Sagarmatha Case Studies

Case studies > Retail Chain | Credit Card Company | Telecom

Case Study: Personalization of mobile price plans & services offers

The challenge

One of the Tier 1 Mobile Network Providers, with more than 3 Million

subscribers and with a years long reputation for innovation and out-of-the-box

marketing strategy, was seeking for additional means to increase revenues

from existing subscribers.

The solution

Using Sagarmatha’s SMART solution, the mobile network provider is getting,

twice a month, a personalized list of price plans & services offers for each

subscribers. The list includes not only the recommended individual price plans

but as well depicts which distribution channel is to be used for every offer and f

or each subscriber. Distribution channels include: text message (SMS),

multimedia message (MMS), subscriber’s data file at the call center, self

service online account manager, etc. The list constitutes the basic building

block of the provider’s periodic marketing campaigns. In order to prepare the

personalized list of price plans and service offers, the SMART system is

analyzing “tons” of raw data, including historic information, previous purchase

experience and the effectiveness of the different distribution channels as well

as individual preferences. Sagarmatha’s data mining engine uses customer

behavior modeling and prediction tools to get the most effective results.

The result after 6 months

Based on data gathered by the mobile network operator on a regular basis, the

SMART system enables to provide intelligent feedback and real life usage I

information. After 6 months of operating the personalized price plans and

service offers, the incremental revenue of the mobile provider was 1.8 Million

Euro (i.e. an average monthly increase of revenues of about 300,000 Euro).The

actual increase in revenues is even higher if taking into consideration that the

campaigns yield incremental revenues not only during the specific month when

the new price plan was operated, but for an additional period of 12 to 24

months!

Additional knowledge we can get from the analysis of usage data: the

incremental ARPU for subscribers that responded to the specific price plans

and service offers was of more than 4 Euro per month which constitutes a

substantial increase in ARPU for private subscribers.

Conclusions

Using the SMART system, the mobile network operator is able to taking care, in

a coherent manner, of large amounts of price plans and services offers, of a

variety of distribution channels and a multitude of constraints that otherwise

would not be possible to be taken into consideration. And even more important:

the data mining capabilities of the SMART system enable better matching of the

right offer to the right subscriber at the right time and via the most suitable

distribution channel.

In conclusion, SMART implementation gives mobile operators the ability

to mix and match highly relevant offers across different services available.

The individualized marketing campaigns, based on behavior modeling, (built from

usage and responsiveness data) are now, more than ever, delivering significant

improvements in ARPU, accelerating suitable price plans and service offers

adoption, increasing subscribers’ loyalty and reducing churn

Ø Retail Chain case study

Ø Credit Card Companies case study