POWERED BY AI

Data-Driven Retail: Extracting Value from Customer Data

Oct 30 2018

As industries face the increasing challenge of multiple options—digital and traditional—retail is perhaps one of the most affected. In response, retailers are increasingly turning to data and analytics to make better business decisions and guide marketing initiatives. Yet, many retailers are uncertain how to use the more customer-specific data they can now collect.

The primary key is to have a plan for what you want to use the data for and then make sure you get the data right. To gain confidence in the data you’ve collected. To know how to leverage it to your best advantage. And then, of course, to use it.

Retail customer data is priceless—when it’s right

It’s no secret that creating more personalized customer experiences is a top priority for nearly all industries, especially retailers. To get a better sense of their audience, retailers must understand how to bring together external data sources, such as demographics, location and market data, with internally held customer data, such as transaction histories and loyalty status. Once these sources have been identified—and the data has been checked for accuracy—retailers can achieve a more a detailed understanding of their customers.

Retailers often struggle with ensuring their data quality is high. “It’s not that retailers don’t have the data,” says Andy Berry, Vice President, EMEA & Global Retail for Pitney Bowes software. “It’s that in many cases they haven’t gone through the exercise of cleansing that data and understanding what models and sales plays to execute with that information.”

Once the data is cleansed and the retailer is confident in it, the data can be used to help improve revenue and operational performance. How?

  • Establish a single customer view, bringing everything that is known about a customer into one manageable place.
  • Increase average transaction value, enhanced by analytics engines identifying trends and upsell opportunities and leveraging demographic and location data.
  • Strategize and plan based on location data, helping businesses improve margins because good data enables them to, for example, optimize the mix of physical and online locations or identify new store locations and plan franchise territories.
  • Streamline requirements, such as frequently changing shipping and tax costs.

When you’ve got the right data, use it

Once retailers are confident they have the right data, they must decide how to best leverage it. “If you don’t act on the data and actually use it to drive additional revenue and margin, you’re not capitalizing on the opportunity,” says Berry. Customer data and location analytics platforms can help, enabling retailers to make sense of the information they have and then act appropriately.

Retailers now prefer a more unified strategy, using their physical and digital platforms in complementary ways. More retailers are optimizing channels, often using the web to show breadth of range and product details, while preferring in-store to encourage customers to experience the product and engage with store representatives.

Data is key to facilitating these strategies across channels so that a customer’s experience is seamless, regardless of how they come into contact with a brand. “The cornerstone to all that is having the data to understand the consumer best,” says Berry. “Whoever pulls that together will need to get the blend of online and offline right.”How to do it?

  • Put your data to work. Data can’t extract value if it’s not used to generate new insights and drive decisions.
  • Understand your data. It is important to understand the types of questions data can answer and the suitability of the data being queried for the specific purpose.
  • Seek expert advice. Outside experts can help outline how to make the best use of existing data and identify where it can be improved, enriched and contextualized to ensure it not only delivers but exceeds expectations.
Author: Pitney Bowes