How to conduct a customer analysis, from an e-commerce perspective

An online store is completely dependent on understanding its customers in order to succeed. A smart way to increase that understanding is by conducting a customer analysis. In this post, we take a closer look at what it means - and what you can use the finds for.

1. Data Collection

The starting point, of course, is to collect relevant data about customers. For example, demographic data, purchase statistics, website behaviour and customer preferences, many people settle for standard reports that they can easily access. However, often, the content of these reports doesn't reflect your actual business needs. They can even be counterproductive by exposing you to a host of irrelevant metrics that distract you from what you should be keeping track of.

Think about what is actually important for you to find out. Perhaps the goals set for the online store are a good starting point for thinking? There are many good channels to collect data from - feel free to use several of them. CRM/order systems and web analytics tools, for example, are two good sources to start with. Don't be afraid to send out a survey to dig deeper into something or pull numbers from a database. The more you know – the better you can understand customers. Just be mindful of obtaining the consents you need!

Why:

By collecting data, you get a detailed picture of who your customers are – and how you can adapt marketing, offers and user experience to meet their needs more precisely.

2. Segmentation

After collecting data, you should segment the customers. Segmentation is an art and a science for which there is no clear recipe. What you're looking for is to divide customers into different groups based on common characteristics or patterns of behavior. It can be something as simple as age groups, but also more complex buying patterns or preferences. Just remember: the end result should be that you differentiate communication to these groups. You should keep this in mind when looking for meaningful divisions, and here too, the goals of the online store are a good place to start: For example, if you want to increase loyalty, it is natural to dig into what separates the loyal customers from the fleeting ones.

Why:

Segmentation gives the online store the opportunity to customize marketing, customer tracking, on-page experience, and much more. It's segmentation that allows us to move from insight to action and actually create value from our data, and for the customer, the result will be - hopefully - a more personalized and relevant experience.

3. Buying behavior analysis

A buying behavior analysis involves examining how customers behave before, during, and after a purchase in your online shop. The goal is to understand what drives their behavior. Are we able to identify trends, patterns or preferences? An example might be researching the checkout process. Are there friction points in that process where customers drop out? Maybe it's something about the payment options, shipping options or time-consuming filling in that is causing problems.

A buyer behavior analysis can also be so much more - it can be about which products sell the most, what triggers purchases, or which campaigns and offers are most effective.

Why:

Results from this analysis can be used to:

• Optimize the marketing strategy (maybe you need to work on customers' perception of the brand?)
• Identify sales promotions (maybe you're missing out on potential revenue from paid search?)
• Customize the assortment (maybe more accessory products can increase the average order size?)

If you succeed in this, you will see increased sales, better competitiveness and perhaps even higher customer satisfaction.

4. Personalization

Taking customer analytics a step further can help you offer personalized experiences and recommendations to customers. This may mean that one group of customers sees a different type of communication and value proposition on the website than others – or that customers receive recommendations based on previous purchases, personal preferences or other customers' behavior.

Here you can start with a manual customer analysis and manual recommendations towards groups of customers. The communication itself can take place via e-mail, for example. However, if you really want to reap the rewards, you should use a system that allows you to automate the process for each individual visitor.

If you use Optimizely, it may be worth taking a look at Optimizely Product Recommendations which personalises product recommendations to visitors or Optimizely Data Platform which allows you to understand and segment users. Voyado also delivers a great solution for personalization that can be integrated.

Why:

Personalization creates a unique experience for customers, increases customer loyalty and the likelihood of repeat purchases. It can also make customers feel seen and appreciated, which can contribute to positive feedback and a strengthened brand.

Summary

Conducting a thorough customer analysis provides valuable insights that can be used to strengthen the entire business. If you succeed in exploiting the potential here, you can offer a better experience for customers, increase sales and achieve competitive advantages in a digital world characterized by increasingly fierce competition.

Should you need help or want a professional review, do not hesitate to talk to us at Epinova!

This blog post is taken from our Norwegian sister agency and written by Torsten Torblå, Senior Advisor in Data Analytics.