Success Stories: Mobile Virtual Networks
TeraMatch® at Work in Mobile Virtual Networks

Situation:

Mobile virtual wireless operators are targeting specific demographic groups to extend or establish their brands. Competition is fierce in the wireless segment and margins are tight with very high churn and acquisition costs. MVNOs often concentrate more resources in sales and marketing and assets than in analytical systems.

Protocols:

A small but rapidly growing MVNO markets pre-paid calling cards, targeting the US Hispanic population. For additional fees, the card can be recharged and re-used when the original purchased allocation of minutes is depleted. The company’s early success was a result of directed marketing to Hispanics using Spanish language advertising and packaging. Points of purchase are convenience and grocery stores in predominantly Hispanic neighborhoods.

Challenge:

MVNOs are confronted with the constant problem of customer churn. They need to deal with acquiring and keeping subscribers and find an approach that does not require expensive marketing campaigns. Even though the MVNO’s cards can be used for international, local, or domestic long distance calls, the company has been losing an average 6.8 percent of its customers each month during the past half year. The traditional method of replacing those lost customers was with costly marketing efforts.

Solution:

S3 Matching Technologies used its proprietary TeraMatch® technology to provide critical business intelligence to mitigate customer attrition. Important datasets from the approximately 20,000 customers such as carrier usage, device fulfillment, and distribution sales by outlet were TeraMatched against vendor call detail records, the access database, and spreadsheets. Using S3’s Customer Acquisition and Retention Tool over the Web, the MVNO was able to graphically map anonymous subscriber calling activity. US Census data was used to enrich the information and show subscriber demographics. TeraMatch® updated call activity and subscriber information every 15 minutes. The MVNO accessed this information over the Web and did not need to install any equipment nor buy any hardware.

Benefits:

The MVNO was able to see a graphic display of calling densities married with store locations and US Census data. Previously unavailable business intelligence delivered by TeraMatch® showed that 77.3% of all calls originated in areas of very low Hispanic American populations, 100.0% of all phones were sold in areas of very high Hispanic American densities, 88.3% of calls terminated in Mexico, and 1.2% of calls were long distance. The MVNO used this information to develop a marketing pilot targeting store locations in regions with the highest calling ratios. Many of these were not in Hispanic communities. The data indicated callers were using their phone cards while they were in areas at work or away from where they lived. The MVNO changed distribution patterns of phones and cards to move them out of low-calling areas and into locations with the highest usage. Also, because customers were buying mixed-use cards but using a disproportionately high amount of minutes for international calls, the MVNO added a “Mexico Only” card. The minutes were cheaper to purchase than those on the mixed use card. Targeting the subscriber base with a product that met its needs, which were revealed in the TeraMatched data, was essential to the customer retention plan. Placing those cards in areas where the phone was being used also enhanced business prospects.

Changing business tactics based upon TeraMatch® business intelligence reduced monthly attrition rates to 3.2 percent over the next six months and increased net operating profit by 12 percent. Profit increases were directly related to reduced acquisition and retention costs resulting from the data analysis. The new marketing tactics resulted in figures that now revealed 68.5% of all calls originated in areas of very low Hispanic American densities, 89.9% of calls terminated in Mexico, and 1.0% of calls were now domestic long distance.