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Captive BPOs- Just cost management or revenue enhancing asset?
Making effective use of customer data
The introduction of advanced technological platforms and databases has made the storage of humongous amount of data possible.
What is however lacking currently is the vision to make effective use of the data. Very few managers are in a position to perform effective data mining to identify drivers of consumer behaviour.
The zillion bytes of data lack the business context to derive useful insights for meaningful action. The relatively easy part in a company is the ability to generate hypotheses on factors that could be driving customer behavior but the toughest part is the ability to extract the relevant data and context to confirm or reject any hypothesis.
Take the example of a Telecom company attempting to reduce customer churn. While it would be easy to obtain a data dump on how many customers have churned by different segments, what the data dump would be lacking is the context to perform relevant hypothesis testing. Managers would not know whether a particular set of customers are churning on account of a new plan launched by marketing and was the communication to the market on that plan ineffective. Or could it be that retention team offered a scheme to the customers that did not work out leading to eventual churn. The frustration of managers to derive meaningful insights makes them fall back to gut-feel approach towards handling customer related issues.
Another example would be of organisations asking their customer service teams to perform up-selling and cross-selling to customers. Organisations create customer matrices or guidelines on when to position what kind of product to which customer. However that is a static snapshot based on historical experience and very few companies put in the effort to dynamically update those guidelines based on new evidence presented in every customer interaction. The problem will be the lack of the right information on when to pitch the relevant product to the customers.
18th-century Presbyterian minister Thomas Bayes, came out with Bayes’ theorem to answer the question: How should we modify our beliefs in the light of additional information? Do we cling to old assumptions long after they’ve become untenable, or abandon them too readily at the first whisper of doubt?
Unfortunately BPOs still don’t make effective use of data and have much to learn from Bayes approach to reject customer notions that have outlived their usefulness.
Aditya Bhallais Innovation Practice Head at QAI Global Services and consults clients on product and process design and improvement. He can be contacted at adityabhalla@yahoo.com
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