For decades, telecom operators have trusted persona-based marketing in crafting pricing plans, designing advertisements, and identifying the potential for new or re-packaged products. The persona-based approach has involved dividing current and potential customers into specific demographic groups based on marketers’ perceptions.
In today’s data driven world, trying to put people into generic groups is no longer necessary. It’s time for carriers to scrap persona-based marketing and embrace big data technology: capturing, storing and processing the network, billing and usage data at a granular level for each subscriber. Data, including customer interactions, usage, location, applications, devices, browsing history, call patterns, etc. makes it possible for carriers to move away from the use of broader archetypes (such as explorer, adopter, outlaw) to creating individual marketing plans based on a “segment-of-one” concept. This involves treating every user as an individual with specific behaviors, interest areas and buying patterns, and then developing individualized marketing messages for use on the most effective channels based on that individual’s specific needs, context and “intent”.
Even changing scenarios can be addressed by segment-of-one marketing. For example, when a person travels abroad, his or her use of telecom services is very different than when at home using a local service. In fact, an iPhone user in Tanzania would use telecom services differently in France than an Android user visiting from the same country. Even the length of a trip affects service usage. Combining a subscriber’s domestic profile with roaming data enables carriers to understand an individual’s transient behavior in a way that persona-based marketing never could.
Carriers using a segment-of-one approach to marketing can take advantage of new marketing scenarios. For example, if a customer is watching a video on a 3G connection in a moving car and experiences video interruptions due to buffering, the user is likely to get frustrated and blame it on the service provider. With personalized marketing, this is an opportunity to target the user with an offer of a 60-minute 4G pass to support better video performance and complete the viewing of the program. Capturing such marketing moments is only possible with complete understanding of each individual customer – that their device can support 4G, while they have only purchased 3G service, and so there are options available to take advantage of which can improve their video experience. Not only has the carrier in this situation made steps to ensure customer retention, but it has created an up-sell opportunity in the process.
Carriers are in the unique position of being able to take this a step further and develop an influencer-based marketing approach. This predicts how a subscriber can influence other individuals, or is influenced by others, and is derived from Call Data Records (CDRs) which includes, for example, who is calling whom, how often a call takes place between two people, and average duration. This helps build a social graph to leverage influence relationships to amplify marketing messages to individuals through recommendations from trusted influencers, pretty much like “word of mouth” marketing that has a higher success rate. In addition, carriers can align such social influence graphs with individual interest graphs constructed using browsing data, and service purchases. The trusted messages can now be further refined for specific individuals using collaborative filtering to determine that if a subscriber “A” likes this they will also like that. As an example, the interest graph will tell us that young females who use iPhones are more likely to buy music service like Pandora, while the social influence graph will help us target promotions to those individuals through their influencers. Combined, these graphs constitute a very powerful marketing tool for carriers, and they are equally valuable to third parties. Carriers have realized that their customer data is their richest and most valuable asset and are now beginning to develop data monetization revenue streams.
The rapid adoption by carriers of data science and analytics based marketing techniques, that made digital service providers like Amazon, Netflix and Spotify successful, has resulted in the scrapping of age-old persona-based marketing in favor of effective, real-time, data-driven marketing.