Become an Omnichannel Retail Pro: How to Rock Multi-Channel Attribution

Omnichannel retail is all the rage right now, and if you're looking to get started (which we highly recommend - here's a guide to help you), there's one tactic you'll need to learn: multi-channel attribution.

When you have dozens of customer touchpoints spanning the offline (brick-and-mortar stores, pop-ups, or direct mail) and the online (digital marketing, social media, mobile apps, and Shopify site), it can be challenging to keep track of which channels are pulling their weight.

Without this insight, determining where to invest your budget becomes less of a strategic decision and more of a guessing game. That's where multi-channel attribution comes in.

Long story short, it's the monitoring and measuring of each marketing effort's impact, plus understanding how they work together. Don't worry: It's not as daunting as it sounds, especially when you have a partner like AdRoll that automatically provides this data in a unified dashboard.

The key to getting started with multi-channel attribution is identifying your key performance indicators (KPIs) and deciding what model to use:

• Linear. Every touchpoint gets equal credit.

• Last-Click. The last touchpoint receives all the credit.

• First-Click. The first touchpoint receives all the credit.

• U-Shaped (or Position-Based.) The majority of the credit goes to the first and final touchpoints, while the rest is shared by the middle.

• Time Decay. The last touchpoints are awarded more credit compared to the earlier ones.

• W-Shaped. The first, middle, and final touchpoints share the most credit.

• Data-Driven (or Algorithmic.) Credit is assigned based on your unique customer journey data. It's a customized model, if you will!

For more in-depth information on choosing the right attribution model, check out this blog post.

Once you've decided which model makes the most sense for your brand, check out AdRoll's Cross-Channel Performance Dashboard, a tool you can use to start collecting, visualizing, and analyzing the data. Good luck!