Analytics trends 2014
In 2014, eight business analytics trends will rule the day - or will they.
When a telecommunications company wanted to shift more services online
Deloitte Analytics helped them find a deeper connection with their customers
The member firm client, a leading telecommunication provider in the Asia Pacific region, was undertaking a major transformation within the organization. The company wanted to make better use of its digital channel to connect and serve its customers, but at the same time do this more cost-effectively.
The member firm team were asked to analyze the current channels of communication and interaction, distinguishing the type of customer using each channel and the cost impact by channel. The behaviors of each customer were examined by combining disparate data sources on their product holdings, their average revenue, their tenure, and their likely risk of churn. The nature of the queries, complaints, and feedback interactions these customers have with the organization were also examined along with their preferred channels for doing so, and the cost impact.
This would allow the member firm project team to move beyond a transaction-based view to reach a deep understanding of the behavioral needs of the client’s customers and to put together a far more granular and measurable adoption plan to help migrate these customers online and realize rapid time to value for the organization.
The member firm client knew that the key to driving online adoption was understanding and appealing to the behavioral needs of its customers. The member firm team worked to develop this customer-centric view, to bring together for the first time otherwise disparate customer data sources and combine them to create a picture of the customer.
The key challenge was to understand the varying behaviors and needs of these customers- to recognize who was performing what transactions, what channel they were using, and why they were doing it, in order to gain the diversity of data needed to identify customer behavioral patterns.
The areas to concentrate on were: Is the customer calling to query a bill? Query their account? Are they making a complaint? Making an enquiry about a product they already have? Are they enquiring about a product they want to purchase? Or are they just making a general enquiry? It was necessary to understand how customers were seeking to interact with the company, which of these interactions could be supported online and, from this, work toward an adoption strategy to migrate those customers from more expensive channels to online.
How analytics helped
Traditionally, the member firm client had looked at each transaction to try and migrate that particular type of transaction online. This project showed them that instead of this, they needed to understand everything about the customer and the transaction. They needed to take into account the customer, how valuable they are, how long they have been with them, what is their typical demographic, what channel they were using for transactions, and how often.
To begin with all the data about the customer was gathered, including; who they were – demographic information on age, gender, profession, education, nationality, and lifestage; their customer profile – products held, average revenue, usage, and spend patterns, tenure; how they engaged – phone calls and IVR, online, visits to the retail center, and to third party dealers; and why they engaged – product and general enquiries, billing and account queries, faults and service queries, and complaints. The data was entered into an environment to model and structure a complete behavioral view of the customer.
Using a clustering technique and artificial intelligence 16 clusters of customer behavior were identified. Relevant features and attributes from these clusters were used to inform how heavily customers were using the online channel, what other channels they were using, and the main reasons for the interactions. The member firm team were able to prioritize the high, moderate, and low adopters as an immediate source of focus and momentum.
While dealing with more than eight million customers, the member firm team were able to pool together all the views around the customer into one environment with a longer history of data than previously considered. The member firm client had never seen this done before.
Member firm specialists from across Deloitte Analytics, Corporate Finance and Consulting came together as one single team. Corporate Finance doing the transaction and financial modeling, Deloitte Analytics performing the complex customer clustering and behavioral analysis, and Consulting providing the strategic insight and thinking into an adoption strategy and action plan to migrate customers online. The analysis that was completed was used to show the adoption techniques that could be applied to migrate customers online.
The member firm client now has the ability to take a more granular approach allowing for a more targeted approach to ‘who’ they seek to adopt online, ‘how’ to best appeal to encourage adoption, and ultimately achieve more rapid ‘time-to-value’ in both cost savings and improved customer retention.
The next stage of the project is to construct a detailed adoption plan – this will include the clusters of customers, and a proposition to migrate these customers online and what the expected outcome will be. A further piece of work has been proposed which relates to customer experience.
Analytics must be used to be useful. Abstract theory might be interesting, but it won’t solve your business problems – unless you put theory into practice.
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