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How to Use Omnichannel Retail Analytics to Grow Revenue and Improve Profitability

Retailers are challenged to meet evolving consumer needs with speed while delivering an excellent customer experience. In today’s complex omnichannel environment, visibility is crucial for anticipating customer preferences, understanding operating costs, tracking performance trends, and optimizing supply chain performance

Omnichannel retail analytics allows companies to combine customer and product data to unlock insights. With these insights, retailers can optimize every area of the business and deliver highly personalized customer experiences. In this article, we explore what retailers can do with omnichannel retail analytics, and we look at examples of successful retailers using omnichannel analytics strategies to drive revenue growth.

What You Can Do with Omnichannel Retail Analytics

With a powerful cloud data platform, retailers can leverage data generated from online and mobile transactions, data exchanges, social media platforms, SaaS applications, the Internet of Things, and more. The ability to analyze this massive amount of valuable data empowers retailers to accomplish several priorities.

Design and manage the customer journey

Today’s customer journey is complex. Consumers may see an ad on their social media feed one evening, do a search for the company on their laptop at work the following morning and sign up to receive a discount code, open a marketing email the following day, conduct research online over the next few days, see an ad as they pull up a news website, and finally visit the company’s website once more the following day to make a purchase. There are nearly infinite combinations of touchpoints and, as a result, myriad possibilities for the path any given customer might take.

Retailers are using omnichannel analytics to better understand customer intent and the journey each customer takes to purchase. With this understanding, they can improve conversion rates and increase customer satisfaction at the same time. Omnichannel retail analytics can be used to track customer behavior at various touchpoints to better predict demand and identify cross-sell and upsell opportunities. Additionally, analytics can help alert a company in real time when a customer is having difficulty completing a conversion or another goal, so the issue can be escalated to a customer success representative. And brick-and-mortar stores can use analytics to understand how shoppers navigate the store.

Personalize the shopping experience

Using analytic insights, retailers can integrate multiple internal and external data sources for a holistic view of customer behavior that can be used to more precisely focus marketing efforts. Complete customer profiles and data-driven segmentation improve decision-making based on past and present interactions.

Omnichannel retail analytics can also be used to engage with customers and quickly respond to needs via contextual listening, which is  listening to, and then acting on customer buying signals. Interactions can be personalized with relevant recommendations and messaging across all touchpoints. 

Improve merchandising

Retailers can analyze sales data and identify patterns to deliver insight to their merchandisers. Analytics can help predict customer demand by channel, geography, and other criteria, and forecast the impact of demand on sales. Additionally, merchandisers can use analytics to identify the best assortment mix based on various factors and objectives.

Optimize supply chain

With omnichannel retail analytics, retailers can evaluate historical sales data and run “what-if” analyses to produce more-accurate forecasts and plan for future events more effectively. Analytics can be used to identify supplier risks and predict disruptions due to weather and other factors. Additionally, retailers can use analytics to improve efficiency while also reducing transportation costs.

Increase data security

With retailers being significantly impacted by privacy regulations such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), improved data security is one of the most valuable benefits of analytics.

With the ability to analyze a wide range of data from many distributed sources, retailers can quickly detect abnormal login times, unauthorized requests, unusual email usage, and other anomalies, allowing them to respond faster and mitigate threats. In addition, analytics can automate threat hunting and detect the movement of data in and out of a network. 

Types of Omnichannel Retail Analytics

Let’s look now at two specific types of analytics that retailers commonly use to help them improve the customer experience and increase revenue.

Product affinity or market basket analysis

Product affinity or market basket analysis is used to identify which products are frequently purchased together. By analyzing the contents of various transactions and searching for attributes that appear together, retailers can find correlations and improve upsell and cross-sell strategies. Market basket analysis is used to improve product recommendation engine rules by funnel stage and other key factors to better tailor recommendations.

Product mix and placement analysis

To increase revenue, retailers must nail the right mix of products. Using analytics, retailers can measure the performance of particular SKUs, evaluate data by region, and uncover customer preferences and purchase behaviors to optimize product mix and placement.

Omnichannel Retail Analytics in the Real World

Let’s bring these concepts to life by looking at two examples of Snowflake customers who are using omnichannel retail analytics to personalize marketing and launch a product-matching service.

Pizza Hut accelerates decision-making during the Super Bowl

Pizza Hut operates over 18,000 restaurants in more than 100 countries. Pizza Hut is using Snowflake to capture data across systems and feed an analytics dashboard so executives can monitor key metrics and adjust resource allocations on the fly—even during peak demand times, such as during the U.S. National Football League’s Super Bowl. The company uses predictive analytics to ensure that customers receive the right messages and offers. 

In addition, Pizza Hut uses Snowflake Data Marketplace to access weather and geolocation data, which the team uses to correlate weather patterns with customer purchases and optimize targeted marketing campaigns accordingly. 

Read the full case study

Sainsbury’s gains greater customer insights and eases GDPR compliance

Sainsbury’s is the United Kingdom’s second-largest retailer, with over 1,400 stores and a large digital presence. The company offers customers distinctive, quality products at competitive prices across food, general merchandise, clothing, and financial services products. Sainsbury’s uses Snowflake to process transaction stream data as well as clickstream data from its websites. With Snowflake, Sainsbury’s was able to launch a product-matching service that compares its products with competitors’ products. The service is a popular feature on its websites. Additionally, with the Snowflake Data Cloud’s powerful governance capabilities, Sainsbury’s is able to quickly respond to GDPR requests. 

Read the full case study

Snowflake for Omnichannel Retail  

The Snowflake Data Cloud empowers retailers to improve operations and to seamlessly and cost-effectively create personalized customer experiences. 

Reveal every aspect of your business: From optimizing your supply chain to improving inventory management, Snowflake delivers the deepest insights needed for data-driven decision-making.

Create consistent customer experiences: With Snowflake, you can consolidate your omnichannel data to gain a universal view of your customers’ behaviors, preferences, and journeys. Engage and delight customers at every step with a 360-degree view across all digital and in-store touchpoints that make up the shopping experience.

Streamline inefficiencies across your business: Snowflake allows retailers to drive accurate supply chain planning, demand forecasting, inventory management, and more, with the advantage of virtually unlimited analytical scale and performance. 

Pursue new data monetization opportunities: Maximize revenue by unlocking value from previously siloed data with Snowflake’s secure data sharing capabilities. Additionally, you can access third-party retail data providers in Snowflake Data Marketplace. 

Omnichannel Retail Analytics Is Part of a Modern Retail Growth Strategy

More retail organizations are turning to the cloud to transform and scale their omnichannel retail analytics capabilities and unlock data-driven insights to optimize every area of their business, from driving supply chain efficiency to optimizing inventory management and fulfillment. The ability to make use of the massive amounts of valuable data being generated by today’s retail operations is an essential part of modern retail growth strategies.

See Snowflake’s retail capabilities for yourself. To give it a test drive, sign up for a free trial.