How retailers can better utilize data to transform customer intelligence

What can a customer intelligence platform deliver?

A CIP provides a 360-degree view of customers by aggregating an organization’s sales and transaction data and combining it with second-party data (from affiliates or other retailers) and third-party data (such as socioeconomic trends, life-stage attributes and even weather patterns). This integration extends to insights from in-store cameras identifying shopper patterns and social media analytics uncovering viral trends or persistent complaints.

With these insights, retailers can segment their audiences, track shopping habits, understand digital and social engagement, and build new online networks. This enables more strategic and impactful marketing campaigns, as well as actionable recommendations for refining merchandise mixes, visual assortments, store floor layouts and product presentations.

To deliver these outcomes, a CIP integrates data from multiple categories, each adding valuable context to decision-making when combined with historical data. The more comprehensive the data set, the clearer the insights into customer behavior and preferences:

Delivering value across the value chain

It’s valuable to think in terms of use cases that can be enhanced or improved to unlock value from a customer intelligence platform. The following are key areas where decision-making and execution can be improved, delivering value across the value chain.

Build insights incrementally in five foundational areas

Investing in technology for a CIP does not necessarily mean building a full-fledged, freestanding platform from scratch. Instead, start small, test and prove value in five foundational areas:

1. Data collection and harmonization

A lack of data is rarely an obstacle for retailers. Instead, data is often everywhere they look, structured differently and fractured across incompatible systems. First, retailers should consider developing a guide to prioritize the data they need most — including customer relationship management (CRM), transactions and digital interactions, whether inside their systems or from second or third parties — and cut out the peripheral noise. That data must be standardized and consistent, with controls that validate data integrity and quality. For instance, the third-party market is unfortunately full of useless information that can deliver more confusion than actual insights.

2. Customer ID resolution

As retailers gather data from multiple touch points, including online transactions, in-store purchases, social media interactions and loyalty programs, the challenge lies in accurately linking disparate pieces of information to a single identity to create a unified view of each customer. Customer ID resolution is typically achieved through advanced data-matching techniques that leverage both deterministic and probabilistic methods. Deterministic matching involves linking data points using unique identifiers, such as email addresses or loyalty card numbers, that explicitly confirm customer identity. Probabilistic matching, on the other hand, uses statistical algorithms to infer matches based on a variety of data attributes, such as phone numbers, physical addresses or behavioral patterns.

3. Privacy and compliance

Addressing the challenge of privacy regulations, such as the General Data Protection Regulation (GDPR) in the European Union or the California Consumer Privacy Act (CCPA) in the United States, is paramount. Retailers can deploy clear and concise consent forms that outline the specific use cases for the data, making sure that opting in or out is a straightforward process. A privacy-by-design approach, where data protection is integrated into the development phase of new products and services, can also help build trust and drive compliance.

4. Continuous monitoring

Customer profiles must be monitored as new data becomes available so that they remain accurate and up to date over time. For instance, retailers should encourage feedback through surveys, reviews and direct communication channels, using this information to refine customer profiles. Retailers should be aware of noteworthy events in customers’ lives, such as moving to a new location, getting married or having a child. These events can be identified through direct customer updates or inferred from purchasing patterns and should prompt profile updates. Regular data cleansing is necessary to remove outdated, incorrect or duplicate information. This can involve processes such as verifying contact details, standardizing data formats and merging duplicate records.

5. Integration and analytics

Data alone will not bring the answer — it must be transformed into insights with tailored analytics for business value. At this stage, companies can think bigger to capitalize on the true ROI of a CIP by integrating resolved profiles with marketing automation and analytics tools to personalize activations, improve segmentation and drive actionable business decisions. AI and analytics are crucial for sensing demand and managing inventory, and they can predict out-of-stock situations and adjust forecasts based on real-time data, to name just a few use cases.