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Situation
KPN offers telecommunication services to both consumers and businesses. Incorporated in 1989, KPN's core business comprises telephony and data services through its fixed network in the Netherlands; mobile telecom services in Germany, the Netherlands, and Belgium; and data services in Western Europe. KPN is market leader in all major segments of the Dutch telecom market. Through E–Plus in Germany and BASE in Belgium, KPN has a number three position in the mobile markets of these countries.
As of March 2005, KPN had 7.4 million fixed–line subscribers and 1.7 million Internet users in the Netherlands, as well as 17.7 million mobile customers in Germany, the Netherlands, and Belgium. It employed more than 30,000 individuals. KPN's shares are listed on Euronext Amsterdam and the stock exchanges of New York, London, and Frankfurt.
Challenge
The telecom market is a very competitive market. Whereas a number of years ago KPN's emphasis was mainly on finding new customers to increase its market share, the current emphasis is on keeping existing customers. The average churn percentage in the mobile telecom market is approximately 20–25 percent. KPN Mobile believes predicting customer behavior and needs is an important method to further improve the effectiveness of its direct marketing campaigns.
KPN Mobile conducts approximately 125 direct marketing campaigns every year, in both the consumer and business markets. A distinction is made between event–driven campaigns that are repeated periodically, and once–only actions. KPN uses all of its available channels for direct marketing (in terms of numbers a year):
- Short Message Service (SMS)
- Direct mail by post
- I–mail (customers with an I–mail address on their I–mode)
- E–mail
- Telemarketing
- Multimedia Messaging Service (MMS)
Many campaigns have a multi–channel character when an e–channel (e–mail) or m–channel (SMS, MMS, and I–mail) is combined with a more traditional direct marketing channel such as direct mail or telemarketing. The e– and m–channels already comprise half of the outbound customer contacts.
In the past at KPN Mobile marketing, campaign models were usually built around experience figures and the intuition of marketeers. The direct marketing process was not efficient, though, because there were too many links (parties involved) in the process. The marketeer launched a campaign and made a rough estimate of the target group. Together with the campaign manager and the marketing analyst, an accurate target group was defined. In this process, the assistance of a list manager was required for the effective selection of the correct target group, a complicated and time–consuming task. SPSS' PredictiveMarketing software considerably improved both the quality and the speed of the process.
To contact more customers, increase the cross–sell ratio, and bring down the churn percentage, and at the same time considerably improve the marketing process, KPN Mobile specified the following project objectives:
- Improve efficiency of the direct marketing process by 15 percent. Considerable reduction of the set–up and execution time of campaigns.
- Increase effectiveness of the direct marketing process by 10 percent. The result of the actions needed to be 10 percent higher than it was currently.
Solution
KPN Mobile's starting point was the creation of a more efficient process to build models. Using predictive analytical software, the target group could be defined much more quickly and more efficiently after consultation with the marketeer and the campaign manager, resulting in a substantial reduction of the execution time.
After the evaluation of several potential solutions, KPN Mobile purchased SPSS' PredictiveMarketing software for campaign management and optimization. The main selection criteria were software performance, user friendliness, functionality, and management. Due to the size of its database, KPN Mobile attached great importance to performance in particular.
Implementation
KPN Mobile has divided its database in three segments: business market, consumer market post–paid, and consumer market prepaid. The implementation project was aimed at creating an analytical environment for the post–paid and prepaid campaigns. Implementation was completed by SPSS. After only six months, the first campaigns with PredictiveMarketing were carried out. Since that time, the use of PredictiveMarketing has expanded to 70 to 80 percent of all campaigns in the consumer market.
KPN Mobile also uses its SPSS solution for the telemarketing and direct mail channels, where the cost of each customer contact is high. And the software is used for the development and management of customer segmentations. Accurate predictions are then made of the expected customer response, so that marketing campaigns with the right message can be aimed at the correct target group.
As part of KPN Mobile's customer value management strategy, the organization intends to keep valuable customers and to develop new customers. By using SPSS to predict which customers might purchase more products, the profitability of customers can be increased. In addition, SPSS' PredictiveMarketing solution allows KPN Mobile to easily identify groups with a high churn risk in time to react proactively and take steps to retain them.
Result
The use of SPSS' predictive analytics software has, in addition to accelerating the marketing process, resulted in substantial cost reductions for a number of campaigns, which has led to an increase in profitability per customer. The first year estimate for the reduction in campaign costs as a result of the SPSS solution is in excess of one million euros for the top three campaigns in which telemarketing was used.
The campaign efficiency improvement goal was set at 15 percent. Based on the measurement of the turnaround time of campaigns carried out both with and without PredictiveMarketing, the campaigns conducted with PredictiveMarketing cut the time required to carry out campaign selections in half. Whereas the execution of a target group selection used to take a day, using PredictiveMarketing this has been reduced to just a couple of hours and, in some cases, to the press of a button for the lifecycle models.
The effectiveness goal—an improvement of 10 percent—was achieved for a number of important campaigns where the expensive telemarketing channel was used. By using less expensive channels, 10 percent fewer costs were incurred and the result was the same.
Using the same marketing budget, dramatically improved results have been achieved.
An example of a recent successful KPN Mobile campaign was a telemarketing action which aimed at converting prepaid customers to a post–paid subscription. Through telemarketing, 250,000 prepaid customers were called and asked whether they wanted to switch. Without SPSS' PredictiveMarketing, this campaign would have resulted in only a four percent conversion rate. Thanks to the SPSS software, the result was as much as 12 to 15 percent, which translated into a clear conversion increase.
We are enthusiastic about the results so far. The software has far exceeded our expectations. SPSS enables us to quickly and effectively identify likely groups in our base of six million mobile customers for marketing actions aimed at value retention and value creation. We can quickly translate this valuable customer knowledge to segment specific actions and get a much higher efficiency out of our marketing investments.
— Leen Molendijk
Implementation Manager, Predictive Marketing
KPN Mobile
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