Customer Journey Analysis with Machine Learning

Customer Journey Analysis with Machine Learning
Ebru Sevik 27.05.2020
Customer Journey For Insurance B2Metric AI Customer Journey Analytics Customer Journey Map Machine Learning Customer Churn Prediction

Customer Journey Analysis is an approach to help a company see its products and services from a customer's perspective. Before the analysis, what the customer journey is and its importance should be examined. Do you know what is it and why you need it?

What is Customer Journey?

Customer journey cites to the path followed through the points of contact of your customers and potential customers before making a purchase action. Customer Journeys explains the path to successive interactions a customer has with a product, service, and company. A customer journey is an observation way about understanding your users, how they behave while they visit your website, and what you can do to improve their trip. They keep coming because of this observation.

Customer Journey Analytics

Marketing is the main area of ​​use for customer analysis. There have been major changes in customer behavior in recent years. Customers usually do not decide to buy a product at the first interaction now years. They often examine different brands several times for a product or service before making a decision. Continuously developing mobile technologies enabled customers to interact with organizations from many different channels. On the Internet, the points of contact of potential customers for a product or service are hard can be watched from multiple channels. With the customer journey, you can better analyze, make sense of these changes in customers' behaviors, and use them to create your marketing strategies. Because customer journey proceeds at these touchpoints.

Why Do You Need Customer Journey Analytics As a Business Owner?

Customer journey analysis allows you to identify your customer touchpoints. Today, companies should think like their customers; customer journey analysis makes this easy. Starting to think like your customers and evaluating your products/services like them will increase your sales. Analyzing customer journeys reveal inconsistencies. This allows us to detect discrepancies and corrects. Analysis of journeys and acting on what is learned can reduce the effort needed of customers, rising their satisfaction and decreasing the number of abandoned journeys. Analyzing a customer's travel trends helps service providers find better ways. Analyzing journeys may push a dialog between departments to develop entire effectiveness, overcoming departmental sub-optimization. By creating and analyzing multiple customer journeys, you can provide test scenarios for a multi-channel solution. Besides, these analyzes and inferences can also be used for your other customers. Thus, your efficiency increases while your operation cost decreases.

Customer Journey

Benefits of Customer Journey Mapping

With customer journey analysis, you can easily see the points where your customers interact with your business Customer journey analysis helps you in your sales process by providing you with an outside perspective. Customer journey analysis helps you to focus your business on customer needs It allows you to compare targeted and acquired customer experiences.

How Machine Learning Improves Customer Analysis?

In the 20th century, with the business now turning around the customer, companies move away from traditional business models and turn to customer-oriented and personalized business models. The customer experience has become the priority way of companies to set themselves apart from their competitors. Customer journey analysis is one of the biggest providers of customer-oriented personalization. Making customer journey analysis with machine learning allows you to analyze your customers and create your business plans much more easily than other methods. With machine learning and artificial intelligence algorithms, you can easily analyze your customer data and draw meaningful results from them. Such as customer churn prediction. In line with these results, you can create a business plan that makes a difference in many business areas, especially marketing and sales areas.

Customer Journey

B2Metric Machine Learning Studio (Register & Start Free Trial Now!) uses different types of machine learning algorithms in autoML pipeline to provide the best solution for you. Each algorithm that B2Metric provides for you can be adjusted to get the most suitable model and provides you the best customer experience. You can see the customer churn segmentation screen created with B2Metric Machine Learning Studio (BMS) above.


Customer Journey

How Can You Analyse a Customer Journey Map?

Journey maps are infographic visualizations to understand how a customer is working towards a goal over time. There are several ways for analyze customer journey maps.

1) Identify points where customer expectations are not met. When users interact, if this interaction does not meet expectations, pain points are seen on the journey. In these cases, it is necessary to think from a user perspective. So you can understand which interactions did not meet the old expectations and experiences.

2) Identify any unnecessary touchpoints. Whether to take steps that can be eliminated to facilitate the overall experience should be examined. You should look for ways to reduce the cost of interaction.

3) Look for low points. You should see where the lowest points of the journey come from. Determine which low points you should prioritize.

4) Bestow time periods for the main stages of the journey on your travel map. Consider how long it took users to reach the sub-steps and whether these elapsed times were appropriate.

5) Look for moments of truth. Some points are based on some other points on the journey. These points are very important for the journey. If these moments go well, they can save the journey. You should analyze these points well and make sure you pay attention to them.

6) Identify the points that expectations meet. Look where the customer journeys are highest. These points are usually interactions that users are happy with. You can use similar experiences in different places. Thus, experiences will increased by you.

7) Determine high-friction channel transitions. There are many trips between the channels. The journey is disturbed when users change channels and transition should be facilitated.