Enterprises today must leverage data analytics to stay competitive and retailers, in particular, have a wealth of customer data, which can be used to personalize offers, predict buyer behavior, improve inventory management and more.
In this post, we’ll highlight some of the top advanced analytics trends impacting the retail industry today, and discuss the new opportunities they’re affording retailers and customers alike.
Flexible pricing strategies
The cornerstone of any good retail strategy begins with pricing and advanced analytics offer insights into customer behavior that were previously unattainable.
Retailers no longer set fixed prices for every product because they have a greater understanding of the value placed on products. For example, they may see that older shoppers are willing to pay more for an item than younger shoppers. Setting a higher price may yield better margins, but it could also mean reduced business from those younger shoppers.
With advanced analytics, you can better understand what segments, and even individuals, are willing to pay. By pricing products differently, you may capture more revenue from more customers.
Key insights through customer engagement analyses
Deloitte recently examined how retailers can better navigate the many uncertainties in their industry through analytics. You can perform customer engagement analyses revealing key insights about the future behavior of customers, including:
- Customer engagement assessments that identify overlooked customer segments that may be more willing to spend more
- Share of wallet assessments that identify the customer segments where companies are lose market share, whilst also identifying which customers are likely to spend more on a product
- Customer churn predictions that identify which customers are most likely to stop purchasing a company and the factors predicting customer churn
Real-time analytics for faster responses to market shifts
Advanced analytics don’t just offer better insights into historical data; today’s tools can analyze data in real-time giving you the ability to adapt to unforeseen changes in your customers or supply chain.
Though retailers have strategies for tackling their markets, the lack of real-time data meant they were always reacting to unexpected changes rather than proactively mitigating them.
Take for example a clothing retailer that sees some of its products aren’t selling like they predicted several months into the season. They have no choice but to mark the products down, meaning significant revenue loss. But real-time analytics identifies these problems earlier, and it gives retailers a chance to swap out products with other, better selling ones.
Omnichannel data integration for marketing optimization
Retailers with an e-commerce presence are leveraging omnichannel analytics tools that integrate seamlessly with their online marketplaces to pull online performance data and analyze it alongside brick-and-mortar stores.
Omnichannel data specifically benefits retailers in attribution modeling. With traditional advertising channels, like television and billboards, it’s difficult to see the exact the number of people your ads reached. Attribution modeling helps retailers understand exactly how customers are buying their products and thereby enables them to make better informed investment decisions.
Some examples of attribution modeling include:
- Pay-per-click (PPC) advertising where users click on an ad on search engine like Google
- Organic searches where users find your website by searching for specific keywords
- Social media advertising where users click on your site after seeing an ad on Facebook, Instagram, etc.
This information empowers you to provide customers with seamless experiences, regardless of the channel, because a customer who views a product on their laptop can then see an advertisement for that same product on their phone.
The advanced analytics imperative for retailers
Leveraging data is a necessary and powerful tool for retailers. Real-time insights help them adapt to an ever-changing consumer landscape, while increasing revenues through dynamic pricing strategies and omnichannel data.
Retailers can maintain a competitive advantage, while reducing costs and continuing to delight customers, by adopting advanced analytics strategies and over time, their prominence and usefulness will only intensify for this industry.