The retail industry is a competitive business, and not just since the emergence and growth of e-commerce.Therefore, understanding your customer’s behavior and preferences contributes to your business’s success. While it can be challenging, the advent of smart retail technologies has aided retailers in gaining valuable insights through in-store tracking and analytics.

The relevant sections in this retail technology whitepaper:

Detailed digital simulations could help to model supply chains and offset risks, easing supply chain challenges. But there are high barriers to widespread adoption.Supply chains are the central nervous system of the global economy, facilitating the movement of billions of dollars in trade every day. But as the past few years have shown, disruptions are hard to predict. 

As companies look for ways to offset these risks, attention has turned to so-called digital twins. These detailed simulations of real-world objects, systems or processes are built with real-time data and provide snapshots that can help firms to monitor threats, test different scenarios and improve decision-making. 

One of the fastest growing ad channels in the US, retail media is predicted to reach $130B in ad spend by 2028, and is revolutionizing the advertising landscape. Our exclusive Retail Media Playbook offers a blueprint for brands and retailers on how to leverage retail media to gain a competitive advantage, with data-driven insights and case studies to help you make well-informed, strategic marketing decisions, including:

The use of retail in-store analytics involves incorporating data tracking and analytics techniques to gain customer insights and make informed decisions about the performance and operations of physical retail stores. By collecting and analyzing various data generated within the store, such as customer behavior and interactions, retailers can optimize store layouts, improve operational efficiency, and enhance the overall shopping experience.

This playbook reveals how brands can break down data silos, personalize marketing, and optimize loyalty programs to increase customer retention and revenue. Retailers are collecting more customer data than ever — but many fail to use it effectively. Without a clear data strategy, brands risk wasted marketing spend, missed opportunities, and customer churn.

Smart brands have employed a strategic roadmap for transforming raw data into powerful customer engagement strategies. With a blend of integrated campaigns, cross-channel personalization, and loyalty programs, brands can build stronger connections and drive measurable business impact.

By postponing the deprecation of third-party cookies, Google just did everyone a big favor. You may have sighed relief, but don’t get too comfortable. Few advertisers were truly ready for a cookieless web. Like a math test in school, where almost no one is really ready, moving the deprecation of cookies to mid-2023 has been met with an industry-wide sign of relief. Unfortunately, like with the postponed test, this has been followed but the same response we all often had in school; a belief that there is now extra time to waste.

Marketers must move beyond backward-looking metrics and embrace AI-powered qualitative insights to anticipate emerging narratives, shape brand perception, and stay ahead of cultural shifts. Marketers face increasing challenges in determining which social narratives to engage with. Without staying ahead of these conversations, they risk irrelevance. Traditional data is backward-looking, analyzing content performance only after it has been tested against an algorithm, making it an inadequate tool for anticipating trends.

Here’s the deal: if you’re an enterprise brand looking to crush it in today’s competitive market, success hinges on your data strategy. Most brands already strive to create a complete, unified view of customers – but messy, fragmented data is usually the norm. So how do you bridge the gap? Download this guide and learn:

Access to centralized customer data (even if it’s not perfect!)

Everything starts with getting your data all in one place – which most brands are already doing, at least to some extent. This means centralizing all customer data across your tech and teams into a single repository or data lake, ideally in a modern data cloud like Snowflake, BigQuery, or Databricks. The key is to then make sure all that data is accessible to your marketing team from that central place.