From Data to Dollars: How to Analyze and Optimize Your E-commerce Performance

 

Are you running an e-commerce business but do not know why your business does not generate maximum revenue? Are you enthusiastically starting an e-commerce business, but after some time, you are going to sell your business? To generate a decent amount of profit, you need to consider the following factors to improve the profitability of your business.

1. First, you should collect your data, like visitors’ statistics, bounce rate, and page dwell time.
2. Second, collect the data about orders, sales, and total sales value.
3. Third, collect the data about users and their purchase history.
4. Fifth, collect data about your advertising campaigns and their results.

The above five factors are enough to learn about your progress. Our main objective is to collect this data to clarify what we want to achieve.

For example:

1. We want to improve our conversion rate. And want to know what products are most attractive for customers.
2. We want to learn about our ads and want to analyze the performance of our campaigns.
3. We want to learn about our inventory, what are the hot products, and what are the slow products.

After setting our main objective to perform data analysis, we first select our main KPI.

1. We want to know how users visit our website and what product they are interested in. In this respect, we want to learn about the search engine’s ranking, social media effectiveness, and other channels.
2. We are also interested in what links the users enter our websites and complete the purchase. What content promotes our product to customers?
3. How many orders do the customers place on our website, and what are the reasons they select our website for particular product purchasing?
4. We also need to learn what products are selling well and what products have slow-moving status. These factors can narrow down our analysis, and we reach our main objective.

The KPI is not enough to correct our direction; we also need other methods to perform our analysis.

1. Trends: We need to learn about trends and their impact on our sales. For example, how do different periods impact sales, and what are the demand and seasonal changes?
2. Cohort: This method is used to learn about the behavior of specific user groups. For example, why users register at our website and how they purchase the products from our website. Basically, we want to learn about user behavior and how we optimize our sales cycle.
3. Funnel: It is also necessary to learn how users enter the website to complete a purchase. Why does a customer abandon their shopping cart?
4. A/B testing: We also want to know which website pages increase conversion rates. How does the selling process progress on our website?

In summary, data analysis for an e-commerce business is not difficult but requires constant effort. By learning customer data and their purchase habits, you can improve your selling process and improve the profitability of your website.