One of the biggest challenges faced by retailers today is figuring out where to put their marketing dollars. With consumers taking so many avenues toward an eventual purchase, it’s tough to know what messages are truly making an impact. Attribution modeling – although an intimidating idea to tackle for some – can help marketers make sense of their customers’ interaction histories and their ever-growing collection of cross-channel data.

Attribution modeling for the masses

Not so long ago, attribution modeling was a fairly straightforward concept. Because there weren’t many channels to interact with a brand on, determining the most successful marketing efforts didn’t require an advanced degree in statistics or mathematics. With today’s multitude of touch points, however, tracking and analyzing a broad marketing campaign can be difficult.

Luckily, marketers can leverage attribution modeling on a fairly basic level thanks to Google Analytics’ eCommerce tracking tool. By embedding a snippet of code on a website or app, marketers can collect transactional data, such as sales and purchase amounts, to better understand what products are selling and why and what path is most effective for ushering shoppers to the checkout area.

Setting up the tool

To get started, Google suggests that marketers work with their site developer to embed the required code. To set up the code, developers can head here. Next up, marketers will need to enable the eCommerce tracking tool at the view level in Google Analytics, using the following five steps:

  1. Click Admin from the menu bar at the top of any screen in Analytics.
  2. Use the drop down menus to select the Account, Property, and View.
  3. Click View Settings.
  4. In the Ecommerce Settings section, click the toggle so it says ON
  5. Click Save at the bottom of the page.

For websites that employ a third-party shopping cart, a developer will also be required to help set that up, too. But once eCommerce tracking is turned on, the tool will automatically pull in the appropriate data.

To begin attribution modeling, go to Conversions and then Multi-Channel Funnels within Google Analytics. Although there are several models to choose from, more often than not, “last interaction” is a good place to start for those who are delving into attribution modeling for their first go-around.

“The Last Interaction model attributes 100% of the conversion value to the last channel with which the customer interacted before buying or converting,” Google’s editors explained. “This model is extremely common – most likely you’re already using some version of it – so it’s a great baseline for comparison with other models.”

Comparing the results

At this point, marketers will be able to review a data table that lays out the conversions and how much value the model credits to different channels, referral sources and campaigns. From there, it will be time to create a second model for comparison purposes. By using the percentage change column, sorted by conversion values, it will be clear as to which channels or campaigns are the most effective.

“Pay attention to big changes in value: for example, you may find a certain keyword or display advertisement shows low revenue value under the last interaction model, but receives more credit under another model,” the Google editors stated. “Consider taking action. You may wish to change bidding strategies, move ad placements, adjust affiliate payments, or update your landing pages to get the maximum benefit out of strong keywords and channels and to increase the value of low performers.”

Considering Google Analytics holds an 80 percent market share in terms of the traffic analysis tools available today, it makes attribution modeling much more accessible. It helps marketers from any size business overcome the cost barriers associated with expensive modeling technology and highly experienced staff.