In the context of the social era for everyone, the relationship between enterprises and customers has changed. In the era of big data, customers will leave a large number of behavioral clues when they are active on social media. Analyzing and digging out customer needs and opinions requires an analysis and management system that adapts to this trend, and the SCRM system was born.
User behavior monitoring includes the collection of user attributes and behavior data, as well as the tracking and monitoring of user interaction trajectories. In a complete marketing activity, there are four main steps for user behavior monitoring: tracking customer behavior-marking user behavior-summarizing user behavior- Analyze user behavior.
01. Track user behavior
Some users may be in our user group, but never participate in promotional activities;
Every user's behavior has its reason, is he not interested in our content? Did the user find other products that could replace us? Is the lack of participation in marketing activities due to cumbersome processes or insufficient rewards? Only by tracking the trajectory of user behavior throughout the process can we discover the reasons behind it, better optimize marketing activities, and increase user purchase rates.
BestChat can automatically track customer browsing behaviors and form user browsing trajectories, including behavior time, browsing time, behavior sequence, etc., capture the behavior of customers opening content multiple times, and help sales to better understand customer needs and customer purchase cycle information. Customers interact to increase user activity and enhance user stickiness.
02. mark user behavior
After tracking the user's browsing trajectory, users can be stratified according to the user's behavior trajectory and consumption characteristics, and exclusive marketing plans can be formulated for different user groups to maximize the value of users.
The most common method of layering is user tags. At present, the main user tags include physiological characteristics (such as gender, age, occupation, etc.), interest preferences (such as dancing, digital products, etc.), and brand level (such as frequency of use, membership level, Consumption ability, etc.), life behaviors (such as shopping habits, reading habits, etc.), companies can tailor user label classification according to their own needs to help companies efficiently and flexibly manage user classification.
BestChat can intelligently label users, conduct in-depth learning on collected user data, record various interactions between corporate sales and customers in the marketing and sales process, help sales grasp customer user portraits, and accurately analyze user purchase intentions. It recommends suitable products and follows up with interested customers, which facilitates customer management and improves corporate marketing efficiency.
03. Summarize and analyze user behavior
At this stage, we already know our own data well. By extracting the user's basic information from the existing data, using user tags to specify the user's image, building a 360-degree user portrait, and realizing the operation of thousands of people.
BestChat automatically associates user follow-up records, contact history, browser tracking, orders, and other data with customers to improve user portraits. Sales can design different types of customer cultivation, conversion, repurchase, and additional purchase processes based on user portraits and data, customer stages, customer tags, and other behaviors, and start a series of customer care cultivation processes to achieve accurate customer conversion.
In addition to providing insight into consumer needs and providing more targeted services, sales staff can also collect customer concerns, sort out and analyze them, and provide timely feedback and processing, thereby enhancing customer satisfaction.
User behavior data is of vital importance to enterprises. It can not only help enterprises effectively connect users, but also provide insights into user needs. Through continuous iterative verification of user portraits, discover the most real needs of users, solve user pain points, and improve marketing effects. It can even leverage the value of users' social groups, keep new users from breaking, and bring growth to the enterprise.