Anonymity is probably one of the most frustrating factors for marketers servicing the mobile prepaid market. A prepaid customer purchases a SIM card in a kiosk, leaving behind no trace of identity – and as a result, unknowingly prevents any future engagement of core services.
Mobile operators find it almost impossible to maintain an ongoing relationship with these prepaid customers – and any marketer will tell you that relationship-building is an essential component for building loyalty and for identifying opportunities to increase share of wallet.
Many solution providers solve this challenge by implementing the “scattergun” approach – essentially releasing massive campaigns with the hope that some customers will respond and make a purchase. However, this method usually results in low response rates or cannibalisation and the offers are often perceived as intrusive.
At the same time, a customer who receives an SMS with an offer to top-up just after the customer has recharged the account will be annoyed and upset and from the loyalty angle, such offers do very little to contribute towards building a lasting relationship with the customer.
However, as the traditional marketing approach is based on behavioural segmentation, in the prepaid market, this is possible only by understanding the customer through explaining it as , “what you do is who you are!”
Customers should be analysed and categorised by the way they manage their prepaid accounts. A few critical parameters such as current balance, top-up amount, speed and profile of consumption should be followed, and this could also include the frequency of the customer’s top-up, which is evaluated by the following:
- a) number of days between consecutive top-ups;
b) number of days at zero balance before next top-up;
c) number of days below low-balance (after notification); and
d) before next top-up
Such data is authentic, available, and most importantly – actionable. This means that it could drive marketing plans. Once the operator mines usage data and defines the business goal per customer, it is easy to communicate personal offers at the most relevant point of time, tracking response rate and following up with offer adjustments.
To conclude, I’d like to highlight that, in order to maximise results, it is important that the marketing platform be able to automatically fulfil and execute personalised offers to a large-scale subscriber base. Success is based on the ability to run multiple micro offers in parallel in no time, track performance through a module integrating analytics and advanced statistical methods, and get receive feedback for rapid follow up.