If you’ve worked at a B2B company that uses an ABM strategy for their Go To Market and has an SDR team you have inevitably run into the problem of lead attribution.
In B2C or e-commerce these problems exist, too. Was it the Facebook ad that helped us drive the sale? Or was it the blog, or the TV ad? What’s the impact of each? It’s hard to know.
But in enterprise B2B, it gets even more complex — you don’t just care about the person, but the full account. Moreover, you must measure lead attribution at the moment it becomes an SQL, rather than waiting for purchase, due to long sales cycles.
It’s tough. Maybe one person attended a webinar, a different one stopped by your booth at a trade show, but it was the CRO’s assistant that sent a demo request after the SDR had cold emailed the VP of Marketing and connected with the Sales Ops Manager on LinkedIn. Good luck with lead attribution in that scenario.
What was the percentage influence of each action to get the meeting? In this article, we’ll discuss the fallacies of current attribution models and propose a better alternative.
The foundations of the marketing/sales attribution problem
Attribution is rarely single-source. If a demo request comes in from an account that was never reached out to by an SDR, it’s purely a marketing lead. The opposite is also true. A net new account scheduled for a meeting via a cold call, is purely an SDR sourced lead. The problem arises in the middle. What if there were a lot of interactions with the account like in the example above?
It’s impossible to split the perfect percentage influence of strategies. It would be crazy to think you can build a model that would perfectly capture attribution to 23% webinars, 18% trade show booths, 15% SDR phone outreach, and 12% LinkedIn outreach. Stop lying to yourself.
Time-based lead attribution in B2B
The most common method is to have a time-based attribution. This was stolen from the B2C world as a purchase coming from a user that clicked an ad 12 days before, can still be attributed to that ad (especially if the item was added to cart then).
In enterprise, it’s commonly between 30 and 90 days. If a lead sends a demo request 23 days after a trade show, we’ll count it as a trade show-driven lead. If they do it three days after a webinar, it’s a webinar lead. So far, so good.
Until you add an outbound SDR to the equation.
Let’s assume a 45-day timeline is being used. Here are two scenarios.
Webinar + Outbound
A prospect comes to a webinar. They get added to a webinar follow-up sequence. Three weeks go by, no response. Twenty days later, the same account gets targeted by an outbound SDR. A meeting is set! It’s been 42 days since a lead came to your webinar, and your current attribution of 45 days says “webinar”. You might argue 45 days is too long. The SDR deserves credit – make it 20 days!
Outbound Driving Inbound
SDR sets a cold outbound demo. Meeting is held. Prospect tells the AE “This is awesome, but we’re too busy. I need six to nine months.” AE offers to follow up and drip content. Prospect declines. “I have all I need, I’ll contact you later.” The AE doesn’t want a deal in the pipeline with no next steps for six months, so they mark it closed-lost.
Five months later, that same lead comes inbound via a demo request. Your rule says 45 days, so lead attribution is listed as organic search. This means the SDR no longer has credit for this lead, which moves to the pipeline very quickly. Commissions for the SDR won’t happen here.
You might argue 45 days is too short; let’s make it 180. But that’s not really the solution.
Time-based attribution is fine for B2C, but it’s a fallacy for B2B companies with outbound SDRs.
To eliminate timelines, some companies have decided to just use a last-touch attribution. If the SDR gets the meeting, it’s SDR sourced. If marketing gets the meeting via demo request or form-fill, it’s marketing sourced. If the other department touched the lead, you mark it as “influenced by,” but is this really helpful?
If you have a limited number of target accounts, it’s easy for marketing to claim to influence all opportunities. They could email every target account every 89 days to ensure they are seen as an influencer in any meeting scheduled by the SDRs.
However, SDRs in the enterprise are more strategic and work 30 to 80 accounts at a time, so a last-touch attribution comes across as biased toward marketing, and SDR commissions get muddy.
What’s more helpful than time-based or last-touch is to have a few buckets and categories?
- Inbound: Marketing teams that have properly set up lead routing know that the response time for a Demo Request, Pricing Inquiry or Chat, should be as fast as possible. Therefore these leads fall into one bucket, and get routed with high urgency to SDRs or AEs.
- Hot accounts: Another bucket is for leads that might have a certain amount of interaction with content on the website – read two blogs, clicked on features, clicked on pricing, downloaded an eBook – have surpassed the lead scoring threshold and have high priority, but SDRs should wait for one to 24 hours to reach out
- Warm accounts: There might be some leads that had a bit of interaction with the website, like just one interaction with gated content.
- Cool accounts: Another bucket might be leads from intent data, or perhaps you’re buying leads from a third-party website that writes articles about your industry.
- Cold accounts: Finally, there’s the “export a list and dial away!”
It’s not always five buckets. You might have three, you might have seven. But if marketing has created these separate buckets, great job! This makes the life of sales development much easier, as each bucket requires a different strategy.
Working different buckets
The inbound ones require a bit of research to ensure they’re within the ideal customer profile (ICP): employee count, geography, industry, and a friendly message to engage.
The hot accounts also require some research and some helpful messaging: “[Name], I see you downloaded our eBook! A lot of people also enjoy this article and this webinar to learn more about [problem]. Find them attached. Finally, if you’d like to talk to a [problem] expert, I’d be happy to schedule a call!”
The warm accounts are suspects and require you to explain the value and reel them in. Try something like “[Name], it might not be you, but according to Bombora, someone at [Company Name] has been researching [solution]. Am I off base? I’d appreciate it if you pointed me in the right direction so we can offer some resources to your team!”
The cold accounts require a pure cold strategy.
Solving the muddy waters of attribution
The reason to reach out, and the bucket you got the lead from, is the driver of how easy or hard it will be to get a meeting.
A sequence about the tradeshow happening in two weeks is only possible if marketing pays for a booth, so if a lead responds to it, marketing deserves credit. A “reheat of webinar attendees” sequence where 1000 leads get added would also give credit to marketing as that sequence would not work without them attending the webinar.
The type of sequence used will tell you which bucket of attribution this falls into regardless of timeline or final touch.
It’s incredibly important to create these buckets in advance. You can’t decide the percentages after the fact. For inbound demo requests, marketing is driving 90% of the interest. For the lead-scored hot accounts, they convert at a high rate, and marketing gets a good chunk of the credit. It’s a sliding scale all the way to SDRs getting 100% of credit for cold accounts.
Each company should determine their own percentages, but here’s a good starting point if you need some help:
The final thing is to determine your decay time and the service-level agreement (SLA). Every lead added to hot or warm must be worked by SDRs within seven days. Once added to the sequence, it gets moved to cool leads where it stays for 30 days.
Once you see the graph above, you might scroll back up and re-read the examples and get how this solves case number one. If the SDR picked the lead from the hot bucket after the webinar, and the lead had responded to the sequence, it was considered a hot lead, so marketing would get 60% credit, but since it got picked up from the cool leads bucket and scheduled through a cool outbound sequence, it’s a cool lead, so marketing gets 15% credit.
Now there can be a formula to determine the ROI on marketing initiatives. Remember that your attribution percentage might be different!
How about case number two? That inbound lead that came five months after their first demo? Would that just be inbound? Isn’t that unfair? You’re right. There’s one last issue to solve here.
The time-based attribution is not a good way to determine the percentage contribution of scheduling the first meeting. However, it’s a good way to determine if a meeting that comes back after it was marked lost should be attributed to a previous bucket. You can use a 12–18 month attribution (starting from the initial discovery call) depending on ACV.
If the first meeting was cold, and the lead is revived within 12 months with a demo request, it’s still cold. Similarly, if the first meeting was booked from hot and gets revived from cold, still mark that as a hot bucket for measuring ROI of marketing initiatives.
That should still not affect SDR comp, which is structured properly for the enterprise. Now you have a new, improved model as a CRO to determine the attribution of each marketing initiative on the meetings generated. This is incredibly important as it will help determine the investment in each initiative.
In the rare instances that leads come inbound after being marked closed-lost, ask the prospect if they’d like to talk to the same AE they worked with before or if they want a new contact.
Many times, there’s a mismatch between the AE and the prospect’s personality, and even though the prospect might like the solution, they did not enjoy working with your AE. But that’s another story for another day. Now, go change your attribution methods and make sure you invest in the right demand generation motions.
Also published on Medium.