Part of the Alliance Data (NYSE: ADS) family of businesses

Making the most of your SKU-level data

Unlock greater buyer potential and create more meaningful marketing efforts 

When brands can personalize their marketing efforts, they’re better positioned to reach customers in more meaningful, relevant, and timely ways. And if they can cross the digital threshold and bring them into the store? Even better. By taking a preference-driven approach to marketing (encouraging customers to buy more of what they already want to buy), brands are more likely to increase engagement, facilitate stronger customer relationships, and provide greater motivation for more cross-category purchases.

Leveraging your SKU-level data is a great way to make this happen. It allows you to know what purchases have been made — whether it’s with a credit card, through a multi-tender program, etc. — and, in most instances, who made them. Depending on what information you choose to collect, you can know more about each customer, from her preferred size and style to the amount of her previous purchases. And when you’ve got all that transactional data on her, you’ve got actionable marketing gold; you can determine which offers and products she’ll find most relevant and compelling. Which means this priceless SKU-level data, all of which you already own, has untold marketing potential.

Case in point: one of Alliance Data’s brand partners sells jeans, among other things. Knowing that their jeans-buying customers spend three times more than other customers, our partner wondered what would happen if they could convert more other customers into jeans-buying customers. Would they see an increase in overall store sales? Because tapping into this data takes time and resources to compile and analyze it, they asked Alliance Data to explore the idea with them.  

To supplement the data we’ve already got on purchases made with our private label card, our partners provided us with additional SKU-level data for transactions not made with our card. With that, our Predictive Analytics team was able, through statistical models and product affinity analysis, to identify two customer segments. The first group was already buying jeans; the second was most likely to purchase jeans if given the right incentive. They assigned relevant offers for each group, and the results were telling. Within a three-month period, the number of people in the jeans-buyer group grew by nearly 10%, and overall sales increased by 8%.

An added bonus? By breaking down their customer base, our partner was able to better control marketing expenses — targeting the right potential customers with the most relevant offers meant not wasting money on sending offers to people who wouldn’t bite.

Customers want a special connection to the brands they love. And they expect brands to engage them on a personal level, recognizing them for their loyalty. Consider all that data you’ve got at your fingertips. All that available CRM potential. Rather than simply reassigning SKU numbers and letting that great data lie dormant, explore ways you can put this invaluable information to work for your brand.  




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