Vai Anand explores the value of first-party data

I lead the Data Science team at Dollar General, and I absolutely love what I do. The wide variety of work opportunities we encounter every day is exciting. The amount of rich data we have at our fingertips has me waking up every day (and sometimes in the middle of the night) with my mind buzzing with fresh insights and new ways of enabling our organization to deliver value for our customers. Our workstreams span data mining, machine learning, statistics, predictive analysis, modeling, and more. One of the most interesting aspects of this work is my team’s involvement with Dollar General’s Media Network, DGMN.

Before I get into how our Decision Science and Analytics team has helped DGMN tackle everything from untraceable cash transactions to how best to quantify measurable performance outcomes, it’s important to understand the uniqueness of Dollar General, our customers, and who we serve. Our ongoing data studies help our team find ways of ensuring that the Dollar General mission – serving the underserved – is always at the forefront of our analysis. The ideas we develop from analyzing our data can help our customers who are looking to stretch their dollars.

Here are some data points regarding our key role in the lives of our unique rural customers:

• We serve as the “small box” or general store format retailer for smaller communities. Eighty percent of our stores are in markets with populations of less than 20,000. Where other retailers can’t or won’t go, we provide access and convenience for our customers to fulfill most of their grocery and general merchandise needs.
• We have over 90 million active and trackable Dollar General profiles, and we can curate custom audiences across 1,400 attributes. This gives brands the ability to connect with 90% of Dollar General customer households, which are oftentimes difficult for others to reach and measure.
• We are a regular part of our customers’ shopping routines. Over 50% of our customers shop at a Dollar General store 35 times a year.
• Our customers are highly engaged. Whether they are actively clipping coupons, searching for deals in our weekly circular, or finding inspiration for the holidays, our digitally engaged shoppers spend twice as much as those who are less engaged.

With the looming deprecation of third-party cookies, the importance, value, and usage of first-party data has grown significantly in the last few years, especially in the areas of marketing and merchandising. We expect to gain additional benefits from this data in the future.

In the marketing world, first party (1P) data can help to communicate and personalize our message to customers. Our Data Science team uses predictive analytics tools – such as machine learning algorithms – to predict customer shopping behavior. Using 1P data, we can predict our customers’ preferences and then personalize the right offer based on their need, as well as target them before they make the buying decision. And when it comes to understanding our customers and translating the data points, our Decision Science and Analytics team collaborates daily with DGMN. We also work closely with our Media Insights and Ad Sales team by providing them with deep analytical views on measurement and reporting.

We know that brands and agencies are craving a true omnichannel view, inclusive of offline attribution. While online attribution makes it easier to tie media exposure to online purchases, many retailers and technology solutions are navigating how to compare media exposure with offline purchases. At Dollar General, we delivered the offline attribution first. Why? Because with approximately 20,000 locations across 48 states and 75% of Americans within five miles of one of our stores, convenience wins.

Some of the areas where the Data Science and Analytics team is working to provide accurate returns on CPG investment include:

• Increasing customer match finding signals in offline transactions, which can then be matched to the customer and thus measure attribute sales;
• Navigating the complex world of retail media: mapping the maximum amount of online exposure back to the individual customer level at our brick-and-mortar locations and providing closed-loop reporting;
• Creating randomized tests and a control audience to ensure we account for any unnatural variance and remove any bias; and
• Providing statistical significance of incrementality calculation so that our partners can understand each factor that contributes to the actual incrementality.

When it comes to understanding our customers and translating the data points, our Decision Science and Analytics team collaborates cross-functionally with multiple teams. As I read other articles about the “third wave” or “what’s next with RMNs,” I’m frequently reminded of the uniqueness of Dollar General, our customers, and our media network!