Marketing Analytics Tools: 8 Picks Sorted by Job

Olamide Sule, founder of Dolphin Analytics: a digital analytics expert based in London delivering solutions for agency and in-house clients.

We set up, connect and fix marketing analytics tools for agencies and in-house teams most weeks, and the teams who come to us are rarely short of software. They’re pulling their hair out with data challenges: a dashboard that disagrees with the ad platforms, a CRM nobody trusts, a GA4 property that stopped recording sales after a site change. The shortlist below sorts the tools by the job each one does, so you can see which jobs your stack already covers and which it doesn’t. If you already own the tools but don’t trust the numbers, our marketing analytics service is built for exactly that.

How we picked these: one tool per job, drawn from the tools we implement, connect or audit in client work. We favoured tools with a free tier or a published pricing model, and named the main alternative for each. Product details were checked on 1 October 2026 against each vendor’s own documentation and pricing pages, so confirm current plans before you buy.

What are marketing analytics tools?

Marketing analytics tools are the software that records, moves and reports how marketing turns into revenue: GA4 for site behaviour, ad platforms such as Google Ads and Meta Ads for spend, a CRM such as HubSpot for leads and deals. No single product does every job. Most teams run a small stack, with one tool each for measurement, collection, reporting, data movement, attribution and modelling.

Web analytics is one part of that. A web analytics tool like GA4 tells you what visitors did on the site; marketing analytics joins that to what you spent and what you sold, across every channel. The join is where most of the work sits, and most of the faults. For a head-to-head of the web and product analytics platforms themselves, including Adobe Analytics, Amplitude and Matomo, see our digital analytics tools comparison.

Which marketing analytics tool does each job?

Each row is one job, the tool we’d reach for first, and how it’s paid for. The entries further down link each vendor’s own documentation.

Job	What it answers	Our pick	Cost basis	Main alternative
Measure site behaviour	Which channels bring visitors, and what they do	GA4	Free; Analytics 360 for enterprise	Matomo
Control what’s collected	Which tags fire, when, and under which consent	Google Tag Manager	Free; Tag Manager 360 for enterprise	Tealium
Report	What happened, in one shared view	Data Studio (formerly Looker Studio)	Free; Data Studio Pro for enterprise teams	Power BI
Move ad platform data	Spend and results from every ad platform in one place	Supermetrics	Free trial, then a paid subscription	Funnel
Store and join raw data	How site data lines up with orders, deals and spend	BigQuery	Free sandbox, then charges past its limits	Snowflake
Lead-to-revenue attribution	Which campaigns produced deals, not only leads	HubSpot	Paid Marketing Hub tiers	Dreamdata
Budget modelling	How to split budget across channels, offline included	Google Meridian	Free, open source	Meta’s Robyn
On-page behaviour	Where visitors get stuck on a page	Microsoft Clarity	Free	Hotjar

Verdict: start with GA4, Google Tag Manager and Data Studio. All three are free, they cover measurement, collection and reporting, and for most marketing teams they answer the day-to-day questions. Add Supermetrics and BigQuery when ad spend and sales need to sit in one place, and hold off on attribution and modelling tools until the tracking underneath them is trustworthy.

The shortlist: eight tools, one job each

The numbers follow the stack from measurement to modelling; they are not a ranking. Microsoft Clarity sits outside that chain and can go in at any point.

1. GA4: best for measuring what visitors do on your site

GA4 (Google Analytics 4) is Google’s free analytics tool and the starting point for most marketing stacks. It measures actions as events, and you mark the actions that matter most to the business as key events, which are then surfaced in its reports. The Analytics 360 tier raises the limits on data collection, reporting, retention and export to BigQuery.

GA4’s weak spot is rarely the tool itself. When we audit a property, the faults are in the setup: key events nobody marked, purchase events firing twice, campaign tagging that scatters one campaign across several channels. Fix those before you judge GA4 or replace it.

2. Google Tag Manager: best for controlling what gets collected

Google Tag Manager (GTM) is a tag management system: it lets you set up and manage tags on your site without changing the site’s code each time. One container can replace the hand-coded tags for Google Ads, Google Analytics and third-party tools. GTM is free, with Tag Manager 360 as the enterprise version.

Tag Manager also carries your consent rules. Its consent settings can hold a tag back until every consent type you specify is granted, and tags with built-in consent checks change how they run based on the visitor’s consent state. Our tag management systems explainer compares GTM with the alternatives.

3. Data Studio (formerly Looker Studio): best for free dashboards on Google data

Google has renamed Looker Studio: its documentation now says Looker Studio is called Data Studio, and describes it as a no-cost tool for dashboards and reports. It reads Google Analytics, Google Ads, Google Sheets and other Google Marketing Platform products through free connectors built by Google, while community connectors for other platforms may cost money. Data Studio Pro adds enterprise collaboration and administration features.

In our experience, Data Studio is the right reporting layer for most teams and most agencies until the data has to come from outside Google. A dashboard on it doesn’t have to be a long project, either.

Built a ski travel company's Looker Studio dashboards from scratch in two weeks, in time for Black Friday.

Our guide to what Looker Studio is and how to build a marketing dashboard in it covers the build. The usual friction is getting Meta, LinkedIn or TikTok numbers in, which is the next tool’s job.

4. Supermetrics: best for pulling ad platform data into one place

Supermetrics is a connector tool: it pulls marketing data from sources such as Google Ads, Meta Ads, LinkedIn Ads and TikTok Ads. Its pricing page lists destinations including Google Sheets, Looker Studio, BigQuery, Excel, Power BI and Snowflake, and prices every plan on the number of data sources and destinations you connect, after a free trial.

For an agency reporting across many clients, a connector is usually the quickest way to get every ad platform into one dashboard. The catch is that the numbers arrive on each platform’s own terms: Supermetrics’ guide to Facebook Ads attribution settings says conversion results won’t line up with Facebook’s own reporting unless the query uses the same attribution setting. A connector moves the numbers; deciding which platform’s count to believe is still your job.

5. BigQuery: best for owning raw data and joining it to sales

GA4 can export all of its raw events to BigQuery, where you query them with SQL-like syntax. Standard GA4 properties have a daily BigQuery export limit of 1 million events, and Google notes that exports past the free sandbox’s limits incur charges. The BigQuery sandbox itself needs no credit card or billing account to start.

The raw export is what lets you join site behaviour to Shopify orders, CRM deals or connector spend, which is the question most marketing reports can’t answer on their own. When GA4 revenue and the shop’s revenue disagree, the answer usually comes out of the BigQuery tables, not the GA4 interface.

6. HubSpot: best for B2B lead-to-revenue reporting

HubSpot’s attribution reports show the interactions contacts have along their journey, and let you apply different attribution models to share out the credit. Contact create attribution needs Marketing Hub (or Content Hub) Professional or Enterprise. Deal create and revenue attribution are for Marketing Hub Enterprise accounts only.

That tier split matters for B2B teams. On Professional, the attribution reports show which campaigns created contacts but not which ones created revenue, and a long sales cycle lives in that gap. Our marketing attribution models guide explains how each model shares out the credit.

7. Google Meridian: best for budget questions attribution can’t answer

Meridian is an open-source marketing mix model (MMM) built by Google, and it’s free for anyone to use. Its code is fully visible and open to modification, and it supports geo-level data, which Google notes contains more statistical information.

Meridian is code you run, not a dashboard you log into, so in our experience it needs an analyst who can build and read a model. It earns its place when spend is spread across several channels, including TV, radio or print that user-level tracking can’t see. Our marketing mix modelling guide covers when it fits and what it needs from your data.

8. Microsoft Clarity: best for seeing where visitors get stuck

Microsoft Clarity is a behavioural analytics tool with session recordings, heatmaps, and event and funnel tracking. Microsoft describes it as free forever, with no obligation to upgrade to a paid version. Its job is to show how people use a page and where they get stuck.

That fills a gap in GA4. A GA4 funnel exploration shows how well visitors succeed or fail at each step of a task, and anyone who misses a step falls out of the funnel. Clarity’s session recordings of that step show how people used the page before they dropped out. We add it through Tag Manager, behind the consent banner, so it follows the same consent rules as every other tag.

Which marketing analytics stack fits your team?

Most teams need fewer marketing analytics tools than vendors suggest. Match the stack to the question you need answered, then add a tool only when the current stack can’t answer the next one.

Your situation	Stack
Small in-house team, mostly on Google Ads	GA4, Google Tag Manager, Data Studio
Agency reporting on many clients across ad platforms	The core three, plus Supermetrics feeding Data Studio
Ecommerce brand matching ad spend to orders	The core three, plus BigQuery for the order join
B2B team with long sales cycles	GA4 and Tag Manager, plus HubSpot attribution (Enterprise for revenue)
Spend across several channels, offline included	Clean weekly spend and sales history first, then Meridian
A key page converting worse than it should	Microsoft Clarity alongside GA4

When we audit a stack, the commonest fault is two tools counting the same thing differently, with nobody deciding which one wins. Pick a source of truth for each number (orders from the shop, deals from the CRM, spend from the ad platform) before you add anything new.

Where tracking breaks in a marketing analytics stack

Tracking breaks at the joins between tools: where a tag hands data to GA4, where a connector copies an ad platform’s numbers, where a lead lands in the CRM. The tools on this list rarely fail on their own. The faults sit in how each one was set up and how they were connected, and these are the ones we fix most often.

• GA4: key events missing or duplicated. An action is only surfaced in reports as a key event once you’ve marked it as a key event, so an unmarked purchase or lead never shows up as a result. A purchase tag that fires twice makes revenue look better than it is; we walk through that case in GA4 duplicate purchase events.
• Google Tag Manager: consent settings that don’t match the banner. A tag held back until a consent type is granted will never fire if the banner never sends that signal, and a third-party tag with no consent check configured fires on its trigger alone. Both faults live in Tag Manager’s consent settings.
• Data Studio: charts that mix definitions. A chart that puts GA4 sessions beside ad platform clicks compares two different things. Label the source of every number on the page.
• Supermetrics and other connectors: platform numbers taken at face value. Google Ads records conversions inside a conversion window after an ad click or video view, while GA4 credits key events with its own attribution model and lookback window. Put both totals in one dashboard and they rarely agree. Our post on why Meta Ads over-report conversions shows how to check a platform’s claim against real orders.
• BigQuery: a sandbox that deletes your history. In the BigQuery sandbox, all tables, views and partitions expire automatically after 60 days. Teams that link GA4 to a free sandbox and walk away find their oldest exports gone when they finally run a query. Once the GA4 link is complete, data should start flowing to BigQuery within 24 hours, so set it up well before you need the history.
• HubSpot: contact credit read as revenue credit. On Marketing Hub Professional, attribution reports cover contact creation; deal and revenue attribution need Enterprise. In reviews, we often find contact-creation credit presented as if it were revenue. The other gap we see often is HubSpot form submissions that never reach GA4, and our HubSpot form tracking fix covers it.
• Meridian: a model built on gappy inputs. A marketing mix model is only as good as the weekly spend and sales history behind it. Missing weeks, spend booked to the wrong period or a tracking change partway through all distort what the model says.
• Microsoft Clarity: a script outside Tag Manager’s consent rules. Tag Manager’s consent settings are set on each tag in a container, so a Clarity snippet pasted straight into the site template never gets them. Clarity has its own consent handling instead: Microsoft’s Consent Mode documentation says Consent Mode is on by default for visitors from the EEA, UK and Switzerland, and Clarity sets no cookies until it receives a valid consent signal. Without consent, Clarity assigns a unique ID per page view and doesn’t use cookies to persist session data, so its recordings can’t follow a visitor from page to page. Load Clarity through Tag Manager and pass the banner’s decision to Clarity’s consent API, so it follows the same rules as everything else.

To see which tags, pixels and consent setup your own site runs, as a visitor’s browser sees them, run our free Sonar scan: one click, no account access and nothing to install.

How do we help when the tools are in place but the numbers aren’t?

Our work sits underneath the tools on this list. We set up, audit and fix GA4 and Tag Manager tracking, build pipelines into BigQuery and reporting in Data Studio, and help teams work out which tools they actually need before they buy another one. That last job can matter as much as any setup work. Here is one example from a data platform purchase.

For a marketing agency we benchmarked a £189K vendor quote for a data platform against a similar build we'd delivered for around £50K in about 50 days, and showed the quote was three to four times too high.

If your stack is in place but its numbers still don’t agree, that’s the conversation to have with us. Tell us what’s broken, or book a call. If you already know you need someone inside the account, our paid audit works through five layers of your GA4 and Tag Manager setup and returns a written findings report.