August 11th, 2008

How Do We Impact Prepaid Behavior?

By Nir Hakarmeli - Director of Consumer Marketing

cube41.gifIn our first post on impacting prepaid behavior we demonstrated how we increased usage within a “mid–ARPU” prepaid segment, using a multi-stage marketing program. What is the strategic impact we achieved? First let us take a look at the before and after status of each phenomenon and then we will explain how we did it.

As we can see in the below graph showing last call date distribution (Phenomenon 1) a subscriber that didn’t talk for 30 days is considered dormant. As a result of our targeted marketing program we managed to reduce the time frame from the last call made (a shift from the right to the left on the graph), where subscribers actually remained active over time. This is based on a three month period that began in January 2008, and three months later we checked how many were still active. So for example, subscribers from day 30 to day 60 in the graph made their last call in March, and subscribers from 61 to 90 made their last call in February. What we managed to do is bring about a shift where more subscribers remained active over time or to put it another way – kept talking!

phenomenon1new.gif

In Phenomenon 2 we have an indication of the average time between top ups. As we can see 11% of the segment did a second top up in less than a week. And 48% (almost half!) recharged after 2 weeks. The goal was to shorten the time between top ups and the example shows how the average time between recharges shortened by 4 days (!) (a shift to the left on the graph). Time between recharges was reduced from 16 to 12 days, making the subscribers much more active.

phenomenon2.gif
In Phenomenon 3 we can review the time between having a zero balance and the subscriber’s next top up - 30% recharged during the first 2 days after reaching a zero balance, shortening the time that subscribers are in zero balance by almost 50%. This translates into millions of dollars in operator revenues. As you can see in the diagram, the average time of silence is 3.5 days and we managed to shorten that by almost half to 1.9 days.

phenomenon3new.gif

In the first phenomenon we managed to bring about a shift where users remained more active, in the second we shortened the time between top ups, and in the third we shortened the time between subscribers’ having a zero balance and their next recharge. It’s not magic. We have a systematic way of achieving these defined goals and you can read all about it in the next post coming up soon.




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