What would you do if your e-commerce store could see into the future? Your competitive advantage would be untouchable. You don't quite have access to that powerful of a tool, but predictive analytics comes close.
This solution looks through your data sources and uses a model that predicts likely next steps. For example, do you know what characteristics indicate a customer is close to making a purchase? What would you do if you knew?
Explore these five use cases that improve everything from your inventory management to your customer experience.
1. Inventory Management
Your customer found what she was looking for, and is ready to buy. There's only one problem–it's out of stock. EConsultancy reports 25 percent of your abandoned carts come from consumers frustrated by unavailable inventory. Predictive analytics helps you keep appropriate inventory levels by tracking customer demand, overall supply and other metrics.
2. Promoting What's Hot
3. Improved Customer Experience
The global marketplace often makes it difficult to compete purely on price, but your customer experience serves as another important differentiator. One of the best-known examples of predictive analytics creating seamless processes for customers comes from Amazon. Each customer sees personalized content throughout the website, such as the recommended products relevant to their interests. The company also holds a patent for anticipatory shipping, which uses analytics insights to ship products to fulfillment centers before customers place orders. The shipping time drops drastically when the products reside at the closest warehouse rather than one across the country.
4. Price Changes
5. Spot Losers
Predictive analytics puts your e-commerce data to work. Are you relying solely on ad hoc analysis and intuition? Or is your data driving your business forward, continually improving your assortment, pricing, promotions and overall growth and profitability?