The success of any ecommerce business, nowadays, depends on the insightful information about their customers and competitors more than ever. This is why businesses are paying more attention on how their customers respond to a marketing campaign or a new product, for instance, or may be on what their competitors are doing that attracts their target market. The science of extracting this crucial data is termed as data mining, and according to experts, data mining is the future of online retailing for a number of reasons, but before we go to that let’s just stick to basics for now.
What is Data Mining?
Data mining is a process of screening the web to collect data and use it for the benefit of a business. Usually businesses focus on sources to get insights of their customers to device a better strategy, provide a better solution and stay ahead of their competitors. Similarly, it is important to keep an eye on key competitors to get a clearer picture of the overall market scenario. Therefore, data mining is anything and everything related to monitoring and collection of vital information for a business, whether it is competitor prices, customers click-through, cart abandonment rate, and so on.
Manual & Automatic Data Mining
Data is collected either manually (data reviewed on competitor’s website over a period of time, collection and analysis to make decisions) or automatically (automated process of data collection that saves a great deal of time and saves the daunting tasks for the employees). The ecommerce landscape is very unpredictable, like for instance, businesses keep updating their prices and if you are analyzing over a dozen of websites you might be missing some.
Customer Data Mining
A small storekeeper smartly uses his shelf space to place products that have greater demand with his customers; customer data works the same way for ecommerce businesses. Customer data help you make rational decisions to improve store merchandising. Data like cart abandonment rate and heat maps are vital to optimize your conversions rate. Heat maps provide information like on which section of the page users are spending most of their time, or clicking through CTA’s. Alternatively, cart abandonment rate provide insights on how you can improve your checkout screens, is the shipping cost too high to turn off users or there aren’t any recommendations, this is termed as basket analysis.
According to researches, 45% of all shoppers are more likely to make purchases at a store with personalized recommendations. You can track the content of checkout list to recommend your customer similar or related items whenever they return to your website. Also, if customers are leaving your website on the checkout screen you can use previously mined data to offer discount via email to get their attention. Retargeting ads are very effective when it comes to regaining your customers than any other marketing techniques.
Competitor Data Mining
Competitor data mining is becoming a common practice for businesses of all sizes; this includes prices, inventory assortment, customer reviews and stock levels. Price intelligence platforms analyze your competitor prices, extract reviews and inventory assortment, which helps you to optimize your inventory with products that offer greater value to your customers and gain competitive advantage.
With this information you can device a business strategy that works for you and keep you ahead of the competition. It is also important that you plan your mining frequency, as competitors are constantly changing their prices a good idea would be mine data every 15 minutes. Amazon is your biggest ecommerce competitor when it comes to data mining. The company has updated prices of most of its products over the years only because of data mining.
Therefore, there is nothing wrong in saying that data mining is the future of online retailing because it gives you enough information about your customers and competitors to design a workable business strategy to derive lucrative results.