The Marketing Data Stack - Part 1: How Some Brands are Beating the Competition by Aligning Technology to Objectives
In 2021 Google and the Boston Consulting Group found that "digitally mature brands" increased their sales by an average of 18 percentage points more than their less mature peers and boosted cost efficiencies by an average of 29 percentage points (source)! But what did they mean by “digitally mature brands”? And how can you be sure that your organization isn’t one of the “less mature peers” falling behind competitors?
The BCG findings affirm the same results that we've seen in countless studies over the past decade: those companies who have mastered the Marketing Data Stack are generating more revenue at a lower cost than their competitors. This is the first post in a 2-part series. In this article we will define the Marketing Data Stack, and explore how those companies are applying it to gain a competitive advantage. In the second article we will share a framework for evaluating your own marketing data stack.
So What Is the Marketing Data Stack?
The Marketing Data Stack is the strategy, technology and processes that turn raw data into valuable outcomes for your business. It is not a synonym for your martech stack–the term describes the elements that align your martech stack with your business objectives.
Most enterprises have made a big investment in marketing software, but when you survey those companies a few years later only 32% report that they are getting the return they anticipated (source). The unfortunate truth is that expensive and well implemented software is not enough to create the value expected for your business. Those companies that are gaining a competitive advantage from their martech investments have put in hard work to ensure that all people and platforms are aligned to accomplish a shared mission and expected outcomes.
The Five Layers of the Marketing Data Stack
If you review the research from BCG and others about how high performing marketing teams are differentiating from competitors, you will discover several recurring themes. We have identified five key elements that these companies use to align a martech stack with business objectives, and we call these the 5 layers of the Marketing Data Stack:
Strategy
Data Collection
Integration & Automation
Analysis & Visualization
Activation & Optimization
To explain how the 5 layers interact with each other, it is helpful to think of the way a business matures over time.
Marketing Data Stack – Stage 1
Any brand that participates in marketing or sales activities today has already created some part of the Marketing Data Stack. Smaller teams may focus exclusively on collecting data from customers and prospects, and then using their martech stack to activate these customers and prospects (by creating content, purchasing ads, cold calls, etc). The illustration below shows how the Marketing Data Stack is the connection between your martech stack and your customers.
The key characteristic of stage 1 is that marketers are using individual martech platforms independently of one another. They are collecting data as each tool is designed, and attempting to use these tools to accomplish traditional marketing objectives (product, place, price and promotion).
Unfortunately this approach does not scale. As a business increases the number of tools and technologies that assist with marketing and sales (such as customer databases, ad platforms, CRM tools, CDP’s and analytics platforms) the complexity of ensuring that your martech investments can support your business objectives will also increase. It is common for large enterprises to include over 100 martech applications (source), and these teams often find themselves with a set of tools that are not working together effectively. This is when they move into stage 2.
Marketing Data Stack – Stage 2
This stage is defined by a shared cross-channel strategy. Marketing teams in stage 2 continue to use individual martech platforms independent of one another, but they have aligned their teams around a shared strategy to accomplish their objectives (often deployed through OKRs).
This is a big step forward above stage 1. During stage 2 marketing teams begin to gain a clearer picture of their audience, how they interact with the business as a whole, and how the various marketing domains contribute to the overall strategy.
But marketing teams who operate in stage 2 will eventually notice the significant gap between their strategy and their martech platforms. This usually becomes apparent when there is disagreement about whether or not the team(s) are on track to meet their objectives. Since each martech product operates independently it can be challenging to understand how the organization is performing as a whole. This is when marketing teams move into stage 3.
Marketing Data Stack – Stage 3
The key characteristic of stage 3 is a shared measurement strategy. Those teams who work independently of one another to achieve common goals will need to understand the metrics that will be used to determine if they are successfully meeting those goals, and they will also need to trust the data that is used to capture and calculate those metrics. To enable this, teams adopt a disciplined approach to data analysis and visualization.
Although every enterprise will have some analysis and visualization capabilities, very few actually make it to stage 3. This is because analysis and visualization capabilities only create organizational alignment when they have the required trust, technical capabilities, and leadership support.
When a company successfully reaches stage 3 they will eventually begin to struggle with the limitations caused by data silos. This is the final gap between a martech stack and the layers on top, and those teams who choose to overcome these challenges move on to stage 4.
Marketing Data Stack – Stage 4
The defining characteristic of stage 4 is the blending of data between martech platforms. This often begins with a goal to optimize cross-channel advertising spend in a marketing mix model, or use a CDP to create segments based on attributes in a CRM system that can be activated across media and experience platforms.
Those teams who have mastered the Marketing Data Stack have developed the capabilities to integrate and automate the data pipelines that are necessary to support the business objectives. BCG calls this “a true end-to-end measurement capability”, and it is the ultimate differentiator of high performing companies. These capabilities are built on top of your martech stack, but they sit under the analysis and strategy layers that align the entire stack toward your business objectives.
So Why Is the Marketing Data Stack so Important?
Studies have repeatedly shown that those companies who gain competitive advantage have developed the strategy, technology and processes to turn raw data into valuable outcomes for your business. The BCG study referenced above as well as others from other research firms use slightly different language, but find nearly identical results. A mature Marketing Data Stack is the key driver that sets apart those high performing brands that generate more revenue at a lower cost than their less mature competitors.
The reason that so many marketing teams complain that they are not getting the value they expected from their martech stack boils down to this: the martech stack wasn’t built for your business. Your business and your objectives are unique, and your martech stack will not help you grow your business without strategy, technology and processes to point your martech stack in the direction you are trying to go.
At DiveTeam, we have designed playbooks to show how a mature Marketing Data Stack can add value across every marketing domain:
| Brand Awareness | Prospecting & Lead Generation | New Product Launches |
| Customer Experience | PCustomer Engagement & Loyalty | New Customer Acquisition |
Why DiveTeam Prioritizes the Marketing Data Stack Over Platforms
At DiveTeam, we believe that tangible value is created from creative people thinking strategically and holistically about how to achieve outcomes, not from filling feature gaps with software solutions. Yes, we need analytics, and CRM, and ad platforms, and cloud solutions–however we believe form follows function. This is where the Marketing Data Stack provides the missing view of how your customer and marketing data need to transcend these platforms to tie them together in unison and align them to your desired outcome. It can also be a valuable tool in planning how your martech stack evolves over time in a scalable, efficient, and effective approach.
Next, In Part 2 - Evaluating Your Marketing Data Stack
In this article, we’ve defined the Marketing Data Stack and explained how it creates a competitive advantage by aligning your martech stack toward the objectives of your business.
In the second part of this series, we’ll introduce the Marketing Data Stack framework that we use to assess your brand’s current state versus your aspirational state and how to identify the missing capabilities needed to push through the barriers that may be holding you back from achieving your desired outcomes.
