Within the last 10 years, the retail industry has experienced an unprecedented digital transformation, further supercharged by the pandemic. In fact, since the pandemic began in 2020, e-commerce has grown two to five times faster than years previous, and in 2022, global e-commerce sales were expected to reach $5.5 trillion.
This growth in digital transformation means that online retailers now have more data than ever to organize and leverage for decision making. As a result, brands need to identify ways to tap into all of that insight-rich data faster than their competitors to find smarter ways to meet shifting customer preferences and outflank the competition.
In truth, nearly 50% of brands say working with data will be their biggest challenge over the next year, according to research from Shopify. To capitalize on the amount of data created by the current ecommerce boom, retailers must prioritize the development of their own modern data stack.
Unfortunately, with ever increasing data volumes and complexity, data teams cannot keep up with the demand for insights — particularly while relying on traditional business intelligence dashboards that only provide a limited view into data. With a modern data stack fueled by artificial intelligence (AI) and advanced analytics, retail businesses can make data-driven decisions that can fuel competitive advantage and boost bottom lines, while easing the strain on their data teams.
The new insights provided by the modern data stack can help brands further understand their customer base, mitigate any supply chain problems and discover creative ways to stand out to the average consumer.
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 augments human decision-making by applying the power of AI and automated data analysis to help more people throughout the organization — from business teams to data analysts — get faster insights from data.
Decision intelligence goes beyond sharing what happened, working to uncover the reasons why metrics change and sharing recommendations on how to achieve business goals in a specific, targeted way. Retailers and brands have the huge opportunity to use decision intelligence to make better and faster decisions that enhance customer experience and brand loyalty, boost sales, and make it easier to navigate complex supply chains.
1. Strengthening and Amplifying the Customer Experience
Consulting firm Forrester found that “data-driven” companies are 23 times more likely to acquire new customers and 19 times more likely to be highly profitable. This is especially true in instances when brands can use data to understand how consumers shop both in store and online to produce a superior and seamless customer experience.
Decision intelligence can help retailers analyze consumer behavior more deeply, enabling them to provide personalized attention to each shopper to increase brand loyalty. For example, brands could use decision intelligence to identify customers who are more likely to make repeat purchases or to discover the most high-value customers by predicting future purchases based on past behaviors. This type of personalized, enhanced experience will ultimately keep customers coming back for more. In fact, according to Shopify’s 2022 consumer study, 50% of consumers say personalization based on their interests and past purchases have influenced their decision to purchase from a brand over the last year.
Decision intelligence can also help retailers find new ways to engage with customers. This can take several different forms based on customer shopping habits, but it can include campaigns such as customized advertising on social media or offering a discount code to recurring online shoppers. Decision intelligence can also analyze every customer transaction, preference, and interaction to help retailers optimize promotions, product recommendations, and advertising channels.
2. Increasing Sales
Nearly 70% of online shopping carts today are abandoned according to Shopify, leaving a great deal of sales revenue untouched for retailers and e-commerce providers. Decision intelligence can analyze web traffic and click patterns together with user data to inform brands of shopper preferences and habits and provide the insights to encourage more transactions. By giving product line managers and other decision makers the ability to analyze this data directly, critical data insights such as new consumer patterns or anomalous behaviors can be identified quicker and used to drive faster, more informed decisions.Such decisions include simplifying the checkout process and removing any barriers so customers can more easily complete their purchases.
Customer data can also be used with decision intelligence to increase product cross-selling and up-selling. Getting customers to bundle more items with their purchase and convincing customers to upgrade are two of the most tried-and-true tactics for increasing profits by up to 30%, according to Mckinsey.
With decision intelligence, retailers can analyze historical purchase patterns, identify the best opportunities for additional sales, predict the likelihood that customer segments will accept specific upsells and cross-sells, and then recommend the specific upgrades and additional products for purchase. This will ultimately increase the likelihood of a new customer to return if they like their purchase and will keep sales high.
3. Building a Better Supply Chain Strategy
To maintain healthy profit margins and fulfill customers’ expectations of lightning-fast delivery, retailers’ supply chains must be as efficient as possible. Companies are relying more and more on data to make informed business decisions related to their supply chains, and decision intelligence can take some of the weight out of this decision-making by offering streamlined analysis.
For example, decision intelligence can help users find and exploit opportunities to remove delays and inefficiencies from the supply chain. From these insights, retailers can take informed, targeted steps to reduce transportation costs, optimize inventory levels, streamline distribution center processes, and improve suppliers’ performance.
Building customer relationships, driving profitably, and squashing inefficiencies in today’s data-driven world requires an innovative approach to analytics. Decision intelligence cuts down data analysis time to place the most important insights directly in the hands of decision makers, increasing collaboration between business and data experts and reducing the reliance on data scientists who cannot possibly answer all the questions their colleagues have.
With AI-powered augmented analytics, brands can overcome the challenges of analyzing and leveraging massive volumes of data in shorter periods of time to deliver better customer experiences, increase sales, and create more efficient supply chains.
— Ajay Khanna, CEO and Founder, Tellius