Martech vs. Adtech: What’s the Difference and Why They’re Converging

In 2011, when Scott Brinker—VP of Platform Ecosystem at HubSpot—published his first Marketing Technology Landscape Supergraphic, a visual representation of all the marketing technology (commonly known as martech) in the industry, only 150 solutions were on the chart.

Fast-forward 13 years, and there were over 14,106 listed in the 2024 edition, reflecting a 27.8% increase from the previous year and a 9,304% growth since its inception.

Like nearly every tech sector, artificial intelligence (AI) is fueling much of martech’s recent expansion and innovation.

But there’s a more fundamental reason behind its growth: the increasing demand for more efficient, data-driven, and scalable marketing solutions.

As a result, business in martech—and, in turn, advertising technology, or adtech for short—is booming.

After initially spiking in the early days of the pandemic, US B2B martech spending is expected to reach $10.11 billion USD in 2025, with 60% of respondents to a 2024 survey saying they either planned to increase or significantly increase their investment in martech.

In another survey, 28.8% of US ad agencies said they used six to seven adtech and martech tools as part of their tech stack, and 17.3% said they used more than 10. 

Even seasoned marketers who use these tools every day may wonder about the differences between martech and adtech, how they complement each other, and how they’re converging.

The lines between martech and adtech continue to blur. In this blog post, we’ll examine the key distinctions between the two and how recent advancements are bridging the gap and allowing marketers to execute more seamless, data-driven campaigns.

Understanding the Roles of Martech and Adtech

Before we get into the differences between martech and adtech, their roles, and how they’re increasingly intersecting, let’s briefly go over their core functions.

What Is Martech?

Martech refers to software and tools marketers use to manage customer relationships, automate campaigns, measure performance, and analyze data. These solutions streamline operations, enable precise audience targeting and personalization, and optimize marketing efforts across channels to improve efficiency and increase conversions.

Martech consists of various types of software and platforms that marketers use to nurture leads and customer relationships, including:

• Customer Relationship Management (CRM) software: Stores and manages customer data, tracks interactions across touchpoints, and helps optimize sales and marketing efforts.
• Marketing automation tools: Automate multi-channel campaigns, lead nurturing, audience segmentation, and performance tracking.
• Email marketing tools: Automate email workflows, personalize messaging, and track campaign performance.
• Customer Data Platforms (CDP): Consolidate and activate customer data from multiple sources to enable more personalized and targeted marketing.
• Search Engine Optimization (SEO) tools: Track rankings, analyze keywords, audit site performance, and provide competitive insights to improve search visibility.
• Social media management tools: Schedule, analyze, and optimize social media posts, monitor engagement, and integrate with paid ad platforms.
• Content Management Systems (CMS): Facilitate content creation, management, and publishing on websites, supporting SEO and digital marketing efforts.
• Analytics and Business Intelligence (BI) tools: Measure marketing performance, track KPIs, provide attribution insights, and help forecast trends.

What Is Adtech?

Adtech refers to the software, tools, and systems that agencies, brands, and publishers use to automate and optimize the buying, selling, delivery, and measurement of digital advertising. It includes platforms for audience targeting, real-time bidding (RTB), ad serving, and performance measurement across digital channels like display, video, connected TV (CTV), and digital out-of-home (DOOH).

Adtech consists of various platforms and technologies that power digital advertising, including:

• Demand-Side Platforms (DSP): Centralized platforms that enable advertisers to buy digital ad inventory programmatically across multiple ad exchanges and supply sources in real time.
• Supply-Side Platforms (SSP): Enable publishers to manage, optimize, and sell their ad inventory.
• Ad Exchanges: Digital marketplaces where advertisers and publishers buy and sell programmatic ad inventory through automated bidding and direct deals.
• Ad Servers: Host, deliver, and track digital ad placements, optimizing performance and ensuring accurate reporting.
• Data Management Platforms (DMP): Collect, segment, and activate audience data to enhance ad targeting and personalization.
• Ad Verification Tools: Monitor ad placements for fraud, viewability, brand safety, and compliance with campaign requirements.

How Martech and Adtech Are Different

Now that we’ve broken down martech and adtech, let’s explore their key differences and the unique roles they play in customer relationship management, campaign execution, and media buying.

Technology and Purpose

The primary goal of marketing is to attract, nurture, and retain customers. As such, martech centres around managing marketing processes, developing customer relationships, and building brand loyalty through software that helps execute, manage, personalize, and optimize marketing campaigns.

Adtech, on the other hand, is focused on increasing brand visibility and driving conversions. It uses audience data to target and deliver ads across digital channels in real time through programmatic advertising and other automated media-buying methods.

Another way to think about it is how they fit within the marketing funnel. While some adtech solutions are primarily used for upper-funnel tactics like brand awareness and prospecting, more sophisticated ones (like StackAdapt) are built to activate and optimize campaigns across the entire funnel, playing a role in mid-funnel retargeting and lower-funnel performance advertising. Martech, on the other hand, supports mid- and lower-funnel engagement, conversion, and retention by managing customer relationships, automating campaigns, and optimizing personalized marketing efforts.

Data Handling and Processing

Martech primarily leverages 1st-party data collected directly from customer interactions across various touchpoints, including websites, mobile apps, and point-of-sale systems. This data is typically stored in CRMs for managing customer interactions or in CDPs for unifying and activating audience data across marketing channels. This allows marketers to personalize campaign messaging and get a more holistic view of customer behaviour and preferences.

Historically, adtech has relied heavily on 3rd-party data for audience targeting and measurement. But with tightening privacy regulations and the ongoing (although often delayed) deprecation of 3rd-party cookies in many environments, there’s an increasing need for 1st-party data strategies and alternatives like contextual targeting to stay ahead of the curve. Innovative DSPs like StackAdapt have been working on solutions like this for a long time and are only getting more advanced, enabling privacy-compliant audience targeting, improving attribution modeling, and delivering better results in a cookieless environment.

Measurement and Analytics

Martech aims to provide a more comprehensive view of marketing efforts by tracking the entire customer journey—from awareness to conversion to post-conversion engagement. As such, martech metrics often focus on lead generation and attribution, customer engagement across channels, and retention and lifetime value.

Adtech, in comparison, is more focused on optimizing ad delivery, audience reach, and media spend efficiency. Key adtech metrics include impressions and reach (for visibility) and click-through rates, conversions, and cost per acquisition for measuring performance. These insights help marketers refine bidding strategies, adjust audience segmentation, and optimize ad placements to improve overall campaign effectiveness.

The Convergence of Martech and Adtech

Although martech and adtech often play similar and complementary roles, they’ve historically been associated with different stages of the marketing funnel, with adtech primarily focused on customer acquisition and brand awareness and martech driving engagement, conversion, and retention. 

Each has a role to play, and when martech and adtech aren’t aligned, it can lead to wasted time, effort, and ad spend. A 2023 Forrester study found that this disconnect can result in a 10-13% loss in resources.

Thankfully, the convergence of martech and adtech—sometimes referred to as “madtech”—is changing that, breaking down silos and enabling marketers to deliver more seamless cross-channel campaigns and get a more holistic, end-to-end view of customer interactions and performance.

Unsurprisingly, data plays a central role in this convergence.

One of the biggest benefits of martech and adtech working together is the ability to centralize customer data in a unified platform. This approach offers a more holistic view of customer behaviour, informing ad targeting and campaign optimization strategies and allowing teams to deliver consistent and personalized messaging throughout the customer journey.

For example, a marketer working for an e-commerce brand could use a DSP to target high-intent shoppers with a display ad promoting a limited-time offer. Let’s say a shopper clicks the ad and browses the website but doesn’t complete a purchase. Their 1st-party data—such as their email address collected via a pop-up—is stored in a CDP. The brand can then use that data to trigger a personalized follow-up email with a discount or product recommendations based on the items they viewed during their session, encouraging them to complete their purchase.

In doing so, marketers can seamlessly connect adtech and martech, ensuring consistent messaging across channels, improving customer engagement, and optimizing ad spend while driving higher conversions.

The Impact of AI on Marketing and Ad Technology

For years, AI algorithms have been used in adtech to determine optimal ad placements, bid prices, and targeting parameters to help advertisers maximize conversions and ROI.

Now, it’s reshaping both adtech and martech in profound ways, doing everything from automating repetitive and mundane tasks to more advanced applications like:

• Using AI-powered predictive analytics tools to tailor campaigns by forecasting customer preferences based on past behaviours.
• Automatically optimizing campaigns and execution by identifying the most effective audience segments and adjusting bidding strategies in real time based on engagement and conversion patterns.
• Fine-tuning and personalizing ad creatives by using dynamic creative optimization, which automatically adapts messaging, visuals, and calls-to-action based on audience signals and performance data.

According to a survey by Ascend2, 60% of marketers say AI and machine learning will have the biggest impact on marketing strategies over the next five years, with personalization and optimization being the most common use cases.

Martech and adtech are at the forefront of this transformation, providing marketers with deeper insights into their customers and streamlining future targeting, personalization, and campaign optimization efforts.

In this article, we’ve only scratched the surface.

To see how AI and machine learning will impact martech and adtech in the years ahead, download our guide to the top martech trends in 2025 and beyond or watch our webinar with EMARKETER and U of Digital for even more insights from industry experts.

If you want to learn more about the convergence between martech and adtech or how to optimize your marketing strategy for better campaign performance, book a call to learn more about StackAdapt.