So you’ve got mountains of data, providing valuable insights on your customers, and the tools to analyze individual strands of this data convincingly. Superb. But can you join it up to provide the valuable insights you require?
As businesses get to grips with making sense of the disparate data they have sitting in individual silos, how do they take the next steps toward connecting those silos of different data types together?
The relevance of this question to marketing and the concept of the Single Customer View is obvious. But it’s also interesting to see that the importance of ‘Connected Data’ in general is being felt across so many industries.
Connected data is a fundamental requirement to understanding your business and your customers.
Generally speaking, the ability to join together every memory of every interaction you have is paramount if you plan to improve your relationships, processes, customer experience, and ultimately, your bottom line.
In many ways, remembering things online is no different to remembering things in real life. If you can’t remember what conversations you’ve had, with whom, and about what, future conversations become impersonal and possibly irrelevant.
In the case of customer data, while some data can be cross-referenced using a ‘common key’ – a unique account number or email address for example – data sources that don’t share a common key have to be processed to create a 'single source of the truth'.
The matching, merging, and deduplication process itself can be a complex series of auditable, data processes that try to ascertain the best possible match rate, subsequently processing the data further to ensure the data is as clean and trustworthy as possible.
In the context of providing insight into customers specifically, this end-to-end process of transforming disparate data sources into a coherent and reliable single source of knowledge, and then storing it appropriately to support a range of business activities, is what we refer to as a ‘Single Customer View’.
When you’re connecting customer data together, you’re dealing with memories of interactions with people – not just businesses, shipping addresses, or accounts.
A good data platform will still provide account/business/household level views, but connecting your data at the individual level will create the right foundation for everything you do going forward.
The cost of developing a connected data strategy largely depends on the number of disparate data sources you have, and the number and complexity of contact channels your customer can communicate through. The frequency at which you update your single source of the truth also affects whether you need an automated data-processing engine, or whether you can manually create the connected data views. The range can be anywhere from one day per week for manual, weekly updates; to a one-hundred-day project to implement a complex, automated, daily refresh that will build a robust Single Customer View across many disparate data sources.
Ultimately, remember that data on its own does not mean intelligence. Ensure that when you connect your data together, you are able to add the empirical insight to the data views that will help you to make the most of it and inform better decisions. Being able to store and connect data is one thing, but being able to shape insight is very different.
Whether you are a marketer getting to grips with the concept of an SCV, need to know what your organization needs to consider before building one, or want to better understand the ROI, Blue Venn's The Ultimate Guide to Single Customer View has the answer.