Creating customer insight from Retail DnA

In Consumer products and retail

Go beyond traditional demographics to create an unbiased way to understand customers based on what they do, not who they are. Retail DnA is designed to generate real customer insight from data that retailers can convert into value-generating actions.

Related topics Consumer products and retail Customer

The team

Robert Holston

Robert Holston

EY US-West Consumer Market Segment Leader

Kristina Rogers

Kristina Rogers

EY Global Consumer Leader

What EY can do for you

By combining a machine’s speed, and its ability to scale and learn, with human power, Retail DnA can help brands to close the customer insights gap.

Retail DnA combines information from various data sources to understand the digital footprint, transactional data, physical interaction and verbal dialogue of a customer.

This allows Retail DnA to generate insights and develop natural clusters based on the actual activity of customers, rather than on their profiles.

An enterprise-wide view of buyers’ purchasing patterns and shopping behavior can allow brands to create the right offer and communicate it at the right time, through the right channel.

Retail DnA continuously works to improve prediction, helping brands maintain relevance and deliver value to their customers.

Using real customer behavioral data to form natural clusters, Retail DnA goes beyond traditional demographics to create an unbiased way to understand customers based on what they do, not who they are. By combining a machine’s ability to scale, speed and learn with human-power, Retail DnA can help brands to close the customer insights gap by:

  • Understanding shopper behavior and preferences
  • Valuing customer individuality
  • Accurately predicting next likely customer action
  • Helping the marketing team to develop and deliver the right personalized offers at the right time through the right channel

  • The power of the single view of customer

    Retail DnA combines information from various data sources to understand the digital footprint, transactional data, physical interaction and verbal dialog of a customer. This allows Retail DnA to generate insights and develop natural clusters based on actual customer activity, not their profile.

    An enterprise-wide view of buyers’ purchasing patterns and shopping behavior allows brands to plan for the right offer, communicate it at the right time, and sent through the right channel.

  • Increase engagement with tailored communication

    With a single view of their customers, brands can understand their buyers on an intimate level and build Retail DnA into their plans to engage, and re-engage with customers.

    With the ability to accurately predict next customer action, Retail DnA gives brands the competitive advantage to model and design tailored campaigns that can help deliver accurate personalized offer recommendations.

  • Improve loyalty by understanding brand affinity

    To get close to your customers and stay relevant (a challenge many retailers are struggling with), you need to understand their motivations. Your shoppers’ needs and behaviors will change over time, and you need to keep abreast of those changes to ensure you don’t become a forgotten brand.

    Retail DnA continuously works to improve prediction so brands can maintain relevance and deliver value to their customers.

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