Advanced Analytics: How Retailers Can Make the Most of Their Data
On average, U.S. households have 11 connected devices and consumers consistently engage with multiple touchpoints before making a purchase. It’s no surprise then that many retailers are struggling to organize and make use of the increasingly high volume of available data. Truly understanding the many types of both first- and third-party data is essential for establishing a solid business strategy and producing return on investment, and therefore, a retailer’s success.
Evaluate Your Systems
Many brands struggle to make use of their data because they're burdened by legacy systems and siloed databases. Without the right system or proper integration, it's hard to identify gaps and capture the insights required for fundamental business decisions, let alone evaluate new technology. As a result, retailers should begin their analytics journey by taking a closer look at their existing systems and asking questions such as: What data am I missing? How are my systems capturing data? Can I connect data from disparate systems? How am I establishing a single customer journey?
Create a Foundation for Success
Once you’ve evaluated your existing systems, you can take steps to integrate or eliminate them to create a more useful, evolved system. It’s important to develop a strong foundation, as it will allow you to transform and activate data, thereby extracting useful insights and uncovering stories across channels. Once the foundation is in place, you can take steps to develop a testing strategy to understand how various channels work together and whether specific marketing campaigns are effective. Lastly, brands can use artificial intelligence (AI) and/or machine learning for predictive analytics to create even stronger future campaigns.
A common method for creating a testing strategy in your data foundation is to evolve the attribution methodology you're using to gauge the success of paid media. We often see retailers relying on traditional last-click attribution for all channels, including upper-funnel campaigns. This method creates a fundamental misalignment between push and pull channels, resulting in ineffective ad spend and missed revenue opportunities. For example, we've seen affiliate spend overstated by 30 percent based on analyzing a customer path to purchase and testing various attribution models. Planning media based on results from a U-shaped multitouch attribution model proved to offer the best ROI instead.
Improve Your ROI
Better analytics present a simple, wonderful benefit: better ROI. But this is easier said than done. By collecting data, properly organizing it, and using it to truly evaluate campaigns, retailers are able to improve the return of individual campaigns, as well as their overall marketing approach.
An example of this is as simple as changing your targeting or modifiers in a campaign for an immediate improvement in return on ad spend. For instance, on one campaign, we used a geo-based split lift test to evaluate the hypothesis that device bid modifiers were restricting the performance of paid search campaigns. We removed mobile bid modifiers and achieved almost a 20 percent increase in top-line revenue.
Another example is using behavior data to understand and optimize to the entire customer journey. Many retailers may know that “Jane Doe” clicked on Facebook retargeting ad C on March 5, 2020, and then spent $50. However, Jane’s final purchase is informed by a full story outside of this single action. She has a history of engaging with the retailer across channels over time before making a purchase. To improve business overall, retailers must uncover the full shopper journey story, using a strategic approach to analytics.
So, what if the retailer also knew that Jane’s behaviors and interests were shared with 60 percent of its customer base? Or that half of its customers, including Jane, initially discovered the brand's top-selling T-shirts after a popular YouTube influencer gave a positive review. Or that the majority of customers watched multiple YouTube videos, interacted with the retailer’s Twitter page, and visited two specific web pages three times before receiving Facebook remarketing ad C and making a purchase.
The detailed information is much more illustrative of Jane’s experience and those of others like her. By analyzing trends, including all audiences and specific touchpoints, marketers are more empowered to make decisions across channels.
Make the Most of Your Data
When detailed data is available in real time to retailers, the possibilities to connect with Jane and her peers are endless. To ensure you maintain a competitive advantage, you must develop a strategy for evaluating your systems, create a foundation for success, and improve your ROI. The retailers that are able to identify and target similar shoppers will increase loyalty and develop high-value customers.
Laura Russell is the director of strategy at Adlucent, a performance advertising and analytics agency for large brands and retailers, where she works closely with clients to tackle their business and marketing challenges, advising on how to best leverage data, audiences and media tactics to drive measurable results.
Laura Russell is the Director of Strategy at Adlucent, a performance advertising and analytics agency for large brands and retailers, where she works closely with clients to tackle their business and marketing challenges, advising on how to best leverage data, audiences, and media tactics to drive measurable results. She has over a decade of experience in ad tech, advertising solution development and digital marketing strategy across various industries. She is passionate about creative problem-solving and excels at proactive planning, guiding Adlucent through innovative new solutions and inspiring her team to be “better every day.”