Customer acquisition is not difficult, but regaining lost customers is costly and nearly impossible. Therefore, it is extremely important to retain your customers and to establish long-term value-oriented relationships with our customers by understanding their journey from the first relationship with the company and increasing their journey comfort and have a better experience by empathizing.
For this purpose, Customer Journey Map becomes critical in understanding our company from the eyes of our customers and developing customer-oriented strategies based on this awareness.
There are some key points in designing an effective user journey map;
- Choosing the right person,
- Evaluating the consumption/purchasing process,
- Identify touchpoints,
- Interpreting actions, feelings and thoughts, addressing opportunities and obstacles.
The most critical point of these steps is analyzing customers' actions, feelings and thoughts, and even handling opportunities and obstacles. This is the step of creating personas. Customers whose behavior, characteristics and demographics differ from each other will not be representative of the general audience. In addition, it will be extremely complex to deal with each customer's journey through different maps. Therefore, the concept of persona gains importance. Just at this point, customer groups and rule-based segments that thought to represent these groups can be created with a common approach. As an output of this, improvements can be made both in customer experience points and what kind of approach will be shown for which persona and segment in marketing strategies can be discussed.
• The persona.csv dataset contains the prices of the products sold by an international game company and some demographic information of the users who buy these products.
• The data set consists of records created in each sales transaction. This means that the table is not deduplicated. In other words, a user with certain demographic characteristics may have made more than one purchase.
• A game company using some features of its customers wants to create level-based new customer definitions (personas) and to determine the segments according to these new customer definitions. Thus, it will be possible to estimate how much profit can be made per a customer in any segment.
• For example, It is desired to determine how much profit can be generated from a 25-year-old male user from Turkey who is an IOS user.
• PRICE – Transaction Amount.
• SOURCE – The type of device the customer is connecting to (IOS/Android).
• SEX – Gender of the customer.
• COUNTRY – Country of the customer.
• AGE – Age of the customer.