With the advent of Big data, mobile operators are moving more and more towards a segment-of-one. This makes it necessary for operators to know who the real customer is and what is his/her product portfolio. It is crucial for mobile operators to understand the household which their customer belongs to. Mobile operators currently look at basic attributes with a certain defined frequency and apply demographic information to predict households. The challenges with this approach are multi-folds. Since this is a simplistic approach, the accuracy of the prediction is less than 30% on average. Moreover, as the market characteristics changes, the applied thresholds would also need to change which makes it difficult to automate the process. Due to the low accuracy of the prediction, the campaign take-up focusing on households tend to be much lower thereby impacting product penetration and top-line revenue. Single Household View is a pre-built solution by Lynx Analytics that addresses this problem and identifies the households within your customer base using your own CDR, location and device data. The approach relies on calling circle and the device attached to the SIM(s) and colocation of multiple SIM(s) has an accuracy of ~70%.

The Outcome

With Lynx Single Household View solution, deployed in one of Malaysia’s leading telecommunications providers, they were able to identify a single household view within their customer base.

Using the SHV solution, the CSP was able to identify 19% households with at least 2 on-net members as shown in the figure below.






Lynx SCV solution allowed the CSP to:

  • Create promotional campaigns to increase the subscription rate through referrals
  • Decrease churn rates among households
  • Delivered a better understanding of their customers’ preferences.