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Customer centric data intelligence

Objective

One of the most important objectives behind a Customer Centric Data Intelligence implementation is the evolution of the company’s culture from “Product centric” to “Customer centric”. Customer centric companies are not only able to better understand and predict customer needs, they are also able to implement and leverage solutions that allow for automated and prompt insight about single customers and entire customer segments. Customers are different, successful companies know that and tailor their offerings and the customer experience towards their specific needs.

With this objective in mind Nextbit has been collaborating with major multinational corporations to bring about this customer centric vision. The project entails not only the reorganization of customer and product data, but a re-organization on business processes as well as the sales and marketing strategies.

Roadmap >

After an initial analysis and evaluation phase on the client’s current status, one of Nextbit’s initial (and fundamental) task is the development of a roadmap that enables the company to achieve a comprehensive Customer Centric approach, including immediate tangible results within a long term strategy plan. The roadmap allows an evolution in terms of: data intelligence, solutions adopted, company-wide strategies utilized to engage and interact with customers.

The Customer Centric Data Intelligence Roadmap is composed of a Data-work stream, an Analysis and Reporting work stream, a Models and Business Rules Deployment work Stream. Each stream is divided into distinct phases with distinct deliverables.

The diagram below depicts each stream and shows just one of the deliverables for example purposes.

customer centric data intelligence

Data Work Stream >

On our latest project, conducted by a major European financial institution, the Data work Streamwas divided into three phases:

  • A first phase concerning customer attributes, product holdings and sales. Collecting all demographic information about the customer as well as all past purchases and utilization of product and services.
  • A second phase on channels and interactions. Collecting information on customers’ channel preference (i.e. web, call center, email, agency), past and current campaign response and levelsof customer interaction.
  • A third phase on external behavior, relationships, profitability. Collecting information about external behavior,satisfaction levels, relationshipswith other clients and prospects.
customer centric data intelligence

Results >

The methodology used in implementing the Customer Centric Data Model follows Nextbit’sapproach to data intelligence implementation, allowing for early results within a long term plan.

Customer centric data enables immediate customer insight such as: basic RFM indicators (Recency, Frequency, Monetary), customer lifestage classification, financial impact and behavior analysis. By tying in other aspects, more insightful measures can be introduced such as: lifetime-value, loyalty, share-of-wallet, influence, relationship with other clients. All of these measures can be used to segment the customer base, monitor the results of campaigns and company initiatives, differentiate and evaluate marketing strategy adoption. The measures listed above are implemented as part of the the Analysis and Reporting work stream, and the Models and Business Rules Deployment work Stream.

A recent analysis conducted by Nextbit for one of the largest department stores in Europe is on Customer Journeys, under the Models and Business Rules Deployment Stream. The objective of this analysis is to understand customer purchasing patterns at a product level within a brand and across brands, tracking customer changes in behavior as they take on more products and predict the type of customer who would interact with multiple product types and multiple brands.