Use Ecommerce Analytics for Better Conversions
What is Ecommerce Analytics?
Ecommerce analytics is the process of accumulating data from all of the areas that have an impact on your store. You should then use this data so that you can comprehend shifts in customer behavior and online shopping trends.
Ultimately, you can make more intelligent decisions by basing them on data, which should result in more online sales being made.
Ecommerce analytics can include a wide range of metrics relating to the full customer journey. Such as discovery, acquisition, conversion, retention and advocacy.
Why do You Need eCommerce Analytics?
Having some sort of analytics tool is pretty much indispensable to having a successful e-commerce business. Integrating and using analytics tools on your eCommerce website is a major key to success. And will help you score a huge advantage over your marketing competitors. Not paying attention to the minute analysis means passing on vital information. That can help you to stand out from your competitors in the eCommerce world.
Without analytics tools, it’s impossible to really understand the various factors that drive the customers to make purchases, how users get to your marketing site, how they behave on it, which products they are interested in, wherein the sales funnel you lose potential buyers and generally how to optimize that will lead to more sales.
Ways to Use eCommerce Analytics to Boost Conversion Rates
Product Page Optimization
The product page is where all the action happens. It’s where the customer can see your product, read up about it and peruse other customers’ reviews. Do a product page well, and you’ll see your sales take off. Do it poorly and sales will struggle to get off the ground. But if your product pages aren’t performing well, how do you figure out what the problem is and how to fix it?
Product page optimization will collect the data gathered by customer actions and then analyze it to observe deeper insights. Sales data analysis assists you to determine where the problem lies in getting a customer to go from browsing to buying.
Predictive Analytics
One key to better engaging your customers and responding to their needs is through predictive analytics. Analysis of the data you collect can help you determine what customers expect. Take recommendation engines for example. Based on what customers have looked at and purchased in the past, it can be determined what a specific customer would likely buy in the future. Think of it like a hyper-personalized marketing approach. Predictive analytics makes sure that what you recommend to customers is more likely to work.
Choosing the Best Match
Sometimes selecting a single approach isn’t possible since customers can vary greatly in their behavior. That’s when utilizing best match algorithms can be extremely useful. This type of algorithm tests out two different versions of something — a landing page, call to action button, etc.. And recording the digital data on which is more effective at getting the desired reaction from a customer.
Based on this information, you can get a better picture of what will lead to more conversions. Some analytical capabilities can change out the choices depending on times of the year, ensuring you are getting an accurate picture of what customers are doing.
Getting the Data
eCommerce data analytics needs the extraction of the data in the first place. These data extraction solutions also give you the ability to monitor customer sentiment, helping you understand how customers are responding to your product. As well as your competitors’ products. Data extraction from websites makes implementing strategies of eCommerce much easier.