In ABM, deals have many parents. Multiple plays touch multiple stakeholders over months. So when you close a deal, who gets credit?
Without a clear attribution model, you'll have turf wars. Marketing says they drove it. Sales says they closed it. Neither gets resources. Your ABM program starves.
A sound attribution model answers the question fairly and makes everyone better.
Traditional last-touch attribution says: "The last interaction before a deal closes gets 100% credit."
That's wrong for ABM. Here's why:
A deal closes with touchpoints like: 1. Week 1: Marketing cold inbound email (CMO opens) 2. Week 3: AE discovery call (CMO + VP Demand Gen on call) 3. Week 4: Marketing sends case study (VP Demand Gen reads) 4. Week 6: Sales sends proposal (IT Director reviews security docs) 5. Week 8: AE final call (CMO signs off) 6. Week 9: Deal closes (IT Director sends PO)
Last-touch says IT Director + the PO email get 100% credit. That's absurd. Marketing touched multiple stakeholders early. Sales closed it at the end. Both matter.
A good attribution model credits the entire sequence.
The simplest model: divide credit equally among all touches.
6 touches = each gets 16.7% credit.
Pros: - Simple to calculate - Fair to all functions (marketing and sales get credit) - Easy to explain to finance
Cons: - Doesn't recognize that early touches (finding and engaging an account) are different from late touches (negotiating terms) - Doesn't account for the magnitude of impact (an email that sat unread is weighted the same as a call that booked a meeting)
When to use: Early in your ABM program when you just need to prove that both teams matter.
Formula: Credit per touch = Deal value / Number of touches
Example: $250K deal, 6 touches = $41.67K per touch
Weights recent touches more heavily than early touches.
Example: Last touch gets 50% credit, previous touches decay backward.
Touch 1 (week 1): 3% Touch 2 (week 3): 5% Touch 3 (week 4): 7% Touch 4 (week 6): 10% Touch 5 (week 8): 25% Touch 6 (week 9): 50%
Total = 100%
Pros: - Reflects the sales reality that recent touches (AE calls, negotiations) drive close - Doesn't say marketing created the deal, but does credit early engagement - Standard in Salesforce, HubSpot, Marketo
Cons: - Can undervalue the work of initially finding and engaging the account - Requires clear definitions of what counts as a "touch"
When to use: When you have 3-6 month sales cycles and clear hand-off moments from marketing to sales.
Formula: Use a decay curve. Assign points backward from close: - Last touch: 50 points - 2nd to last: 25 points - 3rd to last: 15 points - 4th to last: 7 points - 5th to last: 2 points - Older: 1 point
Total points for deal, then apportion revenue by point share.
Different accounts need different attribution because their buying cycles differ.
Cold to close (long cycle, multiple stakeholders): - First touch (finding account): Assign weight to discovery phase - Middle touches (engagement, demos): Assign weight to engagement phase - Late touches (negotiation, close): Assign weight to closing phase
Warm to close (account already talking to sales): - First touch (meeting request): Assign weight to meeting request phase - Middle touches (product fit, fit validation): Assign weight to evaluation phase - Late touches (negotiation): Assign weight to closing phase
Existing customer expansion (short cycle): - First touch (identifying expansion opportunity): Assign weight to opportunity identification - Late touches (proposal, close): Assign weight to closing phase
This model reflects that different plays carry different weight in different contexts.
Pros: - Most fair to actual revenue driver - Accounts for different deal types and cycles - Aligns incentives across teams
Cons: - More complex to implement - Requires clear account segmentation - Harder to explain to finance (but easier to defend)
When to use: When you have multiple deal types (new customer, expansion, multi-year renewals) and clear metrics showing which touches drive which type.
Instead of touches, assign credit by play.
Example:
Cold inbound play: Assign weight based on historical data Warm engagement play: Assign weight based on historical data Sales AE final negotiations: Assign weight based on historical data
If a deal involved all three plays, each gets its allocated share.
Pros: - Directly incentivizes building strong plays - Maps to how you actually structure ABM (as plays, not individual touches) - Encourages teams to own specific plays end-to-end
Cons: - Not all plays have equal impact (cold inbound in month 1 is different from AE call in month 6) - Requires clear definition of when each play "fires"
When to use: When your team is organized around plays and you want to measure play performance.
Formula: - Define the expected contribution of each play based on historical data or industry benchmarks - Apportion revenue accordingly - Track actual win rate by play to refine percentages quarterly
Month 1-2: Pick linear attribution (simplest) and implement it in your CRM. - Tag every opportunity with the ABM play(s) that touched it - Divide deal value equally among plays - Report on "ABM-attributed revenue"
Month 3-4: Measure results and refine. - Which plays convert at highest rates? - Do early touches or late touches matter more? - What's the typical number of touches before close?
Month 5+: Switch to time-decay or custom model based on what you learned.
In HubSpot or Salesforce:
Attributing too much to one function - Ensure both marketing and sales perceive the model as fair. Avoid heavily weighting one function over the other.
Changing your model mid-year - This breaks comparison. Pick a model, run with it for 12 months, then refine.
Counting touches that don't matter - An email that sits unread for 30 days and a call that books a meeting are not equivalent. Weight them differently or don't count the email.
Forgetting to validate - Ask AEs: "Do these attribution numbers match your experience?" If they say "We never touch cold accounts; it's always warm leads," your model is wrong.
Attribution isn't just scorecard. It's a diagnostic tool.
Example: Your attribution shows marketing-touches getting 20% of cold inbound deals, but 60% on warm engagement deals.
Insight: Marketing is weak at finding and engaging cold accounts, but strong at nurturing warm ones.
Decision: Double down on intent data and AE outreach for cold accounts. Invest more in nurturing sequences for warm accounts.
That's how attribution drives better strategy.
Don't spend three months on the perfect attribution model. Pick linear, implement it in 2 weeks, measure for 3 months, then improve.
Attribution is a discipline you build over time, not a problem you solve once.
Abmatic provides multi-touch attribution across plays and stakeholders. See how to credit the entire buying journey, not just the last click.