The Digital Potential of Data Intelligence in Retail

Analyst Viewpoint

The digital age of data has dramatically transformed organizations by providing the insights that are necessary to confidently make decisions and take action. When applied, this is commonly referred to as Data Intelligence, and it comprises all types of data, from customers, purchases and consumers and from all sources including physical and digital activity aligned to a specific identity, which can then be linked to specific interactions. This digital resource can be used across marketing, merchandising and retail operations, as well as across other departments, to optimize the retailer’s plans and execution.

The extreme pressure on retailers to generate the necessary outcomes has created new opportunities for performance growth.

The extreme pressure on retailers to generate the necessary outcomes—whether from digital or physical advertising and merchandising investments—has created new opportunities for performance growth. For retail leaders, the value of data intelligence is in its ability to more directly align data and insights to processes like choosing store locations, optimizing in-person experiences within those locations to increase engagement, or addressing the business priorities of curating audiences and targeting interactions, all leading to optimal consumer experiences and growth of revenue.

The ability to specifically identify audiences is no longer a dream, but a practical reality for every organization. The power lies in knowing the geography and the demographics, which allows prioritized targeting of consumers, regardless of whether they are at home, in transit or at a location. Being able to make selections visually, through an application-specific approach that includes mapping, is straightforward. Access and connection to a range of datasets has now become so simple that the transition to digital-focused data platforms can establish new opportunities.

The application of data science using artificial intelligence and machine learning (AI/ML) lays the foundation for building precision into your datasets. Intelligent virtual agents have been empowered to help even further, simplifying the activities with data intelligence. Advanced identity techniques and analytics are available as well, processes that are beyond the simple approach of a customer data platform. These use sophisticated methods to correlate to place-based datasets, making visible the locations of interactions and how people transition from and within those locations. Integrating additional AI/ML to further enrich the dataset with factors such as details of visits, dwelling times at locations and traffic, with the resulting insights into brands, locations and spend information, will further refine the retail organizational guidance that is critical for market planning and execution decisions.

Those retailers that glean the best insights from data can execute more effectively in the market and can better achieve desired outcomes within the allocated timeframes and budget. The use of specifically designed digital technology can provide for correlation across the various consumer audience and location datasets and can actually help ensure the desired performance. It is therefore possible to optimize market spend, making that information available to your market and data analysts, the people who work to guide decisions and support retail operations.

Providing personalized consumer experiences and interactions can reflect well on your retail brand reputation and can directly contribute to revenue growth. Existing marketing technologies are most often ineffective to intelligently engage buyers in personalized digital experiences. Until recently, data intelligence has been largely isolated to optimizing the digital experiences online. But now, data about consumers and their physical movement in the real world allows retail brands to optimize and improve all relevant digital and physical experiences.

Business leadership and department heads should assess their current technological approach to data intelligence. Through 2024, after concerted investment into digital transformation, one-half of retail organizations will require a new digital business and technology agenda for organizational resilience. It is insufficient to have data simply correlated with an identity, because that alone will not provide the precision targeting or personalization that is required to reach the expected outcomes. Applying data science with AI/ML, however, will harvest the desired audiences and help a retailer achieve maximum business performance.

When examining new technology, make sure to also prioritize the level of manageability and usability of the vendor’s approach, confirming that it can be used by your retail organization internally and not just by external consultants. Directly align your investments using a data-driven approach that is designed for uncovering those insights, and you can convert data and knowledge into the actions and decisions that can enable data intelligence in retail.