This is a continuation of a series of posts sharing my thoughts on the various components of a digital marketing stack. The series stared off with a post: “What does your digital marketing stack look like” and was followed up by posts on CRM, Marketing Automation and Content Management.

The next important part of the stack is Data Services. “Data Services” has historically covered a number of areas such as data integration, federation, cleansing and enhancement and typically because most of these services occur behind the scenes, is the “unsung hero” of most system landscapes.

I will describe briefly why this is such an important part of the digital marketing stack.

Data, data everywhere

Most technologists are already familiar with the issues around keeping a clean list of contact records. Even where there was only a contact database that was maintained manually, the cleanliness of this database was a challenge. Incorrect or missing data (such as emails, company names, phone numbers etc.) has always been a headache and this came into sharp perspective with the rise of CRM systems.

Fast forward to the typical scenario today where the digital marketing landscape comprises of a CRM system, a Marketing Automation solution, a couple of homegrown contact databases thrown in for good measure and data pouring in from traditional channels such as emails and website visits/form fills and newer channels such as social media.

The need for Data Services

With so many systems, all of which maintain their own lead (or contact data), how do you ensure that the following questions are answered at scale?

1. Completeness of data: The data that you buy from a list provider differs in level of completeness as compared to data that you get from a form fill, which in turn is different from the data that you can get off social media. How do you ensure that all lead records have the same level of completeness?

2. Accuracy of data: Getting the same level of completeness of data across all lead records is one challenge. However, even assuming you can achieve that, how do you ensure that the data is accurate? For example, you may have the email for each lead in your database. How do you ensure that each of the emails is current and correct?

3. Consistency of data: Given the myriad systems in the digital stack, this is increasingly critical. How do you ensure that the data that you have for a lead is the same across, say your Marketing Automation and CRM systems? Do you need to have a ‘system of record’ which offers the ‘one version of truth’ of lead data (also known as the ‘golden record’) or do you dynamically synchronize the data across all systems? If the latter, how do you decide which version of the data overrides all others?

Each one of the questions is a significant challenge and I don’t have the space to dive into as many details as I would like.

There are vendors, both traditional (such as Informatica, TIBCO, SAP Business Objects, IBM etc.) as well as newer ones (such as SnapLogic, MuleSoft, Dell Boomi etc) who provide a variety of software tools and services to help companies overcome these challenges.

Do you face these issues around data completeness, accuracy and consistency? If yes, how have you started resolving them? I would love to hear your thoughts.