One journey, from first visit to closed deal
Your buyers see a LinkedIn post, download a whitepaper, meet you at an event and sign a contract months later. Each step sits in a different tool. We connect them, for each person and each account.
Web analytics sees the first visit. The deal happens somewhere else.
On a long sales cycle, most of what decides whether a click was worth anything happens after it. Qualification, sales calls, the contract. That lives in the CRM, the email tool and the event list, not in web analytics.
So reporting falls back to what is easy to count: cost per lead. Campaigns that bring cheap volume look like winners. Channels that bring deals that close can look expensive.
What you can see once the journey is connected
Not every team needs all of these. Most start with one question they can't answer today.
Which channels bring deals, not just leads
Compare channels on pipeline and closed revenue, alongside cost per lead.
What happened before a deal closed
Open a closed deal or an account and see the steps that led to it, across marketing and sales.
Which content and events move deals forward
Whitepapers, webinars and events read against the opportunities they show up in.
Where thought leadership shows up
LinkedIn engagement and the sources buyers name on calls, next to the click data.
Channels judged on your sales cycle
Results read by acquisition month, so a channel isn't written off before its deals close.
Ad platforms aimed at deals
Closed revenue sent back to Google and Meta, so they stop optimising for cheap leads.
Every touchpoint we connect, from first ad to renewal
Which of these matter depends on how you sell. Most teams need a handful, not all of them.
Awareness
01- Paid adsGoogle, Meta, LinkedIn Ads
- Founder and thought-leader postsLinkedIn engagement
- Podcast and newsletter sponsorshipsSurvey answers, vanity URLs
- Website visitsGA4, Amplitude, Snowplow
Engagement
02- Whitepaper and guide downloadsHubSpot, Marketo forms
- WebinarsLuma, Zoom, ON24
- Events and conferencesBadge scans, event lists
- Lifecycle and nurture emailsHubSpot, Marketo, Customer.io
- Trial or sign-upProduct analytics
Sales
03- SDR sequencesOutreach, Salesloft
- Sales calls, and the source the buyer namesGong, CRM fields
- Demo and opportunity stagesSalesforce, HubSpot
- Proposal and contractDocuSign, PandaDoc
- Closed won, first invoiceCRM, Stripe, billing
After the sale
04- RenewalBilling, CRM
- ExpansionBilling, CRM
Not on the list? We connect through standard APIs, custom APIs or scraping, so we can find a way to get the data that's relevant to you.
Together, this gets you one journey per person
| Data source | Event name | Timestamp | Channel | Initiative |
|---|---|---|---|---|
| LinkedIn Ads | ad_click | 04/02/2026 10:12 | LinkedIn Ads | ABM, marketing leaders |
| post_engagement | 12/02/2026 08:40 | Founder posts | ||
| HubSpot | whitepaper_downloaded | 12/02/2026 09:05 | Content | B2B attribution guide |
| HubSpot | email_clicked | 20/02/2026 14:31 | Lifecycle email | Nurture sequence |
| Luma | webinar_attended | 05/03/2026 16:30 | Webinar | Measuring long cycles |
| Event list | badge_scanned | 18/03/2026 11:15 | Event | Industry conference |
| Salesloft | meeting_booked | 19/03/2026 09:48 | SDR | Event follow-up |
| Gong | source_stated | 26/03/2026 15:02 | Podcast | Industry podcast |
| Salesforce | opportunity_created | 26/03/2026 15:40 | ||
| DocuSign | contract_sent | 14/05/2026 10:20 | ||
| Salesforce | closed_won | 02/06/2026 17:05 |
How we stitch every tool into one journey
We build a pipeline from each source into a warehouse, then unify the data with dbt models.
The models match records on what they share: email address, name and company, click IDs and CRM IDs. Contacts then roll up to their account, so one opportunity carries the journeys of everyone involved. Touches that don't match stay separate rather than guessed.
or read about how we build Marketing Data Foundations
Attribution for journeys that are long and overlapping
A B2B deal can run for months, involve several people and pass through most of your channels. Some touches start the deal. Others keep it moving. A single model that gives all the credit to one click misses most of that.
We build the foundation and suggest a starting set of rules. Which touchpoints get the credit is your decision, and the rules can be whatever fits how you sell.
Separate models for leads and revenue
Demand gen reads which channels bring good leads. Sales-aligned marketing reads which bring revenue. Each model uses the data that fits its stage.
Sourced and influenced, kept apart
One rule we often suggest: count the touch that started an opportunity separately from the ones while it was open. Whether you use it, and how, is up to you.
Overlap split by rules you agree on
When several channels and people touch one deal, the rules decide how credit is shared. There's no single right split. We suggest one, you decide, and you can see how results change under another.
What buyers say, next to what the data shows
Podcasts, LinkedIn posts and word of mouth rarely leave a click. The source a buyer names on a call or form sits next to the observed journey.
Windows that match your sales cycle
Results are read by acquisition month, with lookback windows set to how long your deals take. Channels aren't judged before their deals have had time to close.
Rules in plain language
Your team can read each rule in our interface, look up a deal to see where credit went, and request a change without going through a data team.
One limit to be honest about: you're always reading a delayed signal. Connecting the journey makes the delay visible. It doesn't remove it.
or read about how we build Triangulated Attribution
Ad platforms that optimise toward deals, not cheap leads
Ad platforms optimise toward what you send them. If you send every lead as equal, they find you more cheap leads.
The same foundation fixes that. Once the CRM is connected, we can send qualified opportunities and closed deals back as conversions, with their value. Google Ads takes them as offline conversions. Meta takes them through the Conversions API.
A deal that closes months later can be too late for a platform to use. So we usually send an earlier stage as well, and check over time whether it predicts the deals that close.
FAQs
How do you credit a touch that influenced a deal but didn't start it?
That's your call. We define the rules together with your team, and they can be set however fits how you sell. We'll suggest a starting point, like counting influenced touches separately from the one that started the deal, but the decision is yours.
How do you handle deals with several decision makers?
We build the foundation so each contact keeps their own journey, and all of them roll up to the account and the opportunity. How credit is shared across those contacts is a rule you decide, with our suggestions as a starting point.
What if a buyer names one source and the click data shows another?
We keep both. They often answer different questions: the click shows how someone arrived, the stated source shows what they remember making the difference.
How long are the lookback windows?
We suggest windows based on how long your deals take from first touch to close. You decide what to use.
Can you connect a tool that isn't listed here?
Yes. We start with standard APIs, then build custom connectors or scrape where there's no other way in.
How do you match people across tools?
On shared identifiers like email, name and company, click IDs and CRM IDs. Some touches won't match, and we keep those separate rather than guess.
What happens when leads are merged or reassigned?
The models keep the original source attached through to closed won.
Do we need to change how we use our CRM?
Sometimes. If stages or source fields aren't filled in consistently, we'll show you where and what to change.
How long before the numbers are useful?
The foundation goes in during the first two to three months. Revenue-stage numbers get more useful as deals from that period close.
We have no data engineer. Can we still do this?
Yes, that's the usual case. We build and run the pipelines.
