The advent of Big Data in the last few years have made a huge paradigm shift in how organizations across industries make data driven decisions. Customer behavior is a key aspect where companies have been using modern Big Data technologies to get a 360- degree view of customers from different angles. With more and more products and services being available digitally, companies want to know more and more about their existing customers and prospective new customer not just within the parameters of their interaction, but also on what else he or she is interested in. A holistic view of a customer personality helps companies not only to tailor their products and services better, but also communicate with greater relevance to differentiate themselves from the clutter.
Analysis of customer sentiments, changing needs, and evolving trends can be tapped by merging in diverse internal and external information. Internal data, typically owned by the company contains data like transaction details, campaign performances, customer service history, loyalty programs, and customer satisfaction. External data covers category information, demographics and geographic details, lifestyle – attitude- psychographics and social media data.
The challenges in integrating these data sources are vast, and can’t be handled by traditional systems. Big Data platforms have the capability to deal with such vast variety of data, which are terabytes in volume and are generated at a very high speed. Distributed computing and cloud systems enable merging, handling and result generation from these diverse data sources.
The Big Data Environment:
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Big Data technologies have already proven to be highly advantageous over the traditional RDBMS systems, which are critical for modern Customer Management:
- Speed – High Speed Data Mining due to parallel processing
- Volume – Handles large amount of data
- Set Time – Has lower set up time
- Cost – Cheaper than RDBMS for significantly large size of data
- Scalability – Highly scalable and flexible with growing need
- Variability – Handles unstructured data and ready for text analytics
With greater clarity, organizations can drive up their revenue by getting the right information for the right customer at the right time and act on it. Broadly there are 5 steps to using Customer 360 info for maximum results:
- Listen – to what the existing customers are saying about the company products and services. Improve areas of concern, build on areas of strength
- Understand – how customers interact with the company and category in general. Get early symptoms of industry changes and new trends.
- Assess – how well customers are served currently. Identify areas of improvement, cross-sell upsell opportunities
- Improve – interactions through customization. Each customer should feel he is getting individualized attention from the company. His experience of every interaction should be smooth and easy going, leaving him with a wow feeling every time he is in touch with the company
- Strengthen – relationships with customers by engaging with them through channels and offerings most relevant to him or her
The customer view approach should be considered across:
- Past – A meaningful and accessible view that includes purchases, interactions across channels, campaign response etc.
- Present – Key information about who they are and how they relate to the brand, triggers for current interactions and recent history
- Future – Actions that can influence future behavior and relationship. Actions to prevent churn, drive up-sell & cross-sell & maximize LTV
Customer 360 – Build Stages & Data Types
The journey for Customer 360 process consists of 4 broad phases:
- Create Unique Global Consumer ID – Create coverage for members, non-members, new customers, across brand integration, regional overlaps, household information etc.
- Internal data – Transaction information of existing customers, historical customer service details, customer satisfaction measures, web activities, loyalty programs, social activities
- External data – Category information, related category trends and events, geographic and demographic profile, attitude and psychographics information, competition analysis
- Predicted – Propensity and affinity of purchase, pursuadableness of customers for upsell cross-sell, conversion of prospective customers.
The trend is set, movement is on. Some industries have adopted Big Data earlier than others and are already seeing significant improvement in their customer satisfaction and revenue upliftment. Big Data is fast becoming the standard across companies and industries for improved Customer 360 degree view and action.
Mr.Titir Pal(Head of Products & Solutions at Absolutdata Analytics)
Mr. Rajat Narang (Associate Director at Absolutdata Analytics)