14,106 Martech Tools Point to Three Big Trends
Revamping the martech landscape isn't merely about collecting logos—it's a pathway to deeper research. This year, a staggering 14,106 vendors emerge in the curated overview, marking a 27.8% growth from last year. While these numbers may seem overwhelming, they prompt three important trends.
What to Read Next
- TripleLift Announces Partnership with Attain to Unify Context and Commerce
- Seedtag Partners with IRIS.TV to Expand Contextual Signals for CTV Targeting
- Magnite, Cognitiv Announce Deep Learning Integration for Real-Time Curation
- Dscout Announces Integration with HeyMarvin
- Comscore Launches Program-Level Capabilities within CCM
Every year around May the Marketing Technology Supergraphic is released. This year no less than 14,106 vendors surfaced in the curated overview. That is a 27.8% growth rate compared to last year. It is the 13th consecutive year of growth. Those numbers are daunting, but at the same token the question arises: “How are these numbers helping me do a better job?” Good question.
Based on this year’s research there are three martech trends to keep an eye on.
- Martech Consolidation and Growth paces differ
- Martech Atomisation: The Role of Long Tail Apps
- GenAI boosts Martech Growth
1. Martech Consolidation and Growth paces differ
For the past decade trend watchers predicted a huge consolidation in martech. We are not saying it will never happen, but the numbers do not support the yearly predictions. Sure, consolidation does happen, but with only 263 products removed in 2024 that is a very modest force in martech. That’s only a 2.1% churn rate from last year’s cohort. By looking at the reasons solutions were removed, we get a feel for the consolidation dynamics.
- 76 – Out of Business
- 61 – Acquired & merged
- 61 – URL change, due to merged products or modules
- 33 – No longer martech, now Fintech, EduTech, etc.
- 32 – Now agency, giving up software ambitions
Source: The State of Martech 2024
At the same time, 3,331 new tools were added to the overview. The low churn and the high growth rate could originate largely from one and the same reason: The costs to build and deploy software are not high and continue to plummet. No huge investments are needed to launch or maintain martech tools. Generative AI drives these costs — in time, talent, and capital — even further down and faster.
The low costs allow startups, scale-ups, creators, digital nomads, inventors, experimenters, Product Hunters, Betalister, and entrepreneurs to keep developing new martech in the long tail. The low costs allow them also to shift into a sustainable low-overhead, lights-on mode rather than spectacularly failing.
How does this help you? Know that martech growth outpaces martech consolidation by far. As a result, we can establish that “consolidation is not a strategy”. Instead, we’ll need to get to terms with small tools being an intricate part of our marketing technology stack, next to the larger tools. In short: stop waiting for the “One-Tool-That-Does-It-All-For-Marketing”. Try out new tools regularly. It will boost your understanding of what is new and what a commodity. You’ll be an excellent sparring partner in no time!
2. Martech Atomisation: The Role of Long Tail Apps
Since smaller apps are prevalent, let’s delve into that more. Our research shows that small tools are here to stay and are (more) popular. There are some astounding facts about the apps in the Long Tail.
Looking at the frequency of tool mentions in 1,500 stacks (in %) in our database, we see that the distribution of head, torso, and long tail apps has remained relatively constant over the past seven years. We have enriched our dataset with data from Clearbit and G2. Clearbit data, which gave us insights into the approximate age, size, and revenue of these martech companies. G2 data gave us insights into their ratings and reviews: how well-liked they are by the marketers who use them.
The outcome is that martech solutions with lower revenue receive higher ratings. Also, younger martech solutions tend to have higher G2 ratings than larger solutions. An explanation can be that the user of small apps is also the client (buyer). Larger solutions are selected by the client ‘on behalf of’ the actual users, resulting in mismatches and corresponding reviews.
Smaller apps often have been dismissed as ‘point solutions’. In daily reality, they play a pivotal role in completing larger solutions in a marketing technology stack to drive desired customer experiences. Specialist apps perform one task intuitively and seamlessly integrated with their ecosystem partners. This phenomenon we could describe as Martech Atomisation as small apps behave like atoms in the ‘ecosystem’ of a larger molecule.
Also here Generative AI is taking the atomisation phenomenon to a whole new level. Who knows we’ll see soon the first 1-person, $1 billion company in the years ahead. Don’t forget it only took 50 people to build WhatsApp and when Facebook purchased Instagram in 2012, the company had only 13 employees.
The simple insight is that both centre or anchor platforms and specialist apps co-exist in martech stacks. This means you need to have or design a martech strategy and roadmap. One that shows how all apps are licensed, integrated, adopted, and decommissioned. It is strongly recommended that there is one person or team who oversees the martech stack, call it a Martech Architect, Customer Custodian, or Stack Owner.
3. GenAI Boosts Martech Growth
The impact of Generative AI on martech has been felt clearly in the last year. It has given the martech landscape a real turbo boost in multiple ways.
- Martech Growth
Generative AI-based accounts for 77% of the new martech tools in 2024. - Martech Costs
Generative AI supports cheaper, easier, and faster coding of new apps. - Martech Innovation
Generative AI created a whole new category: GPTs.
2,324 newly added tools are GenAI-based in 2024 of which 846 have embedded GPT in their products. OpenAI opened the GPT Store in January 2024 to allow users to create custom versions of ChatGPT based on company-specific data, instructions, knowledge, and documentation.
Astonishingly, we found 3,958 martech-related GPTs that were stand-alone, i.e. not part of a proposition with a pricing model, login, and domain name. As such, they were left out of the 14,106 martech vendor overview. That does not mean they aren’t valuable for many marketing use cases. That is Martech Atomisation at its finest, right there!
Generative AI is introducing a wealth of opportunities and use cases. Sure, in 53% of the cases, Generative AI is applied in the usual suspect use cases of creating copy, images, and videos.
But the impact is also felt elsewhere in martech. On closer inspection, looking at the top 14 of the 49 martech subcategories, we see that 7 of the 14 are not related to content use cases.
Also Read: Generative AI Bridges The Gap Between Hype and Reality
Take a look at the GenAI-based use cases for Sales. There are tools for sales support, such as client meetings, notes, supporting material (n=137), Lead Sourcing & Outreach (n=65), Lead Scoring (27), and Pitch Decks (n=18). And what about Business/Customer Intelligence & Data Science? There are interesting GenAI-based tools that offer Data Infrastructure, Storage & Unification (n=65) Data Interpretation & Chat with Data (n=37), or Data Sourcing & Extraction (n=11).
In all that excitement, we realise that Generative AI is at the beginning of the technology hype cycle. There is research that gives a good impression of the state of GenAI’s maturity in marketing. While some Generative AI use cases are used on a daily to monthly basis successfully, not all Generative AI use cases are equally successful or tried out yet. There is still much to be learned! We’d recommend keeping track of all the (un) successful GenAI use cases in your company using the structure MKT1 used in their survey.
(Look out for Part 2 – Composability is here to stay on May 20)
