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Three ways to organize your martech stack



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Earlier this month, Scott Brinker revealed the 2022 Stackie Award Winners. The Stackies are a contest for organizations to submit a visual illustration of their martech stack. This year, five different winners were selected.

My favorite part of the Stackies is observing all the different ways organizations choose to organize and catalog their martech stacks. After reviewing this year’s entries, below are three of the most common ways to consider organizing your martech stack and some of the unique benefits of each approach.

1. The customer journey

One of the most popular ways to organize your martech stack is to align your technologies with the stage they support in the customer journey. Different companies have different terminology for the different phases, but it typically goes something like “Awareness,” “Consideration,” “Purchase” and “Onboard.”

In this example, SEO tools would typically be categorized under the “Awareness” phase, whereas e-commerce platforms would easily fit under the “Purchase” phase. When categorizing your tools this way, there are two challenges you want to be sure to account for:

  • Make sure you have a way to tag some technologies under multiple customer journey stages. For example, your marketing automation platform would likely be used across multiple stages, including “Awareness,” “Consideration” and “Onboard.”
  • You will also want to have an entirely separate category or two for tools used for internal purposes that customers don’t necessarily directly interact with along their journey. Data and analytics tools, as well as internal workflow and collaboration tools, would fall into these categories.

And there’s an added benefit. Categorizing your tools this way gives you a great visual to see what tools are affecting multiple stages of the customer journey and, therefore, may require more investment or resources. For example, if your marketing operations team has been pushing for increased headcount, showcasing how the platform impacts nearly every stage of the customer journey may help you garner internal support from leaders even outside of marketing, such as sales or customer support.

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2. Technology category or subcategory

One of the most common and popular ways to categorize your martech stack is simply by the technology category they belong to. This is how the famous Martech Landscape supergraphic, along with the new interactive MartechMap, organizes tools. When organizing your martech stack, you could choose to keep your categorization at the highest level, such as “Advertising and Promotion,” “Content and Experience,” “Social and Relationships,” “Commerce and Sales,” “Data” and “Management” or you could choose to get a step more granular and assign your tools according to their appropriate subcategories.

For example, the subcategories under “Content and Experience” may include “Email,” “Social,” and “Web” among others.

Another added benefit: One of the biggest challenges that marketing organizations face is the proliferation of technologies available. Marketing organizations struggle to take full advantage of their martech stack’s potential. According to the Gartner Marketing Technology Survey 2019, marketing leaders report utilizing only 58% of their martech stack’s potential, down from 61% in 2018.

Organizing your tools by the category they belong to can help you easily identify where there may be opportunities for consolidation within your martech stack. For example, you may discover that you are using multiple survey tools across the organization because individual teams needing a quick survey have set up free or low-cost accounts on platforms like SurveyMonkey or Google Forms. You may have a customer experience group using a more robust platform such as Qualtrics, which handles customer surveys. That could be an opportunity to consolidate onto one survey platform.

Consolidating your martech stack can help you take better advantage of your martech stack’s potential by cutting costs, reducing data silos, and ultimately enabling users to spend more time diving deep into all of the available features of one tool and sharing that knowledge with others.

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3. Internal organizational structure

 Another way to organize your martech stack is by the internal teams responsible for operating those technologies. For example, an organization may typically include a data and analytics team, a marketing operations team, a content management team and an advertising team. In this situation, one team may own some tools, such as display advertising tools for the advertising team or the website CMS, which only the content management team can access. However, there are likely quite a few tools that multiple teams have access to, such as some data and analytics tools, like Google Analytics.

When categorizing Google Analytics within your martech stack, you may realize that it needs to be associated with more teams than you initially thought. Of course, the data and analytics team has access to Google Analytics, but so does the advertising team, who is using it to focus on conversion rates of their campaigns. The content management team may have access to look at page load times. The marketing Operations team may also use it to determine the highest converting pages they should incorporate into their lead scoring models.


Added benefit? Cataloging your martech stack along organizational lines helps highlight where there is shared access and ownership within certain tools. This gives you the visibility to ensure you have the right policies, procedures, and rights management in place to ensure that different teams are not stepping on each other’s toes or operating in different ways that could ultimately hurt overall efficiency.

For example, in Google Analytics, you would want to ensure that multiple teams do not share editor rights, which would allow someone in the marketing operations team to edit the default channel groupings, which could potentially break some of the ways that the advertising team is optimizing spend across channels.

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Read next: How startups and small companies should build their marketing stacks

If you categorize your martech stack by your organizational structure, set up regular reviews of tools with shared access to ensure that you have the right governance policies in place and that they are being followed.

There is no right or wrong way to categorize your martech stack, as each approach has its purpose and benefits. You also do not have to limit yourself to just one approach. As you can see above, taking the time to categorize your martech stack in different ways may help you achieve particular goals or better suit you when sharing that visualization with a particular leader. No matter how you categorize it, the most important thing is to ensure you regularly audit and update your martech stack. 

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.

About The Author


Megan Michuda is currently the SVP, director of marketing operations and innovation at BOK Financial. Prior to joining BOK Financial, she served as global head of marketing technology at Janus Henderson Investors. Janus Henderson was a Stackie Award winner in 2018. Megan is currently responsible for BOK Financial’s marketing technology stack, marketing automation, digital analytics, and marketing operations. In 2020, Megan’s startup Stacktus was acquired by CabinetM, a leader in martech management. Megan is now both a user of CabinetM as well as an advisor. Megan received her bachelor’s degree from Brown University and her master’s of science in technology management from University of Denver.

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B2B customer journeys that begin at review sites are significantly shorter



B2B customer journeys that begin at review sites are significantly shorter

The B2B customer journey can be a long one, especially when the purchase of expensive software subscriptions is under consideration.

“The average B2B customer journey takes 192 days from anonymous first touch to won,” according to Dreamdata in their 2022 B2B Go-to-Market Benchmarks — a statistic described by co-founder and CMO Steffen Hedebrandt as “alarming.”

But the report also indicates that this journey can be significantly sped up — by as much as 63% — if accounts begin their research at software review sites, gathering information and opinions from their peers. Journeys that originate at a review site often lead to deals of higher value too.

Fragmented data on the customer journey. Dreamdata is a B2B go-to-market platform. In any B2B company, explained Hedebrandt, there are typically 10 or even 20 data silos that contain fragments of the customer journey. Website visits, white paper downloads, social media interactions, webinar or meeting attendance, demos, and of course intent data from review site visits — this data doesn’t typically sit in one place within an organization.

“We built an account-based data model because we believe that there’s such a thing as an account journey and not an individual journey,” said Hedebrandt. “So if there are two, three or five people representing an account, which is typically what you see in B2B, all of these touches get mapped into the same timeline.”

Among those many touches is the intent data sourced from software review site G2. Dreamdata has an integration with G2 and a G2 dashboard allowing visualization of G2-generated intent data. This includes filtering prospects who are early in their journey, who have not yet discovered the customer’s product, or who have discovered it but are still searching. This creates a basis for attributing pipelines, conversions and revenue to the activity.

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“Strategically, our ideal customer profile is a B2B software-as-a-service company,” said Hedenbrandt. “B2B SaaS companies are particularly ripe for understanding this digital customer journey; their main investment is in digital marketing, they have a salesforce that use software tools to do this inside sales model; and they also deliver their product digitally as well.” What’s more, it takes twice as long to close SaaS deal as it does to close deals with B2B commercial and professional services companies.


Read next: A look at the tech review space

The Benchmarks findings. The conclusions of the 2022 Benchmarks report is based on aggregated, anonymized data from more than 400 Dreamdata user accounts. Focusing on first-touch attribution (from their multi-touch model), Dreamdata found that customer journeys where a review site is the first touch are 63% shorter than the average. In contrast, where the first touch channel is social, the journey is much longer than average (217%); it’s the same when paid media is the first touch (155%).

As the Benchmarks report suggests, this may well mean that social is targeting prospects that are just not in-market. It makes sense that activity on a review site is a better predictor of intent.

Hedenbrandt underlines the importance of treating the specific figures with caution. “It’s not complete science what we’ve done,” he admits, “but it’s real data from 400 accounts, so it’s not going to be completely off. You can only spend your time once, and at least from what we can see here it’s better to spend your time collecting reviews than writing another Facebook update.”

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While Dreamdata highlights use of G2, Hedenbrandt readily concedes that competitor software review sites might reasonably be expected to show similar effects. “Definitely I would expect it to be similar.”

Why we care. It’s not news that B2B buyers researching software purchases use review sites and that those sites gather and trade in the intent data generated. Software vendors encourage users to post reviews. There has been a general assumption that a large number of hopefully positive reviews is a good thing to have.

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What Dreamdata’s findings indicate is that the effect of review sites on the buyer journey — especially as the first-touch channel — can be quantified and a value placed on it. “None of us questioned the value of reviews, but during this process you can actually map it into a customer journey where you can see the journey started from G2, then flowed into sales meetings, website visits, ads, etc. Then we can also join the deal value to the intent that started from G2.”

Likely, this is also another example of B2B learning from B2C. People looking at high consideration B2C purchases are now accustomed to seeking advice both from friends and from online reviews. The same goes for SaaS purchases, Hedenbrandt suggests: “More people are turning to sites like G2 to understand whether this is a trustworthy vendor or not. The more expensive it is, the more validation you want to see.”

About The Author


Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.

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He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.

Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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