A lot of organizations operate with very limited insights into their clients’ relationship with the business itself. Even in this data-driven era, they aren’t using analytical capabilities to develop products and channels for their clients. They want to build strong relationships with their clients, but their understanding of customer needs and preferences is underdeveloped or even non-existent.
Other businesses struggle with developing homogeneity across the diverse channels through which customers seek to access the business. As technology changes and customers look to contact the business through new channels, organizations must develop and homogenize these channels so customers receive the same level of service across whichever channel they prefer. Now, more than ever, customers are demanding self-service access to the goods and services they wish to procure. These self-service channels must be in place and well developed.
Not only are customers demanding self-service access to the business, but they want a custom-tailored experience; an experience that is uniquely designed to meet their needs and values. Businesses have to offer services, state policies, and activate business procedures according to the specific needs and problems of each customer, on a customer-by-customer basis.
Pablo More is a senior business intelligence ERP programmer who has assisted many clients in overcoming these types of obstacles. In a recent interview, Pablo More generously offered the following strategies and solutions for meeting your clients’ analytical and channel development needs in 2013.
Getting your data act together
In order to get a complete and accurate 360-degree view of your client, you will need to collect and aggregate your data from all channels and points of contact through which the client reaches the business. To ensure the accuracy of deductions that you will later draw from the dataset, you must acquire, migrate, and aggregate all client data into one datamart. This datamart will house all current and historical client data in one central repository.
To do this, start by defining your project scope and solution. Next, locate your data sources and begin carefully mapping them to their respective targets in the datamart. Before actually moving your data anywhere, you will want to be careful to set up the correct business rules for the migration. After applying these rules, the data can be migrated to a staging area and transformed using your choice of ETL (Extract Transform and Load) tools. Lastly, after migrating your separate sources to a consolidated data warehouse, you will want to profile your data to verify the accuracy of the business rules you applied.
Analytics solutions for the modern business
Whether your business uses SAS or a different business intelligence analytics tool, the next step is to select your metrics and point your tool to the datamart that you have created. Once you have constructed and configured this system, trained business users and analysts can use their analytics tools to begin generating metric insights about each customer’s needs and preferences. With all data aggregated in one datamart for the analyst to access, it should be quite easy to start deducing specific customer needs, preferences, and values.
By looking at the business systems and channels through which customers are choosing to access the business, analysts can also begin deducing points of needs in the channels and areas where levels of service need upgrading to better serve the client. Most of these analyses should be automated and scalable so they can be applied across the entire system of services, channels, and clientele on a daily basis. Building a consolidated datamart will allow analysts to deliver integrated insights about channel activity and metrics that are key to customer-service by allowing them to publish relevant and timely data analytics and reports about evolving client and system needs.
— Lillian Pierson is a data analytics engineer at Orange County Government, Florida. She also specializes in environmental engineering, GIS, world travel, tech journalism, and would-be digital humanitarianism. You can follow her on Twitter at @lillianpierson