To gain a competitive edge and know their customers better, predictive analytics is becoming popular among the major e-commerce players today. Other than the e-commerce industries, some other industries that use predictive analytics include banking and financial industry, retail sector, manufacturing industries, health insurance companies, energy industry, and public sector, among others. It lets you discover insights about future. Some reasons why every e-commerce player is using predictive analytics for collecting enough data about their customers’ transactions and buying patterns are:
Launch better-targeted promotions
Doing business without any kind of promotion would mean that only you know what you are doing and what your business is all about. Nobody else would know it unless you advertise it. Predictive analytics help e-commerce firms determine personalized promotions and advertisements, according to the niche that they want to target. This allows them to optimize their marketing campaigns and send targeted emails and messages to each of their target customer segments.
Predictive analytics help to forecast sales and demand, through which it becomes easy to figure out how much stock of inventory would be sufficient. This ensures timely delivery and no wastage or shortage in inventory, which results in greater customer satisfaction.
Managing the cash flow for your firm could be challenging if your firm doesn’t have a specific idea about the sales estimates. Predictive analytics help to optimize the different industry verticals and increase their overall revenue generation.
Prices cannot be kept absolute and constant on an e-commerce portal because that would encourage people to go to other portals or retailers, which would offer a better deal to them. Predictive analytics help you manage pricing by looking at the past data for products, sales, customers’ purchases, etc and determining what prices would be suitable at what times, what targeted discounts, promotions and segment-based pricing should these portals offer to target different customers. They adjust prices based on their customer browsing information and their purchase patterns, resulting in maximized profits.
Predictive analytics have pre-built fraud models that analyze customer behavior and sales, which help to identify potential frauds and threats, and thereby, remove the fraud-susceptible products. This reduces chargebacks as well as the fees required to process chargebacks.
Better customer service
Predictive analytics model specific to the needs of the retailer’s customer service, help to understand whether having phone service is mandatory, should the site only have an email customer service, whether it needs to also have a live chat support, what should be the optimal hold time when someone calls, how to prioritize questions between loyal, high-value, and least important customers, etc.
Make decisions in real time
Since a retail environment is high paced, taking real-time decisions is an important aspect that e-commerce firms consider. Predictive analytics help to analyze data and generate insights to allow retailers to take real-time decisions. Through this, the retailers are able to know the best day to launch a particular promotion, target segments with specific marketing campaigns, and determine
To be aware of the changing consumer behavior and habits
Modern consumers and retailers are technology dependent. As technology is changing and advancing, so is the consumers’ behavior. Predictive analytics in e-commerce portals help to focus on the most recent consumer habits.
Accurate demand forecasts are so important because inventory is expensive and firms cannot afford to waste it, neither they want to run out of stock. Since the inventory is distributed by geographical regions, it is essential to get specific regional forecasts, to know what products are popular and demanded in what regions. Predictive analytics allow e-commerce firms to estimate demand patterns by geographical locations.
This is an import aspect that e-commerce portals consider understanding what their customers are looking for, what are their likes and preferences, and their click-through behavior, in order to show their customers relevant product matches and personalized recommendations. Predictive analytics make this an easy task for them.
The challenge to determine what products should be recommended and promoted where is overcome by predictive analytics. It uses algorithms to understand consumer behavior, based on which product recommendations are targeted. This ensures greater chances of generating sales.
Predictive analytics is becoming increasingly popular among e-commerce firms since it helps them get future insights and track their consumers, which helps them to retain them better and improve engagement with them. The list of their benefits is inexhaustive.