Attribution Modeling Answers That Burning Question: “Which Marketing Activities and Channels are Driving My Revenue?”
When you invest time and budget on marketing, you need confidence that you’re using your resources wisely. For most B2B companies, that equates to knowing your marketing is driving new business—especially if you run a high-growth company or you’re backed by investors that expect a strong, fast return.
But attributing revenue to marketing isn’t just a matter of comparing before-and-after sales figures or counting the number of leads that fill out a form asking to meet with a rep. Many companies seek a deeper understanding of how marketing is contributing to new business wins.
Specifically, they want to know which marketing activities and channels played a role in generating a particular lead and helped turn that buyer into a customer.
What they’re describing is attribution modeling.
Think about the journey a typical B2B buyer takes today.
- It’s mostly online. They’re Googling and website-sleuthing long before they interact with a real human from your company.
- It’s complicated. The plethora of channels you can use to influence them is a good news/bad news situation: Many more ways to connect, but that makes for a fragmented, complex landscape.
- It’s anything but linear. No more “get a brochure in the mail, ask to speak with a sales rep.” A B2B buyer might read an article about your service, notice a colleague mention it on LinkedIn, check out your homepage, see an ad for your service online, go back to your website and read a few blogs, then…you get the picture.
Worse, some B2B products have a long sales cycle. So that non-linear, complex buying journey could take many months, even years. Meanwhile, the buyer is still exposed to your marketing messages and channels. How do you know what role each of these channels played in tipping the scales and converting them to a customer?
Trying to figure out which interactions contributed to the sale, and to what degree, is no simple task. But that knowledge wields tremendous power.
Why Last-Click Attribution Doesn’t Work
It’s like a relay race: If your team wins, you don’t attribute the win solely to the last runner. It was the collective effort that made that win possible. And it’s the same with marketing.
Imagine if a company sees that most of its MQLs conduct an online search right before they fill out a form. The company might decide to invest all their marketing dollars into search engine marketing and pull the plug on another channel, for instance, PR. But maybe a PR mention is precisely what prompted some of those buyers to conduct a search in the first place.
Since most marketing programs and most buyers’ experiences are omnichannel, attributing revenue to marketing should take an omnichannel approach, too. That means not only understanding how a mix of online, offline, paid, owned, and earned exposure is contributing to sales, but how their collective interaction is driving the buyer to a purchase decision.
See what I mean about “not so simple”?
How Omnichannel Attribution Modeling Can Help
An omnichannel attribution model helps to sort all that out by enabling you to quantify how much each channel or exposure contributed to each incremental sale, a term that can mean different things to different businesses. In a SaaS company, an incremental sale might be a current customer adding more license seats. In an engineering firm, it might be signing a new client for a short-term project or long-term program.
The beauty of this approach is it enables you to assess the impact each channel had on its own AND in concert with all the others as they engaged with prospects and converted them to customers.
Let’s say a buyer’s journey progressed from reading an article about your product in a trade journal to seeing a social media post to seeing a banner ad while doing a search for your product type. Eventually, that buyer became a customer. The omnichannel attribution model would attribute a percentage of the sale to each channel involved in moving the buyer to act: in this case, PR, social media, and paid search.
That information tells you how you got to the sales you have today. But attribution modeling can also go a step further: forecasting where you could go tomorrow. You can use the information from the attribution to create a predictive model and run simulations that predict the impact of different mixes of marketing channel investments. This allows you to make informed decisions about how to allocate your resources going forward.
- What happens if we spend 10% more on search engine marketing?
- What if we spend 15% more on content?
- What if we drop our paid search budget by 10%?
By discovering the optimal mix of marketing channels to achieve the greatest number of new business wins, along with the point of diminishing returns for more marketing investment, you’re gaining knowledge that’s worth its weight in gold.
A couple of caveats worth mentioning:
- An omnichannel model is just one of many types of attribution models. The right choice for you is the one that best provides the information you most want to know.
- As with any model, you need to validate it in order to have confidence in the output. But that’s a relatively straightforward exercise. An effective test is to ask the model to predict the outcome of a scenario that’s already occurred, such as your 2022 revenue. The lower the Mean Absolute Percentage Error (MAPE) for that outcome, the more accurate the model is. Your goal would be to deliver a result that has less than a 15% MAPE.
How B2B Clients are Winning with Attribution Modeling
By taking a deeper dive into measuring and optimizing their marketing results, companies that use attribution modeling are realizing some pretty significant benefits.
- Better ROI. Sometimes it’s extremely difficult to measure the return of your marketing, particularly when the sales process is lengthier, like those that take 12 to 18 months to close.
- Better predictability. By analyzing what-if scenarios, you can begin to predict which mix of channels and approaches will yield the best results.
- Better profit optimization. When you know the optimal mix of channels to drive the most incremental profit, you can optimize your marketing budget for the best return. Some models can even help you drive the most profitable customers to a sale, so you can avoid courting less profitable buyers.
- Better understanding of marketing cost-per-sale. Besides optimizing your spend, you can use an attribution model to determine the cost per incremental sale by each channel and by groups of channels.
Marketri understands how important it is to tie marketing investment back to business results. In fact, our focus on marketing optimization is all about driving increasingly better business results. While we don’t build attribution models ourselves, we use partners that specialize in developing highly customized statistical models that help B2B companies understand which channels are driving new business wins and optimize their channel mix and investments for the best ROI.