4 Ways Predictive Analytics is Redefining E-commerce

When most people leave their jobs, they lose their salaries, benefits, and a desk. When Ronald Wayne left his job, he lost $280 billion.

Ronald Wayne founded Apple along with Steve Jobs and Steve Wozniak, and when he left after just 12 days, he sold his 10% share in the company for $800 – a share worth hundreds of billions of dollars today. For context, no single person currently owns as much as 3% of the company. If Ronald Wayne had just kept back 16 cents worth of stock, he would own as much as current Apple CEO Tim Cook.

If Ronald Wayne had a way to predict the future, he would have made different decisions. Unfortunately, there’s no crystal ball to predict the future, but there are tools that can give you a fighting chance.

Predictive analytics redefines e-commerce by helping companies anticipate future needs and find the best path forward in uncertain times.

Key Takeaways

Optimize your digital spaces with predictive analytics.
Predictive analytics can help you easily qualify leads.
You can use predictive analytics to determine the best pricing strategy for your business.
Forecast demand using predictive analytics with Hypersonix .

Overview of Analytics

While the broad idea of “analytics” frequently moonlights as an umbrella term for any data-driven process, analytics is a field of computer science that uses technology to find meaningful patterns in data. Within this broad idea of analytics, several subcategories exist, including descriptive, diagnostic, predictive, and prescriptive analytics.

Descriptive analytics looks to the past to describe past activities in data-driven terms. For example, descriptive analytics may answer questions like “When were our sales at their highest?” or “which template leads to the highest conversion rate?”
Diagnostic analytics similarly look into the past, but this time answer questions like “ why were our sales so high in 2019″ or “ why does this template lead to the highest conversion rate.” In comparison, descriptive analytics describes and diagnostic analytics diagnoses.
Predictive analytics, unfortunately, can’t use data from the future, so it does the next best thing. Predictive analytics uses data to make predictions about future trends. Predictive analytics answers questions like “which product will perform the best in this market?” and “what is the lifetime value of this customer?”
Prescriptive analytics goes hand in hand with predictive analytics rather than simply predicting future outcomes. Prescriptive analytics uses data to determine the best path to achieve intended results.

These categories of analytics are not discreet, meaning they overlap, work in tandem, and often describe different aspects of the same process. In particular, predictive and prescriptive analytics work hand in hand because questions like “how will this design change impact sales?” and “what’s the best design change to achieve a certain sales impact?” are really two different ways of describing the same kind of data.

Space Optimization

In the world of brick-and-mortar retail, businesses use planograms to optimize their store layout. While this kind of visual merchandising has a long history in physical storefronts, e-commerce retailers can apply the same tools to their online storefronts.

Imagine that you are selling homemade candles. You have 40 different types of candles in different scents and sizes and a few accessories like matches and wax trimmers. You ostensibly have two categories of products: candles and accessories, but should you split your visual space 50/50 between these categories?

Not only should candles rank higher on your visual hierarchy, but you should draw attention to specific scents and sizes as well. Predictive analytics helps the most successful e-commerce companies (like Amazon and Alibaba) determine which products should take precedence and when.

Lead Qualification

Your sales funnel is full of leads from a variety of sources. Unfortunately for e-commerce companies, not each of these leads will convert into a sale. Among the leads that do, not each converted customer will result in the same lifetime value. Predictive analytics helps e-commerce companies qualify leads by using historical data to predict which kinds of leads will result in conversion and which of those converted customers will provide the greatest lifetime value.

Pricing Strategy

Pricing strategy is extremely complex and varies wildly from industry to industry. With no one-size-fits-all answer available to e-commerce companies, predictive analytics is the best way for you to determine the best strategy for your unique company and market.

Demand Forecasting

Predictive analytics redefines e-commerce by helping companies forecast demand and adjust their strategies accordingly.