In complex sales, exact attribution is out of reach: long cycles, several people, offline channels, and a first contact nobody recorded. Three imperfect readings are still enough to decide: the customer-declared first contact, pipeline share by origin, and the stop test. The question is not who deserves credit, it is where to put the next euro.
Attribution is the subject that produces the most internal debate for the fewest decisions. Marketing claims deals sales believe they closed alone, everyone produces their table, and nobody changes anything about budget allocation.
The cause is not a missing tool. It is that the question being asked is the wrong one. Looking for who deserves credit for a deal is a question about sharing merit, and the data cannot answer it in complex sales. The useful question is different: where does the next euro go.
Why exact attribution is out of reach
Four obstacles compound, and none is solved by tooling.
The cycle is long. Between first contact and signature, six to eighteen months can pass. Tracking identifiers expire, devices change, people change jobs. Part of the journey is lost before the deal even opens.
Several people decide. The user read your article, the buyer saw an advert, the executive heard about you from a peer. You measure individual contacts and the purchase is collective.
Part of the journey is not digital. A conversation at an event, a referral over dinner, a former colleague citing you. Those contacts are often the most decisive, and they leave no trace.
The real first contact is almost never recorded. When someone fills in your form, they have often known you for months. The channel that gets the credit is the last one, the one that harvested, not the one that built.
What multi-touch attribution actually does
It splits credit between known touchpoints, with weightings. The problem is not the method, it is the precision on display: it produces percentages to two decimals from an incomplete journey.
The result is a number that is incontestable without being accurate. Nobody argues with a calculated figure, so it steers budget with an authority its quality does not justify. It is the same flaw as forecast weighting laid over badly defined stages, described in making your sales forecast reliable: sophistication makes the error more credible without reducing it.
It has a second effect, a political one. As soon as attribution establishes who won what, each team defends the model that serves it, and the conversation stops being about decisions.
Reading one: the declared first contact
The simplest, and the most underused. One question in your form or in the first meeting: how did you hear about us.
It is declarative, therefore imperfect: people forget, simplify, cite their most recent memory. It is still far closer to reality than last click, because it is the only reading that captures referral, word of mouth and offline contact, which is often most of it.
Two precautions make it usable. Ask it as an open field rather than a closed list, at least at first, otherwise you will never discover the origins you had not thought of. And have the salesperson fill it in after the meeting rather than the prospect in a form: the quality is not comparable.
Reading two: pipeline share by origin
Rather than attributing a deal to a channel, look at the overall split: what share of your pipeline, then of your signed revenue, comes from each broad origin, over a rolling twelve months.
This reading does not say who did what on a given deal. It says whether a channel produces, and whether its contribution is rising or falling. That is exactly the information you need to arbitrate a budget, and it tolerates imprecision: a channel going from 30 to 15 % of pipeline shows up despite imperfect data.
It also monitors dependency: beyond sixty to seventy per cent on a single origin, you have a fragility, a point we develop in splitting your demand generation budget.
Reading three: the stop test
The most honest, and the least practised because it is frightening.
Stop a channel for a quarter and watch what happens. It is the only causal measurement available to you: everything else is correlation. A channel whose suspension changes nothing in the pipeline was not producing, whatever share your model assigned it.
It needs two precautions. Pick a representative quarter, not a quiet period. And account for the lag: a long-horizon channel takes months to stop producing, so its suspension does not read immediately. For fast-effect channels, the test settles the matter in six weeks.
What to put in place
Nothing sophisticated, and all of it assumes a clean foundation, the subject of building your revenue operations foundation.
An origin field per deal, filled in by the salesperson, with a short and stable list. A first-contact date, even approximate. And a quarterly review where you look at the split and decide on a budget shift, however small.
That last point matters most: a measurement that never triggers a decision is useless, and a rough reading that moves a budget beats a refined model that feeds a debate.
Where to start
Take your last twenty signed deals and call five of them with one question: how did you first hear about us, and what made you get in touch that day.
The answers will not look like your attribution table. That is precisely the point of the exercise, and it costs an hour.
Frequently asked questions
- Which attribution model should you use in B2B?
- No single model works in complex sales: the cycle is long, several people are involved, and part of the contact never gets tracked. Use two complementary readings instead, first contact and pipeline share by origin, knowing what each one ignores.
- Why does multi-touch attribution disappoint in B2B?
- Because it splits credit with a precision the data does not carry. It ignores conversations, referrals and events, and it assigns percentages to two decimals from an incomplete journey. The number becomes incontestable without becoming accurate.
- How do you measure an untrackable channel?
- By asking the customer. One question in the form or in the first meeting, 'how did you hear about us', gives declarative information that is imperfect but far closer to reality than last click. It captures referral and word of mouth, invisible otherwise.
- What should attribution be used for?
- To decide where the next budget goes, not to split credit between teams. As soon as it establishes who won what, each team defends its own model, and measurement becomes a political matter rather than a decision tool.