Understanding Customer Behavior

One of the primary goals of retail analytics is to better understand customer behavior. By analyzing purchase history, demographic data, in-store behavior and more, retailers can gain valuable insights into what types of products and brands resonate most with different customer segments. They can see what influences purchase decisions and what deters customers from buying. For example, a retailer may find that millennial customers are more likely to purchase when certain styles or brands are on trend on social media. Or they may see that customers who live closer to a store are more frequent buyers than those who live farther away. Gaining these kinds of actionable behavior insights allows retailers to make data-driven decisions about merchandising, marketing and more.

Improving Personalization

With a clearer picture of customer preferences, Retail Analytics can significantly improve their personalization efforts. That may mean sending tailored email promotions featuring products a specific customer is most likely to purchase based on their profile. It could involve tailoring the layout of an e-commerce site to better suit individual shoppers. In-store, tablets or interactive displays can provide personalized recommendations and introduce customers to new brands or items they may enjoy based on past purchases. Advanced personalization like this increases relevance and drives higher engagement, conversions and average order values.

Optimizing Inventory and Reducing Waste

By tracking sales velocity, seasonal trends and more, retailers gain a better sense of demand forecasting and can optimize inventory levels accordingly. They can order smarter quantities of the just right products without overstocking slow-moving items. Analytics also helps identify conditions under which products sell best, so retailers know what to feature together for improved cross-selling. With such insights, they reduce excess inventory, out-of-stocks and wasted floor space from slow sellers. That strengthens profit margins. Predictive analytics helps retailers foresee demand shifts so they're prepared with the right assortment as customer preferences change over time.

Improving Store and Website Experience

Retailers are applying analytics to make ongoing improvements to the in-store and digital shopping experiences. For example, they can see which areas or sections of a store are most trafficked to identify where additional staffing, signage or product displays would boost conversions in those aisles. Way-finding and interior layout optimizations help customers find what they need faster. Online, eye tracking and click-stream data exposes points of confusion or drop-off on websites that can be streamlined. Understanding task completion paths gives insights for simplifying navigation and checkout. These kinds of continuous experience enhancements based on analytics keep the brand top-of-mind and make the shopping process as seamless and personalized as possible.

Pricing and Promotions Optimization

Leveraging analytics, retailers have more data to strategically optimize pricing, promotions and discounts for maximum profitability and ROI. They gain an understanding of price elasticity for different products and customer segments. For example, some categories may see increased overall revenue from occasional sales compared to steady everyday pricing. Others retain value better at higher regular price points. Analytics also guides promotional strategy like knowing which daypart drives the most traffic or when bundle offers resonate most. Retailers maximize every advertising dollar spent when guided by quantitative analytics on response rates, click-throughs, conversion lifts and more.

Driving Growth Through Better Decision Making

As the above examples illustrate, retail analytics provides a treasure trove of customer and market insights that simply weren't available before today's advanced data collection and analytical capabilities. By leveraging analytics across key areas like merchandising, personalization, inventory, experience and more, forward-thinking retailers are making dramatically improved strategic and tactical decisions. Those decisions are directly translating to accelerated growth through increased customer satisfaction, conversions, average order values, margins and lifetime customer value. In today's ultra-competitive retail landscape, leveraging the power of data analytics is arguably one of the single most impactful ways for brands to outperform competitors and empower ongoing success.

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