Drive Retail & E-Commerce Success With Predictive Analytics
Retailers and e-commerce sellers collect data in massive quantities. With today’s shifting trends and stiff competition, businesses must take full advantage of this rich resource through Predictive analytics uses data, statistics, and machine learning techniques to build mathematical models that can generate predictions about things likely to happen in the future…. for retail and e-commerce.
Worldwide retail sales are estimated to grow 5% YoY in 2022 and will likely exceed $27.33 trillion. Consumers have returned to shopping at brick-and-mortar stores again, and online retail and e-commerce growth is likely to slow. Yet more than 20% of global retail sales will still happen through e-commerce outlets.
Across these channels, today’s customer expects a seamless shopping experience. Whether in-store, on the web, on mobile, or elsewhere, customers want a consistent experience that provides both personalization and convenience.
Analyzing your customer data and purchase history might have seemed sufficient in the past. But in today’s fast-changing environment, retailers and e-commerce sellers need to get ahead of shifting trends. Historical data no longer provides a reliable guide.
Businesses must plan proactively for what customers will do in the future. Anticipating customers’ needs allows you to provide customers with the relevant products and services they want — when, where, and how they want them.
In addition, retailers and e-commerce companies need to prepare for consumers’ changing attitudes toward privacy, data sharing, and trust. Planning better ways to use your company’s First-party data is the data that a company collects itself instead of acquiring it from other sources. For example, data on visits to the company’s… with machine learning is critical as the privacy ecosystem changes.
In this whitepaper, we discuss significant trends in the retail business and in e-commerce that are shaping how marketers can best use their data. We examine changes in customer attitudes and how predictive Analytics is a business practice that uses descriptive and visualization techniques to gain insight into data; those insights can then be used to guide business… for e-commerce and retail can anticipate and personalize the customer journey. We’ll also dive into details on six predictive strategies, with examples of how businesses benefit from these strategies:
- Lead scoring is a method of predicting the chance a new lead (prospective customer) will become an actual customer. Each lead is assigned a score…
- Likelihood to opt-in or subscribe
- Conversion Broadly speaking, optimization is a process used to either maximize or minimize an output value by selecting the right input values. In data science, this…
- Customer lifetime value and VIP identification
- Customer churn and retention
- Customer upsell and Cross-sell models are developed based on customer data and can identify which complementary products might most interest a specific customer. The goal of these models…