What is it?

Marketing DataOps is a set of practices that aim to improve the quality and cycle time of Marketing data products by orders of magnitude. Its impact can be related to the one that Agile, DevOps, DataOps and InfoSec methodologies brought to software development. It inherits a lot of principles from those concepts and applies them to the realm of Digital Marketing. If the terms: sprint, backlog and release cycle are new to you, the SAFe site has a lot of great foundational resources. On the other hand, if you are familiar with the principles, have tried agile marketing before and/or want to learn more, I invite you to keep reading.

 

What are Marketing Data Products and how are they different?

Marketing Data Products are deliverables to customers or internal users that create value and are crafted with data and analytics materials. Imagine an automated email workflow, a retargeting campaign or the performance dashboard that monitors both. The crafters work with the product owners to solve the challenges in the product backlog one increment at a time. Compared to most technology product development processes, Marketing is in a different situation because of the size of the product portfolio, the overlaps of product ownership and the spectrum of crafters.

Marketing communicate as a product

Product portfolio size

Marketing tends to have a larger number of products in it’s portfolio than other teams in an attempt to match the customer segment, customer lifecycle stage and channel in detail. In the example below, the combination of these factors translate to 300 different Marketing products. There may be a new customer promo for those in the ‘young parent’ segment that is only available through the newsletter channel for instance.

Meeting customer needs with the right mix of product, price, place and promotion has always been the goal of Marketing. Digital took that to a whole new level with personalization and real time customer segmentation based on online behaviour. Acknowledging this complexity is a key differentiating factor between the Marketing DataOps practice and other Agile Marketing frameworks.

If we are to truly manage Marketing deliverables as data products it is critical to productize the entire portfolio. The reality in most firms is that innovation portfolios are clogged with too many projects  (Murray, 2008). Therefore, analyzing and packaging products into a manageable  portfolio is necessary before any agile optimization practices start. This ensures the focused efforts are going to the most impactful places.

The overlaps of product ownership

Agile frameworks emphasize the need to have a single product owner directing the product backlog. The challenge with digital marketing is that it is often responsible for every communication channel (website, app, customer portal) but it may not fully own them. The mobile app for example may be owned by another team that reserves the right of feature prioritization. If there is important data that needs to flow from the mobile app to the CRM and Marketing does not controll the assets, exploiting innovation will not be efficient. This situation leaves marketing data product owners in a silo or a constant negotiation. It is the reason behind problems like team and tool duplication – as marketers attempt workaround – and conformism – as they leave their product become the side project of another team.

It is worth mentioning that the scope of this problem goes all the way to the blurry line between CMOs and CTOs these days. After all, “Technology currently accounts for the largest proportion of marketing budgets” (Gartner, 2020) and there are increasing discussions about new and old role definitions. Addressing this huge organizational problem is critical before attempting any optimization. Making improvements under certain control limits could of course help. But focusing on the features that generate the highest value is recommended, regardless of them being off limits as they often are. Marketing should work in cross functional teams across the organization to take ownership of the data it needs to function.

Spectrum of Crafters (users)

The operations in Marketing Data Ops are focused around the crafters, marketing analysts, media buyers, email automation specialists, content creation and optimization specialists. These team members have unique objectives and require different support. Enabling data flows for them means covering a large spectrum of requirements. Meaningful benefits for the analyst may mean less data prep and more time spent on getting real insights. For email marketers it could mean more automation of communication. While Content creators may be able to scale personalization.

 

What problems does Marketing DataOps solve?

Since implementing a DataOps approach to Marketing requires adjustments to tools, people and processes. There are many problems that are addressed consciously and unconsciously during the transformation. They can be categorized as value blockers under the following categories:

Gaining value from Technology

Gartner research shows that marketers use only 58% of their existing technology capabilities. Extracting their full value may come with costs such as upskilling marketing talent or investing in workflow management applications — investments that would be hard to justify in a challenging business environment. (Gartner, 2020)

  • How should companies manage the technology resources that support Marketing to extract full value?

Legal compliance

GDPR, CCPA and similar legislations demand careful handling of customer data and Marketing is often the one collecting, storing and retrieving the sensitive pieces. 

  • How can InfoSec and Data Governance be implemented in Marketing?

Gaining value from People

Knowledge workers, on average, spend just 2.8 hours a day on productive tasks (Mackay, 2019). Most of the time is spent in neutral tasks like meetings, data entry, coordination and distracting activities like social media and news. This brings forth the following challenges:

  • How do we cut down on the neutral tasks, should automation take over?
  • Could better job definitions and boundaries improve focus and work-life balance?

Gaining value from Data & Analytics

For many enterprise Firms, fixing core Marketing data issues is a multiyear and million-dollar task. The Boston Consulting Group study (2018) shows: 83% could not link data across consumer touch points. 68% lacked automation, relying instead on manual processes. 78% could not attribute value to their individual touch points with consumers. 80% suffered from inadequate cross-functional coordination.

  • Where should the next marketing dollar be spent?
  • Can strategies from technology development process optimization help given investment restrictions? 

References

Murray, F. (2008). 15. 351 Managing Innovation & Entrepreneurship – Class 18 R&D Portfolios. Retrieved from MIT Open courseware: https://ocw.mit.edu/courses/sloan-school-of-management/15-351-managing-the-innovation-process-fall-2002/download-course-materials/

Gartner. (2020). Gartner CMO Spend Survey 2020-2021: Technology and Digital Channels Withstand Budget Cuts. Retrieved from Gartner: https://www.gartner.com/en/marketing/insights/articles/gartner-cmo-2020-2021-tech-digital-channels-withstand-budget-cuts

Mackay, J. (2019). The State of Work Life Balance in 2019: What we learned from studying 185 million hours of working time. Retrieved from Rescue Time Blog: https://blog.rescuetime.com/work-life-balance-study-2019/

Field, D., Shilpa Patel, & Leon, H. (2018). Mastering Digital Marketing Maturity. The Boston Consulting Group.