How to Set Up Multi-Touch Attribution in GA4 Without Writing a Single Line of Code

    Muiz Thomas

    Muiz Thomas, Founder & CEO, AttributeIQ

    · 9 min read

    You’ve got GA4. You’ve got content going out. Deals are closing. And someone in the boardroom is asking which of it is actually driving pipeline.

    GA4’s attribution reports won’t answer that. They’ll tell you organic search drove 38% of conversions. They won’t tell you which blog post started the journey, which case study shifted the deal, or which landing page closed it. If you’ve tried to dig deeper and hit a wall, this post is for you.

    I’ll cover what GA4’s attribution actually does, where it breaks down, and how to get genuine multi-touch attribution from your GA4 data, connected to HubSpot deal values, with no code required.

    What GA4’s Multi-Touch Attribution Shows vs. What B2B Marketers Actually Need

    To be fair, GA4 does provide meaningful attribution context. Its Advertising reports include model comparison tools and conversion path analysis, and its data-driven attribution model allocates credit across multiple touchpoints rather than relying on last-click assumptions. For many organisations, this is enough to understand how channels contribute within broader conversion journeys.

    Where it starts to break down is when you’re asked to connect that activity to revenue.

    GA4

    What B2B Teams Actually Need

    Granularity

    Channel-level credit

    Page-level impact (which exact content touched which deals)

    Outcome

    Form fills, demo requests

    Closed revenue and influenced pipeline

    Buying cycle

    90-day lookback

    12+ month journeys, end to end

    Reporting

    Aggregated, anonymised

    Deal-level journeys you can inspect

    Data scope

    GA4 only

    GA4 joined to CRM, contacts, deals, close dates

    Attribution model

    Blended, opaque

    First, last, and full path, side by side, explainable

    None of this is a knock on GA4 as a product. It’s built as a web analytics tool, not a revenue attribution platform. The problem is that a lot of content promising “multi-touch attribution in GA4” either ignores this distinction or acknowledges it briefly before sending you down a path that requires engineering work most marketing teams can’t prioritise.

    Why Building Multi-Touch Attribution in GA4 Is Harder Than It Looks

    Assume you’re a marketing director at a B2B SaaS company, Series B, £8M ARR. You have GA4 connected to your site, HubSpot as your CRM, and a small but productive content team. You decide to build proper multi-touch attribution. Here’s what happens next.

    #

    Barrier

    What It Means

    1

    The BigQuery Barrier

    GA4’s UI-level attribution is built on sampled, aggregated data. What it doesn’t show you is the full journey: every page visit, every session, every touchpoint in every buyer journey.

    Getting to that data requires setting up the BigQuery export, writing SQL to reconstruct journeys from the raw events tables, handling the three ways GA4 fragments sessions across devices and time, applying an attribution model, and presenting the output in something leadership can read.

    That’s weeks of engineering work before you’ve answered a single marketing question.

    2

    The 90-Day Limit

    GA4’s DDA model operates within a 90-day lookback window. For B2C companies with short conversion cycles, that’s plenty. For B2B SaaS companies where a qualified prospect might read a blog post in January, attend a webinar in March, and sign a contract in May, that 90-day cap means the early-funnel touchpoints that started the journey simply disappear from the attribution model.

    Also: DDA requires approximately 600 conversions per month per conversion event to generate reliable model outputs. Most mid-market B2B teams don’t come anywhere near that threshold. Which means even if you stay within the 90-day window, you may be looking at model outputs that GA4 itself can’t produce reliably from your data volume.

    3

    The Revenue Gap

    Even if you clear the first two walls, even if someone does build the BigQuery pipeline and you get clean journey data out of it, you’re still attributing to conversion events, not revenue.

    A form fill is not a closed deal. A demo request is not £120k ARR. GA4 has no native connection to HubSpot’s deal records, so there’s no way to answer the question “which content influenced closed-won deals?” without someone manually correlating GA4 export data against HubSpot reports.

    How to Set Up Multi-Touch Attribution in GA4, Step by Step, With AttributeIQ

    If you’ve been considering the BigQuery route but haven’t had the engineering resources to pursue it, this is the genuinely no-code path.

    Step 1: Connect Your GA4 Property to AttributeIQ

    When you create an AttributeIQ account, the onboarding flow starts with a GA4 connection.

    AttributeIQ will ask you to select which GA4 property to connect. If you have multiple properties, pick the one where your main conversions are tracked.

    2

    Select Your GA4 Property

    nexa-marketing (GA4)
    nexa-marketing (GA4 Property)Current
    nexa-prod (GA4 Property)
    nexa-staging (GA4 Property)
    client-brightwave (GA4 Property)
    Continue
    or+ Add another property

    Once you’ve selected your property, AttributeIQ automatically starts syncing your raw GA4 event data from BigQuery. There’s no implementation project to manage or tracking changes to deploy. Most teams are connected and waiting for their first data sync within 24 hours of signing up.

    Step 2: View the Multi-Touch Attribution Report

    In AttributeIQ, go to Multi-Touch Attribution in the left nav. We’re using demo_request as the conversion event in this example, so what you’ll see here is every blog post that appeared in a journey that ended with a demo request, broken down by the role each post played.

    AttributeIQAttributeIQ
    7 days
    demo_request

    Multi-Touch Attribution

    See every page influencing conversions, with journey position breakdown.

    2 days
    7 days
    28 days
    More
    Page containsblog

    Total Conversions

    46

    Avg Journey Length

    1.1

    Most Influential

    /blog/ai-seo-...

    Top Mid-Journey

    /blog/measuring-...

    All Pages
    Solo Closer
    Entry
    Mid-Journey
    Closer
    Recurring
    13 pages

    Page Coverage

    Reach by page (% of converting journeys). Colour = journey role

    /blog/sales-pipeline-stages
    88%
    /blog/how-to-forecast-sales
    85%
    /blog/b2b-sales-lead-scoring
    72%
    /blog/automating-follow-up-emails
    68%
    /blog/sales-rep-onboarding
    52%
    /blog/reducing-sales-cycle-length
    50%
    /blog/crm-dashboard-metric
    38%
    0%2%4%6%8%
    PageReachJourneysRole Distribution
    /blog/sales-pipeline-stages
    88%of journeys22
    /blog/how-to-forecast-sales
    85%of journeys21
    /blog/b2b-sales-lead-scoring
    72%of journeys22
    /blog/automating-follow-up-emails
    68%of journeys17
    /blog/sales-rep-onboarding
    52%of journeys13
    /blog/reducing-sales-cycle-length
    50%of journeys12
    /blog/crm-dashboard-metric
    38%of journeys9
    Entry
    Mid-journey
    Closer
    1 / 2 →

    Here’s what each part of the dashboard is telling you:

    #

    Metric

    What It Means

    1

    Total Conversions

    The number of demo requests where the buyer visited at least one blog post before converting. This is the pool everything else is calculated against. Change the date range and the number updates, along with every reach percentage and journey count below it.

    2

    Avg Journey Length

    The average number of pages a buyer visited before requesting a demo. A 1.1 average, like you see here, means most people converted after reading a single blog post. A higher number (say, 4 or 5) would suggest buyers are doing more research before they’re ready to talk. Neither is good or bad, it’s context for how your funnel actually works.

    3

    Most Influential

    The page that appeared in the highest percentage of converting journeys, regardless of role. It doesn’t mean it closed the most deals, it means it showed up most consistently across the widest range of buyers.

    4

    Top Mid-Journey

    The page that appeared most often in the middle of journeys. If a post keeps showing up here, buyers are returning to it during consideration. It’s not pulling them in, but it may be what’s keeping them moving.

    5

    Page Coverage Chart

    The bar chart above the table ranks every blog post by reach, with each bar colour-coded by journey role. Mostly teal means it’s an entry page, mostly grey means mid-journey, mostly purple means it’s a closer.

    6

    Reach

    The percentage of converting journeys that included this page.

    7

    Journeys

    The raw number of converting journeys this page appeared in.

    8

    Role Distribution

    The bar on the far right of each row shows the breakdown of journey roles for that page across all its appearances: Entry, Mid-Journey, Closer. A page that’s almost entirely Entry is a top-of-funnel puller. A page that’s mostly Closer is doing the final convincing. The interesting ones are the mixed bars, pages that play different roles for different buyers depending on where they are in their cycle.

    Step 3: See Every Conversion Path Behind Any Page

    Click the chevron next to any page in the table and AttributeIQ expands every converting journey that included it, in full, in order, with dates and days-to-convert.

    You can see exactly what a buyer read before they requested a demo, what they came back to, and where your blog post sat in the sequence relative to everything else.

    JOURNEYS THAT INCLUDED /BLOG/SALES-PIPELINE-STAGES: 22 JOURNEYS

    Buyer #12 Jundemo request
    11 days
    1
    /blog/sales-pipeline-stages
    2
    /blog/how-to-forecast-sales
    3
    /pricing
    4
    /blog/b2b-sales-lead-scoring
    5
    /demo
    converted
    Buyer #25 Jundemo request
    1 day
    1
    /blog/sales-pipeline-stages
    2
    /pricing
    3
    /demo
    converted
    Buyer #38 Jundemo request
    7 days
    1
    /blog/reducing-sales-cycle-length
    2
    /blog/b2b-sales-lead-scoring
    3
    /blog/sales-pipeline-stages
    4
    /demo
    converted
    Showing 1–3 of 22 journeys
    1 / 5

    Step 4: Connect HubSpot to Match Journeys to Real Deals

    GA4 alone can tell you which pages were visited by users who converted. What it can’t tell you is who those users were, what company they’re from, or what deal value is attached to their journey.

    To close that gap, head to Settings → Integrations → HubSpot inside AttributeIQ and click Connect HubSpot. You’ll be taken through a standard OAuth flow, authorise access, get redirected back, and you’ll see your portal ID confirmed and the status showing “Connected.”

    Property

    NexaPathora
    HS

    HubSpot CRM

    Portal ID: 146264324

    ConnectedDisconnect

    Sync Contacts

    Pulls contacts with a ga4_client_id property and their associated deals into your account. Last synced 6/7/2026 (96 contacts).

    Contacts sync automatically every 6 hours.

    Once HubSpot is connected, you’ll be able to see the complete, end-to-end buyer journeys for every deal, from first anonymous touch in GA4 through to closed-won revenue, including every page viewed, every return visit, and the full sequence that led to conversion and beyond.

    Daniel Hughes / Orbitly

    daniel@orbitly.io

    Deal

    £24k

    contract sent

    Conversion Event

    demo_request

    Touchpoints

    3

    Duration

    5 days

    First TouchMar 19 · Organic / Google · 4m 22s on page

    /blog/attribution-guide

    TouchpointMar 22 · Direct · 3m 08s on page

    /case-study/10m-arr

    Last TouchMar 24 · Direct · 1m 44s on page

    /pricing

    Conversion!

    demo_request · 24 Mar 2026

    Presentation Scheduled

    Post-conversion visit

    /case-study/enterprise-roi

    Contract Sent

    See every content interaction
    from first visit to closed deal.

    AttributeIQ shows page-level pipeline attribution natively over your existing GA4 and HubSpot stack, live within 24 hours.

    Try 14 days for free →

    Nexa Corp · Journey

    Best MTA tools 2026

    Blog · Organic · Day 1

    Attribution guide

    Blog · Organic · Day 12

    Case study: Intercom

    Blog · Organic · Day 28

    Pricing page

    Direct · Day 31

    The Attribution Models Available, And Why They’re All Visible at Once

    One of the more frustrating experiences in attribution tooling is being asked to commit to a model before you’ve seen the data. First-touch or last-touch? Linear or time-decay? Position-based? The honest answer for most B2B teams is that the model choice depends on what question you’re asking, and forcing a pre-selection means you only ever see the answer to one of them.

    AttributeIQ doesn’t ask you to choose an attribution model up front. Instead, it presents first-touch, last-touch, and multi-touch attribution side by side as a default view. You see the same journeys through different attribution lenses without needing to reconfigure or re-run queries.

    • First-touch: 100% of credit is assigned to the first interaction in the journey. This highlights the content and channels that initiate new relationships.
    • Last-touch: 100% of credit is assigned to the final interaction before conversion. This highlights the content that drives conversions and closes deals.
    • Multi-touch (linear): Credit is distributed evenly across all interactions in the journey. This provides a balanced view of how multiple touchpoints contribute across the full buyer journey.

    The ability to compare models side by side is valuable for a reason: different attribution models produce different channel and content valuations. Seeing them simultaneously protects you from over-indexing on any single model’s bias.

    How B2B SaaS CMOs Use Multi-Touch Attribution Data to Drive Decisions

    Attribution data that sits in a dashboard nobody checks is just overhead. Here are three ways CMOs at B2B SaaS companies are using it to change decisions.

    #1 Prove Content ROI to the Board

    Most CMOs walk into budget reviews knowing the content programme is working, but not being able to prove it in language the board responds to.

    AttributeIQ’s Board Summary solves that in a single view. Qualified pipeline, closed revenue, average deal size, top account, channel breakdown, and the five content assets that appeared in the most closed deals, all scoped to a defined period, all in one place, with a one-click PPTX export.

    AttributeIQAttributeIQ

    Board Summary

    Export a board-ready summary of marketing’s influence on pipeline and revenue.

    Q2 2026 · Board Summary · 1 Apr 2026 – 30 Jun 2026

    Qualified Pipeline

    £4.1M

    from 47 contacts

    Total Revenue

    £1.27M

    from 14 closed deals

    Avg Closed Deal

    £90.7k

    from 14 closed deals

    Top Account

    Nexa

    £340k influenced

    Channel Breakdown
    Organic / Google
    £1.68M41%
    Paid / Google
    £902k22%
    LinkedIn / Social
    £697k17%
    Direct
    £451k11%
    Referral
    £246k6%
    Email
    £123k3%
    Top 5 Content in Closed Deals
    PageDeals ContainingRevenue Influenced
    /pricing14/14 (100%)£1.27M
    /case-study/10m-arr11/14 (79%)£1.01M
    /blog/cmms-vs-spread..9/14 (64%)£823k
    /homepage14/14 (100%)£1.27M
    /b2b-saas-seo-audit g..7/14 (50%)£635k

    #2 Optimise Budget Allocation

    Channel-level attribution tells you organic search is working. Page-level attribution tells you which part of organic search is working, and more importantly, which content isn’t appearing in closing journeys despite generating traffic.

    A blog post that gets 3,000 sessions a month but never appears in a journey that converts to a deal is a different editorial brief than one. You might keep writing it, but you’d write it differently, position it differently, or repurpose the slot for something that does show up in closed-won paths.

    #3 Accelerate Deal Velocity

    The Journey Explorer inside AttributeIQ lets you see which page sequences are associated with shorter time-to-close. If you identify patterns, “users who visit a case study convert 40% faster than those who don’t”, you can actively replicate create more paths to that page, through CTA placement, email nurture, or content recommendations.

    If any of these use cases describe a gap in how you’re currently reporting or allocating budget, AttributeIQ is built to close it. GA4 and HubSpot connect in minutes, and the Board Summary, Journey Explorer, and channel attribution are all live from day one. You can start a free trial here.

    Muiz Thomas, Founder & CEO of AttributeIQ
    Author
    Muiz Thomasin
    Founder & CEO, AttributeIQ
    Muiz is the founder of AttributeIQ, a multi-touch attribution platform for B2B marketing teams, and GrowUp, a B2B search agency. He started building attribution tooling because he got tired of writing “directional.” in client reports as a way of saying “I can’t actually prove this.” He works mostly with SaaS, construction tech, and enterprise software teams, and has helped connect marketing programmes to £5M+ in qualified pipeline.