✓ | ✓ | ✓ | ✓ |
| Northbeam | First-party multi-touch attribution across channels | · | · | · | · | · |
| Triple Whale | Ecommerce measurement and attribution on the Shopify stack | · | · | · | · | ✓ |
| Supermetrics | Moving marketing data into BI tools and warehouses | ✓ | ✓ | ✓ | ✓ | ✓ |
| Polar Analytics | Ecommerce reporting and attribution on a warehouse backend | ✓ | ✓ | ✓ | · | ✓ |
| NinjaCat | Unified agency reporting with automated QA and pacing | ✓ | ✓ | ✓ | ✓ | ✓ |
| Whatagraph | White-label multi-channel client reporting | ✓ | ✓ | ✓ | ✓ | ✓ |
| Vaizle | Low-cost multi-channel ad analytics with natural-language querying | ✓ | ✓ | ✓ | ✓ | ✓ |
✓ 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.
Data unification
Does it bring channels into one dataset, or just show them side by side?
Attribution reconciliation
Does it resolve double-counted conversions, or present each platform's own claim?
Comparison basis
Can it compare channels on one consistent measure?
Interpretation
Does it explain cross-channel shifts, or leave the reading to you?
Action
Can it act on the conclusion across channels?
Channel coverage
Which platforms, and how deep on each?
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. 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.
3. 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.
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. 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.
6. 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.
7. Whatagraph
Best for: White-label multi-channel client reporting
Platforms: Meta, Google, TikTok, LinkedIn, Shopify
Whatagraph builds multi-channel marketing reports and dashboards for agencies, with white-labelling, scheduled PDF delivery, custom data transformations, and onward transfer of data to BigQuery or a BI layer.
Key capabilities
- Report creation with custom transformations and aggregations
- White-labelling and automated PDF email delivery
- Goals and alerts on KPI monitoring
- 68 integrations spanning paid media, analytics and ecommerce
- Data transfer to BigQuery and BI tools on higher tiers
Pros
- Unlimited users and reports on published tiers — cost scales with data sources, not headcount
- Custom transformations go beyond what most agency reporting tools allow
- Can act as both the reporting surface and a pipeline into a warehouse
Limitations
- Entry pricing is materially higher than other agency reporting tools in this list
- Annual billing only on published tiers
- A reporting layer — it presents and transforms data rather than diagnosing performance
Pricing: Max from €699/mo (billed annually, from 50 source credits); Prime custom (checked September 2026)
Best suited for: Agencies reporting across many channels and clients
Verdict: A premium agency reporting layer — strongest where custom data shaping matters.
8. 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.
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 |
| Northbeam | · | · | · | · | ✓ | ✓ | · | · | · | · | $1500/mo |
| Triple Whale | ✓ | · | · | ✓ | ✓ | ✓ | ✓ | · | · | ✓ | $179/mo |
| Supermetrics | · | — | — | — | · | ✓ | ✓ | · | — | ✓ | $49/mo |
| Polar Analytics | ✓ | · | · | · | ✓ | ✓ | ✓ | · | · | ✓ | Custom |
| NinjaCat | ✓ | · | · | · | · | ✓ | ✓ | ✓ | ✓ | ✓ | Custom |
| Whatagraph | ✓ | · | — | · | · | ✓ | ✓ | · | · | ✓ | €699/mo |
| Vaizle | ✓ | · | · | · | · | ✓ | · | · | · | ✓ | $9/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 need the cross-channel picture explained and acted on
GoMarble
Analysing Meta and Google as one account rather than two reports, diagnosing where a shift came from, and executing across five channels. Where we stop is attribution modelling.
If the question is attribution itself
Northbeam, Polar Analytics
Both are attribution-first and model credit across touchpoints. Genuinely stronger than us at deciding which channel deserves the conversion.
If the context is ecommerce
Triple Whale
Channels unified against store revenue, which is usually the number that settles cross-channel arguments.
If you want the data in your own model
Supermetrics
The most reliable pipeline into a warehouse or BI tool, leaving analysis to you.
If the output is a cross-channel report
NinjaCat, Whatagraph
Both present channels together well. Presentation is not reconciliation — the double-counting persists underneath.
If cost is the constraint
Vaizle
Multi-channel visibility from $9/mo, with less rigour on reconciliation.
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 a cross-channel shift | GoMarble |
| Resolve double-counted conversions | Northbeam, Triple Whale, Polar Analytics |
| Channels against store revenue | Triple Whale, Polar Analytics |
| Unify into a warehouse | Supermetrics |
| Cross-channel reporting | NinjaCat, Whatagraph |
| Act across channels | GoMarble |
What to consider before choosing a cross-channel analysis tool
Platform numbers will never sum correctly
Meta and Google each credit conversions they influenced. Added together they exceed reality. Any cross-channel comparison built on summed platform numbers is comparing inflated figures.
Side by side is not cross-channel
Two charts on one page is presentation. Cross-channel analysis means a consistent basis that allows a real comparison.
Decide your source of truth first
Platform-reported, pixel-based, or store-side — pick one for decisions and treat the others as directional. Without that, every review reopens the same argument.
Channels interact
Cutting prospecting on Meta often raises brand-search CPA on Google a fortnight later. Channel-level analysis that treats each as independent misses this entirely.
Match the tool to the layer
Pipeline, attribution and interpretation are three different products. Most teams need two, and buying one expecting all three is the common mistake.
Windows must match
Comparing a 7-day-click channel against a 28-day-click channel produces a difference that is measurement, not performance.
FAQ
What is the best tool for cross-channel ad analysis?
Why don't my channel numbers add up?
Do I need an attribution platform for cross-channel analysis?
What is the difference between cross-channel reporting and analysis?
How do I compare Meta and Google fairly?
How much do cross-channel 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
- Northbeam: https://www.northbeam.io/pricing
- Triple Whale: https://www.triplewhale.com/pricing
- Supermetrics: https://www.supermetrics.com/pricing
- Polar Analytics: https://www.polaranalytics.com/pricing
- NinjaCat: https://www.ninjacat.io/pricing
- Whatagraph: https://whatagraph.com/pricing
- Vaizle: https://vaizle.com/pricing
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