It is always a challenge in the telecommunications industry to perfect user experience and increase profit. The traditional planning and optimization methods have dominated our working strategy for more than a decade.
Apparently, it's more and more powerless to achieve the targets by traditional methodologies. Moreover, as time goes on, the network technology and user behavior have changed dramatically. Let's have a quick view on some common phenomena that occurred in current market.
The following diagram is a sample of revenue reference from the X operator in S region:
Mobile user penetration and user behavior distribution are shown below:
From the above data statistics, we can draw a conclusion that the top ARPU users contributed 58.2% of total revenue although they were only 15.1% of total amount of users. Meanwhile, the mobile market user penetration had almost achieved 90%+, and user behavior still changed drastically with the changes of business packages.
What are the meanings of those data to the operator?
- It's a big loss for operators once the HVC (High Value Customer) churned.
- It will cost more to develop new subscribers under fierce market competition.
- Operators have to trace the changes of user behavior and fulfill the new requirements to retain customer experience and service branding.
The question now becomes finding the High Value Area (HVA) and HVC and guaranteeing their experience and increased requirements. Generally, the high value area will be generated by the aggregation of HVC. Based on this conception, ZTE provides the service solution as below:
With the leverage of benefit and experience by ABC, we can define the different property of specific grid by size 500m*500m, 1km*1km or customized. Then, we can classify the region by the 9- Rectangle-Grid as below. The high value with poor experience grid will have the higher priority to get the planning and optimization resource. The solution target is to help operators to transfer grid of CC/CB/BC … to AB/BA/AA.
With visual grid statistics and intelligent geography distribution as below, it will be easier for operators to evaluate network quality and identify valuable areas.
Based on the Value and Experience assessment result, we can define the proper strategy for each area, and regarding the high priority area (e.g. AB, AC, BC) we can provide a tailored planning and optimization solution for user experience improvement.
In summary, high value users are the most important property for the operator. By combining the customer experience and network benefit with scientific big data methodology, it will help operators to get better rewards from the market.
