Seeing daily recommendations for products on your favorite social media platforms has become the norm. But have you ever wondered what kind of technique is used to know which product you’re likely to buy? It’s called predictive analytics, and it works on a principle of collecting and analyzing purchasing history, browsing patterns, and other types of customer’s activity. The data is later used to know what kind of products do people want and when. Also, it is much easier to make recommendations and sales offers with the buyer’s information at hand.
Predictive analytics can ultimately turn your eCommerce business into a powerful practice by using statistics about the behavior of your customers.
This practice is of great value to large-scale as well as smaller companies, and both can profit from it as well (especially if they have an online shop). Following are some of the reasons why predictive analytics is crucial for eCommerce.
Trend Forecast
Trend forecast helps to promote the products that will soon become popular among visitors. Online retailers can predict which items they should have in stock and which products to put on sale. The result: Not only this prediction improves customer engagement, but it also influences the inventory management.
Although trend forecast was invented well before the times of internet, the process of collecting big data lets you know what your customers want before they do. Trend forecast uses the data gathered about your customer’s buying habits: The more precise information is used in the overall statistics the best as over time your company will be able to track customer behavior with their actions on your website.
Better Inventory Management
When the online vendor knows what quantity of items he needs to order, it is much easier to manage the inventory. The problem of overstock is a major issue to most retail businesses as keeping track of real-time inventory and its management can be not only time consuming, but it also requires a huge amount of resources. That’s where the predictive analytics can be a powerful tool to reduce the amount of ordered goods planned.
Overstock and out of stock issues are less likely to occur when predictive model clearly indicates that there is no need for certain types of goods leaving retailers with the possibility of investing their resources elsewhere as, for example, funds for a better marketing strategy or simply buy products of higher demand.
Price Optimization
Except for ameliorating inventory management, the track of a customer’s activity can help to determine the right price of a product. In fact, price optimization can be the sole most critical factor that affects the conversion rates.
It goes without saying that A/B testing is one of the most accurate ways to determine the ideal price of your products. However, this approach takes a lot of time, and it makes harder for retailers to set up the prices in real-time.
Predictive analytics software uses much broader sets of data, such as desired profit margins, competitor’s prices, available goods, purchasing history, browsing habits, etc. What’s more, it tracks all of those factors in real-time, while comparing them with last year’s information, thus providing an accurate pricing model for every individual item at any given time.
Effective Target Promotions
No eCommerce marketing strategy is complete without a well thought out plan of effectively targeting your promotions to the right clients. The incorporation of predictive analytics will help your business attract only relevant customers. By making effective and constant use of this tool, businesses yield higher conversion rates and, ultimately, a higher revenue.
Despite the wide range of programs that help online shop owners to target customers and offer better promotions, advertising strategy can use the predictive model as an addition to other aspects of a marketing plan. For example, some companies ask visitors to take a survey about their preferred products and then use predictive analytics to offer them the items they might like at a lower price.
Using Predictive Analytics in eCommerce
Trend forecast, good inventory management, price optimization, and effective target promotions all lead to enhanced customer engagement. When online retailers offer products ahead of time with effective advertising approaches, customers are more likely to visit the website.
But, where to start?
Tracking customer behavior is crucial for the success of a marketing campaign and InstantSearch+ is one of the main sources of predictive analysis software available in order to make the process fully-automatized.
Moreover, this company’s range of e-commerce tools is absolutely fool-proof, proving to be an invaluable resource to retail site owners who do not have at their disposal a big budget for a technical department. All it requires is the installation of a simple plugin on your eCommerce site.
Once the navigation and the design of your eCommerce shop is all set, you can add the predictive analytics factor to start analyzing the shopping patterns. With the plug-in installed you will easily navigate the customers through the site to show them the most relevant products.
The collected data will then match the right person with the perfect item through product recommendations. These recommendations allow you to have heaps of satisfied customers and give you more data in turn. A win-win situation, right?
However, product recommendations are often not enough to assure the purchase. In this case, it is great to know what the customers want, assist them in the shopping process, and reply to them at all times with no errors.
This last step involves interaction, so eCommerce search bot can help you automatize the responses through apps like Telegram or Facebook Messenger.
Conclusion
To sum up, predictive analytics help large and small businesses in their race for a bigger customer base. Whether it is used in every step of the business strategy or just one marketing aspect, it can be a huge competitive advantage and enhance overall customer experience and revenue.