Retail Data and Analytics: How to Wow Your Customers

July 4, 2023

Retail data and analytics are reshaping how brands and customers connect in 2023. With online tracking facing more restrictions and customers demanding more data privacy, brands need to smartly use data to offer attractive and relevant experiences to their customers on all channels.

Customers value personalization and associate it with positive feelings that make them loyal to a brand. According to a recent McKinsey report, personalization marketing can lower customer acquisition costs by up to 50%, boost revenues by 5 to 15%, and increase marketing ROI by 10 to 30%. In addition, it can improve customer outcomes and drive faster growth rates. Companies that grow faster drive 40% more of their revenue from personalization than their slower-growing counterparts.

In this article, we will look at some of the ways that brands can leverage retail data and analytics to deliver personalized experiences to their customers in 2023, as well as the opportunities and challenges that come with them.

Retail Analytics Data in Action:

Retail data analytics can be used in many ways to improve the customer experience, optimize operations, and increase the sales of retail businesses.

  • Business Intelligence: Retailers use tools to organize and visualize data, such as sales, inventory, pricing, and customer behavior. For instance, Walmart uses Data Café, a cloud-based data warehouse, to analyze over 40 petabytes of data and generate real-time insights for its managers and suppliers.
Retail Data and Analytics
  • Sales Forecasting: Retailers use data analytics to predict future sales based on historical trends, seasonality, promotions, and other factors. Target uses DemandTec, a predictive analytics tool, to optimize its pricing and promotions based on customer demand and competitor actions.
  • Demand Forecasting: This strategy helps retailers forecast the future demand for their products based on customer preferences, market conditions, and external events. As an example, ALFRED, H&M’s machine learning algorithm, analyzes data from online and offline channels and adjusts its production and distribution accordingly. 
  • Livestream Selling: With data analytics, brands can enhance their livestream selling platform and deliver personalized experiences to their customers. According to Shopify, 81% of brands plan to either increase or maintain investment in livestream selling to drive sales over the next 12 months. Livestream selling can help brands create a more engaging and authentic shopping experience for their customers, especially in categories such as fashion, beauty, and electronics. Take Macy’s, which launched its own livestream shopping platform called Macy’s Live in 2022. On this platform, customers can watch curated shows featuring Macy’s experts and influencers, get exclusive deals and discounts, and shop directly from the videos. Macy’s Live aims to replicate the excitement and discovery of in-store shopping online,while also providing personalized recommendations and tips to customers.
  • Artificial Intelligence: Combining AI with personalization provides a powerful tool for brands. By processing data from various sources, AI creates invaluable insights and predictions that enhance customer outcomes. Netflix and Spotify are prime examples of AI-driven personalization. Netflix tailors content recommendations and user interfaces based on subscribers' viewing history, ratings, context, and other factors. Spotify, on the other hand, provides personalized music suggestions and playlists based on users' listening habits, preferences, and moods.
  • Customer Interaction: AI can also enable new forms of customer interaction, such as chatbots, voice assistants, and AR, that can provide personalized assistance and advice to customers across different channels. According to Forbes, AI will be one of the top data science and analytics trends in 2023 as more businesses adopt AI solutions to enhance their decision-making and performance. In 2022, Sephora launched a new AR feature on its app called Sephora Virtual Artist, which allows customers to try on different makeup products virtually using their smartphone camera. Moreover, this Virtual Assistant also provides personalized product suggestions based on the customer’s skin tone, face shape, and preferences.
Retail Data and Analytics

Retail Data and Analytics: Opportunities and Challenges in CX

Retail data and analytics offer brands a precious opportunity to captivate and attract customers by tailoring products, offers, communications, and interactions to individual preferences. For instance, brands like Kohl's employ data and analytics to reward loyal customers with personalized coupons and optimize inventory, pricing, and promotions.

Moreover, personalization comes with challenges that can significantly impact the customer experience. Data management, privacy, personalization at scale, and measuring impact are among the main hurdles that brands must overcome. Mall of America faced challenges in personalizing its navigation experience for visitors and, to become a leader in the sector, invested in AI-powered chatbots and location-based services. 

Bottom Line

Retail data and analytics are the magic ingredients for personalized customer experiences in 2023. By using data to spice up products, offers, communications, and interactions for each customer, brands can delight and retain their customers. However, personalization also involves some challenges that call for smart data management, privacy respect, scalability innovation, and impact measurement. How is your brand using retail data and analytics to cook up personalized customer experiences in 2023?

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