Today, B-end products are no longer an era that only needs functions, and they are also moving towards the refinement of C-end products. Data embedding is an objective means to verify conjectures and discover problems, and it is also instructive in bulk sms service product direction. significance. So, how should B-end products do a good job of data embedding? The significance of data buried point for B-end products Data embedding is very common in C-end products to monitor user behavior. The surface layer can understand products and activities, optimize functions and interactive experience; the deep layer can carry out user tags, channel conversion analysis, and personalized bulk sms service recommendations. For example, Taobao Double 11 event, product managers and operations will want to know:
How many people participated in the event? When is the traffic peak? What is the conversion rate of each link from browsing to placing an order? ... But for B-end products, the quality of the function is not directly related to the number of clicks, but depends bulk sms service on whether the user has this business demand , so the data burying point of B-end products is of little significance? Not too! Not too! B-end products are no longer an era that only needs functions, and they are also moving towards the refinement of C-end products. Data embedding is an objective means to verify conjectures and discover problems, and it has guiding significance in the direction of products. 1. Optimize bulk sms service experience and improve efficiency The optimization of C-end products may be more to increase exposure, increase page views and transaction volume.
The task of B-end products is even more arduous, and it is necessary to improve the efficiency of users. We all know that B-end users have very high bulk sms service requirements for efficiency. For example, at the front desk of a restaurant, you must click one more step to confirm whether there are coupons every time you collect money, and this restaurant does not have any discounts. Then this action will waste 1 second of the cashier's time each time, assuming 300 customers a day, it will waste 5 minutes. Of course, this is just a waste of one point. If there are other points of waste, the bulk sms service accumulated time is still very considerable. By burying points, we may find that in an operation path, the usage rate of some pages is obviously low, so we can consider simplifying the steps;