Digital channels have transformed the mindsets of customers. They are now dynamic, context-sensitive and impulsive when it comes to making purchases and reacting to marketing offers. Hence for Communication Service Providers (CSPs), one-size-fits-all kind of marketing techniques and competitive pricing can no longer give them the competitive edge in the market. The focus needs to shift from macro-marketing to nano-marketing.
Challenges in nano-marketing
Nano-marketing is based on the premise that each subscriber is unique with differentiated tastes and preferences, and campaigns must be carefully tailored keeping these specific needs in mind. CSPs have millions of subscribers, and they generate billions of transaction each day. Making sense of such an enormous amount of data pertaining to subscribers’ dynamically changing profile and actions to understand them at a personal level is both a challenge and an opportunity.
To add to the complexity in terms of volume, the data resides in varied sources in structured, unstructured and semi-structured forms and in known and unknown formats. Big Data analytics holds the promise here. It potentially allows CSPs to construct a holistic persona and mind map of each subscriber reflecting his demographic profile, psychographic interests, socio-economic behavior and so on.
Constructing subscriber mind map is the key to nano-marketing
The first step in nano-marketing is to construct a mind map of each subscriber that can bring out explicit and implicit demographic, behavioral and other attributes including:
- Persona reflecting the psychographic interests (for example, a music lover or sports fan)
- Usage models to identify his mobile usage patterns, frequency of usage and typical contexts of usage
- Social models for understanding his social behavior and identifying influencers like friends circle, communities, etc.
- Spending patterns to understand his buying preferences and purchasing power
- Location models to trace whether he is a commuter or international traveller or a frequent weekend tourist
- Predictive models to state his likely needs and behavior for a futuristic time frame or context, similarly his preferred products, channels, etc.
Role of integrated analytics in nano-marketing
To construct such a holistic mind map for each subscriber you need to deploy multiple analytical models. Descriptive and exploratory analytics can help in understanding his demographic profile and spending in a deeper and granular manner.
Heuristic analytics can help you discover his behavioral patterns and variations to construct usage models, persona and social networks.
Predictive analytics can help in predicting his needs and actions for the future.
Once you construct this mind map, prescriptive analytics algorithms can take over and recommend the best market actions to deal with the stated and predicted needs as well as for different contexts. This is where marketing becomes really effective as it is now personalized, contextual and instant too.
These marketing actions could be anything such as recommending best-fit offers, personalizing service and content as well as delivering a consistent and personalized experience across various touch points. Prescriptive actions can be derived either through machine-learning-driven algorithms or rule-driven modeling, depending on the complexities at hand.
Nano-marketing is here to stay
Having the capability for nano-marketing has become a “must” for almost all the CSPs irrespective of the markets as they are competing aggressively to retain their customer base and market share without compromising on margins. It helps in influencing the behavior and attitude of customers to an appreciable extent and improves their experience so as to strike a long-term, profitable relationship with the CSP. With the onset of advanced analytics tools and Big Data technologies, nano-marketing is going to get better and bigger, delivering higher returns to CSPs on a sustained basis.
Pravin Vijay is director-marketing at Flytxt. He is an avid technology marketer with 12 years of experience working with software product companies in the Telecom and Banking domains. He manages global marketing initiatives of Flytxt, a fast-growing Big Data analytics technology company with a focus on enabling mobile operators to generate measurable economic value from data.