This blog was adapted from BrandMaker’s: “Marketing Ops Now” podcast. Each installment discusses valuable ideas for both management and marketing executives. You can listen to this 20-minute podcast here.
Data is the foundation for companies for all customer experiences. And as a consequence, data is at the basis of all the sophisticated tactics you can think of, whether it is analytics, personalization, campaign operations, performance measurement, or journey orchestration.
If the data isn’t consistent, accurate, and available, none of the above works. Getting data right is an important step we simply cannot skip. We have to make sure that the actual foundation of data is really solid. It is indispensable for almost every company out there, as they become increasingly digital.
Laying the groundwork for customer experiences starts with definitions. Just like we discussed in the playbook podcasts and articles. We need to have a shared definition of fundamental concepts such as a lead, account, touchpoint, engagement, contract, etc. This is required to establish a data model that is relevant to the business. In the world of data management, people often call this metadata. Metadata is data that describes where what data is.
These definitions help to shape the data models, unique customer IDs, data relationships, data entities, or even data fields. So when customers interact with a company we can capture and process feedback from prospects and behavioral insights. As we go, we improve the data accuracy as we fill the gaps in the data, e.g. in B2B industry, size of this company, purchasing stage, as well as better understanding roles in each account, recognizing the decision maker, etc.
With more complete data we will be able to tell at what funnel stage a specific lead or account is, based of course on the mutually agreed definitions. With more complete data we’ll ultimately be able to hand customer records over to the sales organization. The relevant data give sales reps a head start when starting sales conversations with the customer.
And it does not stop with sales. They in their process enrich the customer data during the sales process. And once a lead has become a customer, it is the beginning of the ongoing relationship with the customer. Inevitably there will be renewals or new purchases or even expansion into other teams. With customer data crossing departmental boundaries, companies start to group and align around the customer, data-wise.
Not just definitions will bring marketing to align with different departments. The variety of systems across the business where that data is stored urges us to sit down together and align.
There has been a lot of progression in the field of data operations as businesses are all becoming digital companies. Data operations is concerned with the management of data infrastructure across entire companies.
Companies are coming to understand that tons of data almost never sit in just one system. It is more like an ecosystem of different operational systems. To get our head around how to structure such a data ecosystem, we come up with concepts like a data warehouse, data lake, data lakehouse, data mesh, etc. These are all variations of the specific particular concept: data federation.
The huge benefit of data federation is not about collecting data in a smart way, it is also about pulling and distributing data to departmental solutions. Ultimately all that data of those customer interactions has to continuously flow back into that cross-departmental data ecosystem. The different business units and departments need the data as input e.g. for analysis at the data science department, for understanding the client status at the customer success team, or for finetuning campaign messages at the marketing department.
It is important to realize that data models need maintenance. When daily reality kicks in, we need an extra tool here or a new field there to stay ahead of the competition. Companies need that kind of flexibility. But as we add new things the data quality might suffer. The data starts to degrade. Especially in marketing organizations that is a challenge.
That is why core definitions of a customer record are critical. These are maybe based on the core definitions of the deal stages, an account. Before you know it 30% of the overall record is following the agreed model but 60% of it starts to drift off. This is where the value of a marketing operations team really comes. They are that disciplined curator who says ‘no, you can’t add these new fields, you can’t change the definitions on this’.
Maintenance and governance of the data ecosystem bring us to the role of marketing operations in this. From a marketing data model perspective, marketing operations has to make sure they own that governance model. That governance model is not a stand-alone model, it should reintegrate into the rest of the digital infrastructure of the organization.
As a result, marketing operations needs to participate in DataOps meetings. That seat is required to agree on how the customer data is going to contribute to the larger environment. This often comes with defining a kind of translation layer to make sure that their model is speaking the same language as the rest of the organization.
The governance model and translation layers are not the only elements that need to be discussed at the DataOps table. Also, the standardization and leveraging of tools are important. It’s can be incredibly advantageous to leverage data tools organization-wide. Maybe there are data warehouses or BI solutions that marketing operations can leverage. It can go as deep as sharing data views or database queries. In its turn, marketing operations has to decide which data needs to be centralized and which data does not. Not all the data needs to be federated. That is where marketing operations really make a call and make a good judgment saying: ‘what is the data costs versus the value trade-off?’.
BrandMaker’s “Marketing Ops Now” podcast series has officially started. In each podcast industry luminaries and deep thinkers share valuable marketing ops ideas for both management and marketing executives (some worth stealing).
For every podcast in the series we’ll do a blog post to share the highlights with you. You can listen to this 20-minute. podcast here.
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