The pandemic has accelerated a significant digital transformation in the retail industry over the last decade. E-commerce sales have grown exponentially since 2020, with sales increasing by two to five times compared to previous years. By 2022, global e-commerce sales were predicted to reach $5.5 trillion. As a result, online retailers now have access to more data than ever before, which means that brands must find ways to utilize this insight-rich data faster than their competitors to gain a competitive advantage and meet shifting customer preferences.
Almost 50% of brands believe that working with data will be their biggest challenge in the coming year, according to a recent study by Shopify. To capitalize on the amount of data generated by the current e-commerce boom, retailers must prioritize the development of their modern data stack.
Unfortunately, traditional business intelligence dashboards can only provide a limited view of the data, making it difficult for data teams to keep up with the increasing data volumes and complexity. By utilizing a modern data stack that incorporates artificial intelligence and advanced analytics, retail businesses can make data-driven decisions that boost their bottom lines while easing the strain on their data teams. These new insights can help brands better understand their customers, address supply chain issues, and find innovative ways to stand out from competitors.
To bring the power of the modern data stack to life, many retailers and e-commerce platform providers are turning to decision intelligence, one of Gartner's top technology trends for 2022. Decision intelligence leverages AI and automated data analysis to augment human decision-making, providing faster insights to business teams and data analysts. It goes beyond reporting what happened, uncovering the reasons for changes in metrics, and offering targeted recommendations for achieving business goals. Retailers and brands can use decision intelligence to make faster and better decisions, leading to enhanced customer experiences, increased brand loyalty, boosted sales, and better management of complex supply chains.
More efficient supply chains
Efficient supply chains are crucial for retailers to maintain healthy profit margins and meet customers' expectations of fast delivery. In today's data-driven world, companies rely on data to make informed decisions, and decision intelligence can simplify this process by offering streamlined analysis.
For instance, decision intelligence can help retailers identify opportunities to remove inefficiencies from the supply chain, allowing them to take targeted steps to reduce transportation costs, optimize inventory levels, streamline distribution center processes, and improve supplier performance.
To build customer relationships, drive profitability, and eliminate inefficiencies, businesses need an innovative approach to analytics. Decision intelligence can reduce data analysis time and provide important insights to decision-makers, increasing collaboration between business and data experts and reducing reliance on data scientists.
Using AI-powered augmented analytics, brands can overcome the challenge of analyzing and utilizing massive volumes of data in shorter time periods, resulting in better customer experiences, increased sales, and more efficient supply chains.
According to Shopify, almost 70% of online shopping carts are abandoned, resulting in a significant loss of sales revenue for e-commerce providers and retailers. By analyzing web traffic and click patterns with user data, decision intelligence can provide brands with insights into consumer preferences and habits to encourage more transactions. Critical data insights, such as new consumer patterns or anomalous behaviors, can be identified faster and used to drive faster and more informed decisions, including simplifying the checkout process and removing any barriers that prevent customers from completing their purchases.
Using customer data with decision intelligence can also increase cross-selling and up-selling opportunities. Mckinsey reports that bundling more items with a customer's purchase and convincing them to upgrade are two effective tactics for increasing profits by up to 30%. Decision intelligence enables retailers to analyze historical purchase patterns, identify the best opportunities for additional sales, predict the likelihood of customer segments accepting specific upsells and cross-sells, and recommend the appropriate upgrades and additional products for purchase. This approach can increase the probability of new customers returning and maintaining high sales.
Higher customer satisfaction
By understanding how consumers shop both in store and online, companies can use data to produce a superior and seamless customer experience, which leads to greater customer acquisition and profitability. Consulting firm Forrester discovered that “data-driven” companies are 23 times more likely to acquire new customers and 19 times more likely to be highly profitable.
Retailers can use decision intelligence to analyze consumer behavior deeply, enabling them to provide personalized attention to each shopper and increase brand loyalty. This can include identifying customers who are more likely to make repeat purchases or predicting future purchases based on past behaviors to discover the most high-value customers. According to Shopify's 2022 consumer study, 50% of consumers say personalization based on their interests and past purchases influenced their decision to purchase from a brand over the last year. Providing personalized, enhanced experiences ultimately keeps customers coming back for more.
Retailers can also use decision intelligence to find new ways to engage with customers, such as customized advertising on social media or offering discount codes to recurring online shoppers. By analyzing every customer transaction, preference, and interaction, decision intelligence can help retailers optimize promotions, product recommendations, and advertising channels."