5 essentials for your retail data strategy in 2025

By Mikhail Templeton

Holiday spending was expected to exceed record levels in 2024, with consumers budgeting a record $902 for gifts and seasonal items. This was $25 more than 2023 and $16 higher than the previous record set in 2019.¹ The retailers most likely to have won outsized portions of the historical spend will have been those who moved customer service and support beyond historical norms.

It all starts with data.

Today’s consumers expect omnichannel experiences and rapid delivery within three days or less. With so many retailers at their fingertips, they also seek out those that share their values of equality and sustainability.²

The retailers that harness the power of data strategies to meet these expectations will win mindshare, wallet share and loyalty for the foreseeable future. Here are inventory management, pricing and personalization use cases I expect to see play out in the year ahead, as well as five essentials to enable them.

Retail data strategies to reveal why, when and how purchases are made

Data analytics offers more than just numbers—it provides a window into the psyche of consumers. Retailers can gauge not just what consumers are buying but also why, when and how they’re making those purchases.

One way retailers can capture some of that raw data is by enabling shoppers to seamlessly transition from their phone’s cellular data to a store’s Wi-Fi without having to sign on.

Once on Wi-Fi, the customer’s information becomes first-party data, which allows the retailer—with proper notification and consent from customers—to capture rich data sets such as dwell time and product interests. This data can be used to enrich the retailer’s app experience, empowering the app to become an actual tool and not just an information hub.

Retail data strategies for personalized shopping experiences

Shoppers crave experiences. By analyzing data, retailers can identify individual preferences and trends and even predict what a consumer might want in the future to create a unique and memorable customer journey.

Retailers can use customer purchase history and browsing data to personalize their website’s homepage. When each customer logs into the retailer’s website, the customer will see a selection of clothing items in their preferred styles, sizes and colors.

Additionally, the retailer can send personalized email promotions showcasing new arrivals or sales on items similar to what the customer has previously ordered. This targeted approach not only enhances the shopping experience by making it more relevant and efficient but also increases the likelihood of the customer making a purchase.

Retail data strategies for inventory management

An empty shelf may not only let down customers and result in a missed sales opportunity for the retailer but also indicate ineffective use of data.

Data analytics allows retailers to anticipate demand based on historical data, seasonality and market trends. Retailers can use this foresight to their advantage. By utilizing data from past sales, customer engagement and social media, retailers can predict which items will be most popular leading up to the holiday season.

Additionally, AI solutions can automate reordering processes to maintain optimal stock levels, track real-time stock levels and accurately forecast demand by analyzing external factors like seasonality and economic conditions.

The knowledge gained from data can help prioritize items before peak timing. For example, a retailer selling holiday decorations will be able to ensure that the right products are available in the right quantities, maximizing operation efficiencies and sales while minimizing costs.

Retail data strategies for dynamic pricing

Data-driven retail introduces the concept of dynamic pricing, where prices can be adjusted in real time based on market demand, competitor prices and other external variables.

When a customer uses their rewards card at the gas pump, the retailer can use customer rewards data to customize the video ads playing while they pump. The ads can display offers based on customer preferences. For example, if the data shows that the customer often buys coffee when they stop for gas, the video ad can display a BOGO coffee deal.

Five essentials for any retail data strategy

1. Agree on your tech stack

Retailers will need to build technology stacks that are appropriate to support their data strategies. This involves selecting the hardware and software solutions that can efficiently collect, process, analyze and store data. The tech stack should include tools for data analytics, customer relationship management, inventory management and point-of-sale systems.

It’s important that these tools are compatible with existing systems to ensure a smooth flow of data across different business functions. Line-of-business leaders and IT cannot have these conversations in siloes. Both the business and IT leaders need to align on a roadmap that will rationalize aspirations with current and desired tech capabilities.

2. Ensure data security and compliance

One of the easiest ways to lose customer loyalty is to lose customer trust. That’s why it is so important to implement robust data privacy and security measures to protect consumer information from breaches and cyberattacks. These measures include encryption, secure data storage and regular security audits.

As online shopping continues to grow, so do risks associated with fraud and data breaches. AI-driven security systems can identify vulnerabilities in your digital infrastructure, and detect unusual patterns and potential threats in real-time to protect your business and your customers.

Additionally, compliance with data protection regulations such as GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act) is essential to maintain customer trust and avoid legal penalties.

Beyond compliance, retailers should also consider the implications of data usage. This includes being transparent with customers about how their data is being used and giving them control over their personal information.

3. Implement data quality management

For data to be helpful, it needs to be accurate. Retailers need to establish protocols for data entry, validation and regular cleaning to avoid issues like duplicate records, outdated information and inaccuracies that can lead to poor decision-making.

4. Integrate customer data for a 360-degree view

Integrate customer data from multiple touchpoints, for example, online, in store, mobile and social media. Using data from multiple sources is key to gaining a 360-degree view of the customer. This comprehensive perspective allows for more effective personalization, better customer service and improved targeting in marketing campaigns.

AI-powered tools can add value by analyzing the customer data to deliver tailored product recommendations, targeted marketing campaigns and individualized shopping experiences.

Leveraging machine learning algorithms to predict customer preferences can enhance customer satisfaction and boost sales and loyalty.

5. Prepare for AI everywhere

In 2025, a robust AI strategy is no longer optional for retailers—it’s essential.

Retailers can use generative AI to strengthen security, improve inventory management and personalize customer experience. We’re even seeing retailers use generative AI to customize product descriptions by using customer data such as age range to tailor descriptions for specific customers.

Retailers need to prepare for the integration of AI technologies by ensuring their data infrastructure can support these advanced applications. This preparation includes training staff in data science and analytics, investing in AI-capable tools and establishing processes for data-driven decision-making.

We are still learning all the ways generative AI will transform the industry. But before retailers can even begin to harness the power of AI, corporate lines of business and IT must come together to rationalize envisioned use cases with the technology foundations they’ll need for them to succeed.

Mikhail Templeton is Vice President and Senior Partner at Kyndryl.

¹  Holiday spending levels reach new record, The National Retail Federation, October 2024
²  The five zeros reshaping stores, McKinsey & Company, March 2022