Big data and data analytics has revolutionized the way businesses work. Each person creates 1.7 MB of data per second. It sums to some quintillion bytes of data produced every single day. We always have used data in some capacity to optimize our business strategies. Fast-food chains like McDonald's and KFC decided to offer various vegetarian options in their Indian stores based on the data they gathered about the religious and cultural eating habits of the Indian population.
Data helps a business identify the best markets to explore, the right products to launch, create the appropriate communication for its audience and strategize its operation for maximum impact.
The implication is endless, possibilities boundless with what you can do with data. Only if you know how to read it and make sense out of it. if by any chance you are not making use of analytics, then it’s high time you realize that you have missed so much.
In this article, we’ll explore how you can use data analytics to boost conversions and create optimum strategies for your online store. Without further ado, let’s dive in!
Identify Paint Points in Purchase Cycle
Whenever a customer lands on your website, they go through a certain purchase journey for a successful conversion. This is also called funneling. The customer goes from a broad spectrum of tasks to more specific call-to-action before finally making their purchase decision.
However, many customers drop out in the middle of the cycle for various reasons. These places that customers dropped off are called pain points in the purchase cycle. Analytics can help you identify these pain points in the cycle and determine the cause of these pain points. This makes it a piece of cake for you to either remove or amend these pain points so that customers can smoothly funnel towards the buying decision.
You can use tools like Google Analytics to identify the touch points where the customer left of the journey. The supporting data can help determine why did it trigger the customer to leave and how you can improve upon it.
Have you wondered if you already knew what your customer wanted? Or perhaps if you knew what will be the most selling product from your store this season? Well, with data analysis it is possible to know all that. It is called predictive analysis. By analyzing your previous sales data, customer responses, engagement, reviews, and demand you can predict a lot of things that could help you stay prepared.
Have you seen amazon’s recommended products or Netflix’s recommendation engine that recommends movies and tv shows? Well, these are excellent examples of predictive analysis. Based on previous user behavior, activities and touchpoints, they create a series of predictions that they recommend to their users. This is more like a hyper-personalized approach by predicting user behavior, likes, and needs.
By implementing predictive analysis on your gathered data, you can arrive at the optimum price to sell at in the coming future considering the predictable market situation. You can also predict which products can sell more than others and what time of the year is great for event-specific engagements.
Various eCommerce platforms offer a feature called cart analysis. It allows you to analyze the cart of previous customers to look for patterns, buying behaviors, and trends. You can find out how many customers are abandoning their carts and at what point, for what reasons. This can help you reduce the abandonment rate and boost conversions.
You can use Google Analytics to analyze your cart data by inserting your eCommerce data into Google Analytics eCommerce tracking code. If you observe a pattern that customer that buys Product A also buys Product B along, you can club these two products for increased sales.
Most of your customers may visit your website through a social media platform rather than an organic search. This redirect from social media channels to your website can be optimized and used to its maximum capacity.
By analyzing which platform sends you the most traffic, you can validate the campaign you ran, what kind of response you get per channel. You can also analyze the data to understand what kind of engagement is working for what platform. It is best to club your own analysis with Google’s social report to get a more comprehensive picture.
The channels that send you the most traffic can be optimized for better targeted ads, improved engagement, and service.
Content is an important tool in engaging the audience and creating a meaningful community around your brand. Through your content, you can influence opinions and persuade your audience to successfully convert.
How does analytics help with content? Well, analytics can determine what your customers are looking for on the internet. You can analyze their search queries that lead to your website or their most searched keyword. This tells you what they are really looking for. You can create content catering to what they want.
A simple analysis can tell you that if your blogs are getting more eyes or the videos. Depending on what’s working for you, do a bit more of that. You can see what kind of content engages your audience more and increases the visit duration.
Placing The CTA
Content analysis can help you go a step further in optimization. Have you wondered why certain articles do well than others in terms of conversions? There is a certain psychology behind it. However, it got uncovered through analysis of the data, no wonder. Articles that are too short make the visitors jump to other pages for info and articles that are too long also make visitors bounce to more concise sources of info.
Thus, optimizing your content for length is important because in both the above cases the visitors missed the CTA. Your call-to-action should be placed at a point in the article where most readers reach and are also the maximum point of clarity and interest.
Data helps you identify what is the appropriate length for your blogs as it can vary depending upon your specific industry and audience.
There are endless ways in which you can leverage analytics to optimize your eCommerce store for conversions and sales. Analytics are powerful and can quickly become too complex. You can start with the basic and medium-level analytic practices that we have discussed and slowly graduate towards more complex data analytic practices.
These simple to implement practices are inseparable from eCommerce websites today. We recommend that you do make use of analytics to the hilt. We hope our article helps you get clarity on how you can use analytics to optimize your conversions.