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We used to wish we’d know what online visitors wanted to buy.
Big data and predictive analytics is close to giving us that. In fact, a lot of businesses nowadays – including your competitors – are already using it to identify opportunities for engaging and converting their leads and prospects.
If you’re a bit skeptical about the potentials of predictive analytics, then you should see some of ways the world’s most successful companies are using this technology to boost their competitive advantage and drive sales:
1. Determine customer preferences to personalize content
The most extensive use of predictive analytics in ecommerce is predicting what visitors want to buy based on their demographic and psychographic profiles. Using the combination of visitor information with their browsing and purchase behavior, companies are able to increase engagement by delivering highly personalized, highly targeted content and advertisements.
Amazon, as we all know, is the paragon of retailers everywhere in harnessing the power of predictive analytics. Amazon’s growth is fueled by their ability to use data to build a complete picture of their online visitors and then predict customer purchase. It has seamlessly integrated its predictive technology into every aspect of the purchasing process, tracking visitor behavior from the moment he/she logs in order to make effective recommendations for current and future purchases.
Netflix, another forerunner of personalized product recommendations, utilizes predictive analytics to deliver highly relevant content to users. Netflix gathers data on users’ preferred genre, ratings given, views, surveys, and other actions to predict and recommend movies and shows. According to the company, 75% of what people watch on its platform can be traced to its personalization efforts.
Predictive analytics combined with geotargeting can produce remarkable sales results, as the experience of sportswear-maker Helly Hansen shows. Helly Hensen achieved 170% conversion rate by predicting what its visitors were likely to buy based on weather forecasts in the visitor’s location.
2. Estimate customer lifetime value
Predictive analytics also helps businesses identify visitors who are more likely to become high-value or loyal customers. In B2B, this is called predictive lead scoring, wherein prospects are analyzed and ranked according to their likelihood to buy. The same technology is also applies to predict customer churn. By utilizing data, both ecommerce and B2B companies are able to plan their marketing and sales strategies to attract and retain customers, as well as prevent losing them.
The ability to estimate customer lifetime value helped shoe manufacturer Crocs transform its online marketing strategy to become less driven by heavy discounting. Crocs’ marketing team used big data to identify customers who were more likely to become dissatisfied with the absence of discounts in order to test a new, no-discount online experience. Based on insights from their initial testing, the team optimized their promotions for their more affluent customer base, resulting in increased average order value and overall company margins.
3. Optimize inventory management to increase profitability
Predictive analytics is also being used by successful companies to improve back-end operations. Inventory management, for instance, is critical to the success of online retailers. They must be able to accurately predict demand for certain items in order to optimize stock replenishment. Otherwise, they are bound to carry too much of certain items that customers don’t want while constantly running out of stock on the products that are in-demand.
Retail giant Walmart, for instance, utilizes a cutting-edge inventory management system called vendor-managed inventory (VMI) which provides its suppliers with data on inventory levels and predicts re-stocking needs. This technology not only allows Walmart to reduce the costs of inventory management, it also helps the company decide which products to buy according to customer demand and keep the optimum number of stocks for products with high profit potential.
While you can’t achieve success by simply copying the predictive analytics strategy of these companies, they are proof that predictive analytics pays off.  Learn where and how predictive analytics can create the biggest impact in your organization before investing in the tools and technology, so you can create a predictive analytics strategy that’s tailored for your specific business, consumers, and industry.
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