An adtech/martech hierarchy of needs

Tips for investing in your tech stack

Investing in adtech and martech can be a daunting experience. Implementing the right tech stack is a critical component of any organization’s marketing efforts. It spans the gamut from understanding the customer journey to evaluating a marketing campaign’s performance and beyond. While selecting the right components for your adtech or martech stack has been the popular discussion as of late, the order in which you invest is equally crucial to ensure a smooth rollout and to help incrementally move towards becoming a truly customer-centric and data-driven organization.

For a variety of reasons, I have too often witnessed clients investing in the wrong part of the stack in their lifecycle – and with disappointing results, often causing them to roll back their investments and start again. 

My hope is that a careful, steady approach to investment will ultimately improve your experience in working with your tech stack, helping to drive better marketing results. So how do we go about it? While there are a number of different ways to tackle this problem, what I often refer back to is a form of Maslow’s Hierarchy of Needs – but tailored to a tech stack – a sort of adtech/martech hierarchy of needs.

While Maslow’s Hierarchy of Needs tries to match an individual’s motivations with their varying levels of needs, a adtech/martech hierarchy is more related to an organization’s maturity in capturing, reporting, analyzing and operationalizing an organization’s customer data to deliver more relevant, more valuable and ultimately more profitable customer experiences. 

Here’s my typical approach to the hierarchy:

Data collection

Without sounding like a truism, data is the backbone of any data-driven marketing initiative. As such, implementing an accurate and trusted data collection regime is the foundation to any attempt at a tech stack hierarchy. While we often think of the CRM as the core of this layer, there are other crucial pieces such as web analytics and ad servers that play an important role in generating the raw data that will be used down the road.

Data reporting and visualization

Having the data is great, but as any analyst will tell you, it means nothing if it’s hard to organize, report, interpret and understand. This is where the industry has made great strides beyond simply using Microsoft Excel to showcase the numbers. Whether your organization uses Tableau, Google Data Studio (or even Excel or PowerPoint), it’s important that the tool you use is malleable and universal – that you can import data from any of your sources, as well as visualize it in an impactful and meaningful way.

Audience and campaign analysis

With more powerful systems and better algorithms, we finally have the ability leverage a massive volume of existing raw data to finely segment, model, and predict behaviour and derive new insights and tests. Tools with built-in media mix modelling and attribution modelling are starting to become more ubiquitous and accessible to more marketers, allowing us to make robust marketing investment decisions to drive incremental results. When married with first and third-party audience data, marketers can craft campaign strategies that are both highly targeted and highly relevant.

Data activation

With the deprecation of cookies looming over our heads, the industry has taken great leaps in simplifying and enabling audience data activation. As I’m sure you’ve been told dozens (if not hundreds) of times by this point, data management platforms (DMPs) and data clean rooms are crucial to ensuring that digital marketing remains relevant. However, as you can see, simply implementing a DMP or uploading your data into a clean room without the prior work of data capture and processing could make data activation inefficient or, even worse, provide a poor user experience.

Driving towards tailored experiences

Last but not least, to unlock truly tailored and personalized ad experiences, we need to finally marry the activated data with relevant creative. Through dynamic creative optimization (DCO) and CMPs, marketers are managing mass-market but hyper-targeted campaigns efficiently, and understand ROI more quickly and effectively than ever before. While this may still be a pipe dream for many advertisers and marketers (especially those of us in small and medium-sized businesses), it’s oftentimes better to let those with deeper pockets test them out first and refine the experience before they become mainstream.

Final thoughts