This free, no obligation performance analysis will uncover:
    • Opportunities to earn more from your catalog
    • Ways to optimize performance across search, shopping, social, and discovery channels
    • Wasted ad spend and how to reduce it

Changing Attribution Models Wasn’t Easy, But With a 120% Jump in Sales, It Was Worth it for Moosejaw

Considering the rapid rate change in the retail space, it’s amazing that one thing has remained constant over the past decade–attribution. Most retailers continue to use last touch attribution to measure the success of their campaigns, attributing all credit of the sale to the final click before the shopper makes a purchase.

While some may take comfort in last touch’s constancy, it’s quickly becoming an outdated approach for managing online marketing budgets. Not only does it ignore the increasingly complex marketing journeys shoppers take in an omnichannel era, but it forces retailers to optimize low funnel initiatives while overlooking upper and mid-funnel marketing.

Moosejaw, a leading outdoor equipment and apparel retailer, recognized the constraints of last touch when it began to scale its business. “We were knocking it out of the park in terms of last touch with direct response and lower funnel marketing campaigns,” explains Kelli Patterson, Senior Manager of Digital Marketing at Moosejaw. “But in order to scale, we knew that we needed to be able to measure brand awareness and launch campaigns that could drive new customer acquisition.”

That’s why Moosejaw made the switch to multi-touch attribution, adopting a custom model that uses a game theory methodology in order to attribute fractions of a sale to different channels. Kelli spoke with Sidecar in our latest podcast about how Moosejaw made the switch, what challenges her team encountered along the way, and what the results have been so far.

Interviewing Kelli is Mike Farrell, Sidecar’s Senior Director of Market and Customer Intelligence. Mike is an expert in digital marketing, with specializations in e-commerce, Google Shopping, and paid search for enterprise retailers.

Listen to the full podcast or read the top sound bites from the interview below.

Top Sound Bites

(edited for clarity and brevity)

Mike Farrell: How did Moosejaw choose which attribution model was the right fit for its business?

Kelli Patterson: We looked at three different vendors. We looked at Abakus that was then acquired by SAP, so they’re now going by SAP Hybris. We looked at C3 Metrics, and we looked at Convertro, which I believe is now defunct. We ended up going with SAP Hybris because they had great integration support and we really believed in their methodology.

When we looked at some of the other methodologies, there’s some different analysis types like survival analysis or time decay, that we didn’t think really fit with the e-commerce shopping behavior. Whereas, we thought that the game theory model really matched along with how we see our users interacting with our different marketing channels, and how they interact with our website.

I think it depends on what your KPIs are, and what you consider a conversion. There might be some different kinds of websites or retailers that have different user behavior, and so they want to measure those users a little bit differently. But the game theory worked for us.

MF: What were the key goals you wanted to achieve by rethinking your attribution?

KP: Our key goal over the last couple of years has been to scale. When we’re scaling, we want to keep efficiency in touch. We were knocking it out of the park in terms of last touch with direct response and lower funnel marketing campaigns. But in order to scale, we knew that we needed to be able to measure brand awareness and launch campaigns that could drive new customer acquisition. So in order to scale, we had to rethink about how we measure success. We decided to go with the multi-touch attribution.

And the ultimate goal is to be able to use a more complete data set to allocate marketing dollars to balance growth with efficiency. We want to be able to allocate marketing dollars further up the funnel and drive users to our site in more of the awareness and consideration stages. That was our main goal.

MF: What have been some of the early results since making the switch to multi-touch attribution?

KP: We have been using the attribution model to optimize our text ads, Google Shopping ads, and Bing shopping ads for quite some time now. For text ads, it’s been about a year and a half, and then we made the switch on the PLA side in the summer of 2018. What we’ve seen is great results in both efficiency and overall growth. The model is giving fractions of sales to different keywords and sort of bubbling up those keywords when we look at revenue. Then we can take into account these new terms that we probably would have overlooked or undervalued in our old model when we set our bids.

Overall, we’ve had strong results in text ads, with sales up over 120% year over year, and a 40% improvement in ROAS. For shopping ads in Q4, our sales and orders we’re up 58% year over year at the same ROAS. That’s despite some really serious competition in Q4. We’re calling that a huge win.

MF: What advice would you give retailers who are looking to make a change from last touch?

KP: I think the best advice is that you have to crawl, walk, and run, but you also kind of have to jump right in. So what I mean by that is, you have to go feet first into your decision to move forward with a new model, find all of the different vendors that you can, talk to people there, get demos, and really try to understand what the data says and how the attribution model works.

I think the crawl phase is really important. It’s believing the model, it’s getting all of your data and your taxonomy set up correctly. It’s pulling the data, talking to your team, talking about what it means versus last click. It’s really understanding what the data says, what it means, what it means down to the keyword level, and what it means at the macro level.

And then I think what really helps is to have like an evangelist. So I’m kind of the attribution evangelist at Moosejaw, and I am reminding people, “That’s cool that that’s what we see in last click, but what does the new attribution model tell us?” And I think it’s important to look at those two data sets together and understand how they translate. If you don’t understand the difference between your last click and multi-touch attribution, I think it’s harder to move on to the multi-touch model completely.

MF: What would you say to a person that might be in your position that needs to convince a C-level boss that this is the right move for a company?

KP: I think the key that we’ve come down to is that this was absolutely necessary for being able to scale and onboard new marketing channels. Moosejaw had never really done display advertising. We have several programmatic display campaigns running now that we couldn’t measure without our multi-touch attribution platform.

From a digital marketing standpoint, it’s really easy to improve efficiency when you’re measuring on last touch. You can cut and optimize and drive efficiency. And if efficiency is your goal, by all means stick with last touch. It is not easy to scale and maintain efficiency when you’re just measuring on last touch. But if you want to be a player that has more influence in that mid and upper funnel, drive brand awareness, and be a part of the consideration stage, then multi-touch is absolutely the way to go.

Metricool tag