How Data Management Helps Retailers Monitor Omnichannel Behavior

Who’s ready for some holiday cheer after a year marked by fluctuating tariffs and economic headwinds? Consumers are cautiously optimistic, which could define an unpredictable sales season. With a large amount of holiday retail planning already underway, and some retailers that stocked up early to get ahead of tariff hikes, it is time to closely monitor omnichannel behavior and stay responsive as this year’s strategies unfold.

Retail brands can leverage insights from the holiday season and carry them into their 2026 planning strategies, while real-time analytics can help make the most of every shopping day along the way.

Real-time data is a gift

Until recently, category teams relied primarily on syndicated market reports for seasonal performance indicators, which were often made available weeks after the fact. An increasing number of category teams are partnering with their retailers to utilize point-of-sale (POS) data reports for actual sales and inventory levels. However, the process remains very manual for many companies and is not optimized to rapidly leverage the robust data needed for decision-making during this critical business period.

With technological advancements, real-time data can now be automated and integrated into sales, supply chain and inventory management software to provide teams across the organization with a continuous flow of intelligence for decision-making. Comprehensive reporting offers brands and retailers unprecedented visibility into performance, enabling them to respond faster and more effectively than ever before.

Access to real-time data enables the separation and measurement of the impact of Black Friday, Cyber Monday, regional promotions, and store-level surges, rather than just the weeks in aggregate. Every day between now and the New Year is an opportunity to read live shopper signals and act accordingly.

Measure, respond, refine in the New Year

As teams navigate the holiday season, their focus spans three critical time frames – preparation, in-season management, and future planning – each requiring distinct data-driven approaches.

Supply preparation: Online, pick-up and delivery orders are expected to grow year over year. To meet this demand, brands may need additional facings for high-velocity seasonal items, using sales data to secure more space. Having those extra facings ensures that sufficient supply is on hand to fulfill all orders beyond in-store traffic alone.

In-season adjustments: Real-time data allows retail teams to quickly assess the success of holiday strategies. For instance, after analyzing how items performed during Thanksgiving, adjustments can be made for Christmas. While major modular changes are unlikely during the season, data can still justify additional endcaps or display space for brands that are dramatically outperforming the category, especially if online, pick-up and delivery performance warrants it.

Post-holiday planning: The holiday rush coincides with another critical time for many merchandisers: line-review season. With real-time data, managers can leverage Q4 insights to inform category reviews for the following year. While traditional syndicated market reports will still be valuable, more timely resources like category scorecards and data feeds compliment those insights with more immediate, comprehensive views of performance and competitive benchmarks. Analyses can help retailers and brands understand whom they are gaining or losing share to and uncover new trends.

When it is time to build planograms (POGs), data will help adjust facings and inform expansions, ensuring brands are well-positioned for upcoming resets, along with next year’s festive season. Modern planogram automation lets teams spend less time creating and validating thousands of sets and more time perfecting the retail strategy.

Ring in the AI agents

No holiday playbook is complete without this year’s standout trend – retail AI. For teams ready to get started with AI-driven insights, AI can be activated on top of clean retail data in cloud environments to surface valuable insights around on-shelf availability, store clustering, assortment optimization, and more. Throughout retail’s busy season, it is essential to stay informed about issues like phantom inventory and zero-sales instances, as well as begin to intelligently group store locations by demographics and sales trend behavior.

Agentic AI takes it a step further, turning deep learning into autonomous action on clean, structured retail data. AI can deliver custom business performance reports to different teams, watch and signal supply chain updates in real time, create and optimize in-store promotion plans, and more. Gartner predicts that by 2027, 50% of business decisions will be augmented or automated by AI agents.

More than last year, the 2025 holiday season presents AI-driven opportunities that brands can take action on today, and the learnings will apply seamlessly to what is ahead. With the proper data foundation in place for accuracy and reliability, these advances in technology can layer in as value-adds to an already strong plan for real-time seasonal analysis and action.