What is MarTech?
MarTech (marketing technology) refers to the software, platforms, and tools that marketing teams use to plan, execute, measure, and optimize campaigns. The term covers everything from email automation and CRM systems to analytics dashboards and programmatic ad buying. As of 2024, the MarTech market includes over 14,000 distinct solutions, according to the annual Chief Martec supergraphic compiled by marketing analyst Scott Brinker.
The MarTech Stack
A MarTech stack is the collection of tools a company assembles to run its marketing operations. Stacks vary by company size, budget, and channel mix, but most include tools from six core categories:
- Advertising and promotion: paid media platforms like Google Ads, Meta Ads Manager, and programmatic DSPs
- Content and experience: CMS platforms, landing page builders, and personalization engines
- Social and relationships: social media management, influencer platforms, and community tools
- Commerce and sales: e-commerce platforms, CPQ tools, and sales enablement software
- Data management: CDPs, DMPs, CRMs, and data warehouses
- Management and finance: marketing attribution, project management, and budget planning tools
HubSpot, Salesforce Marketing Cloud, and Adobe Experience Cloud are among the most widely adopted enterprise MarTech platforms. Each attempts to consolidate multiple stack layers into a single suite, though most enterprise teams still integrate specialized point solutions alongside them.
Why MarTech Spending Has Grown
Gartner’s 2023 CMO Spend Survey found that marketing technology accounts for roughly 25.4% of total marketing budgets, making it the single largest line item ahead of paid media, labor, and agencies. Three factors explain the sustained investment.
1. Data Volume Outpaced Human Capacity
Modern campaigns generate data across dozens of touchpoints simultaneously. A mid-size retailer running paid search, email, social, and in-store promotions may log millions of customer events per day. MarTech tools automate the aggregation, segmentation, and activation of that data at a scale no team can replicate manually.
2. Personalization Raised Conversion Expectations
McKinsey research from 2021 found that personalization typically delivers a 10–15% revenue lift. Delivering that at scale requires tools that match the right message to the right user in real time. Platforms like Braze, Iterable, and Klaviyo are built specifically for this.
3. Channel Proliferation Created Coordination Problems
Running consistent campaigns across search, social, connected TV, email, SMS, and push notifications requires orchestration software. Without it, teams risk conflicting messages, duplicated spend, and attribution gaps. Marketing automation platforms and customer data platforms (CDPs) address this by centralizing audience data and campaign logic.
Key MarTech Categories Explained
CRM
A customer relationship management (CRM) system is the foundational record for customer data. Salesforce holds approximately 23% of the global CRM market. Marketing teams use CRM data to segment audiences, trigger campaigns, and track pipeline attribution.
Marketing Automation
Marketing automation platforms handle the rules-based execution of campaigns: send an email when a lead fills out a form, trigger a retargeting ad when a cart is abandoned, score a lead when a prospect views a pricing page. HubSpot, Marketo (owned by Adobe), and Pardot (Salesforce) dominate the mid-market and enterprise segments.
Customer Data Platform (CDP)
A CDP unifies customer data from multiple sources into a single persistent profile. Unlike a DMP, which handles anonymous audience segments for advertising, a CDP connects known customer identities across channels and systems. Segment (owned by Twilio) and mParticle are common CDP choices for mid-size and enterprise brands.
Analytics and Attribution
MarTech analytics tools range from web analytics (Google Analytics 4, Adobe Analytics) to multi-touch attribution platforms (Rockerbox, Northbeam, Triple Whale). Attribution software answers the question of which marketing touchpoints contributed to a conversion and in what proportion.
A simplified last-touch attribution calculation looks like this:
| Channel | Last-Touch Conversions | Revenue Attributed |
|---|---|---|
| Paid Search | 420 | $84,000 |
| 310 | $62,000 | |
| Organic Social | 95 | $19,000 |
| Direct | 175 | $35,000 |
Multi-touch models distribute credit across all touchpoints in a conversion path, giving a more accurate picture of channel contribution than single-touch models.
MarTech Integration and the “Stack Tax”
A persistent challenge in MarTech is integration overhead. Marketers call this the stack tax: the hidden cost of connecting, maintaining, and training teams on multiple platforms. Research from Gartner in 2023 found that marketing teams use only 42% of their MarTech capabilities on average, down from 58% in 2020.
Common integration patterns include:
- Native integrations: pre-built connectors between platforms (e.g., HubSpot to Salesforce sync)
- iPaaS tools: middleware platforms like Zapier, Workato, or MuleSoft that connect separate systems via APIs
- Data warehouses: Snowflake, BigQuery, or Redshift as a central hub, with tools reading and writing from a shared data layer
MarTech ROI Measurement
Calculating MarTech ROI follows the same logic as any marketing investment:
MarTech ROI = (Revenue Attributed to MarTech-Enabled Campaigns − Total MarTech Cost) / Total MarTech Cost × 100
Total MarTech cost includes software licensing, implementation, integrations, and staff time. A team spending $120,000 per year on its stack that generates $600,000 in attributed pipeline would report an ROI of 400%. Benchmarking is difficult because attribution models vary widely, but measuring tool utilization rates and campaign performance lift relative to a pre-tool baseline provides directional evidence of value.
Emerging Directions in MarTech
AI-Native Features Are Now Standard
AI-native features are now built into most major MarTech platforms. Salesforce Einstein, Adobe Sensei, and HubSpot’s AI tools offer predictive lead scoring, content recommendations, and send-time optimization.
First-Party Data Is Replacing Third-Party Targeting
Third-party cookie deprecation in Chrome has accelerated the shift toward first-party data. That shift has driven investment in CDPs and email list growth tools as alternatives to third-party audience targeting.
Programmatic advertising platforms are integrating directly with CDPs to enable audience activation without third-party data brokers. This pattern is called data collaboration or clean room technology. Companies like LiveRamp and InfoSum provide infrastructure for brands to share anonymized audience data with publishers and partners without exposing raw customer records.
Frequently Asked Questions
What does MarTech stand for?
MarTech stands for marketing technology. The term covers the full range of software and platforms that marketing teams use to plan, execute, measure, and optimize campaigns, from CRM systems and email automation to analytics dashboards and programmatic ad buying.
What is a MarTech stack?
A MarTech stack is the specific set of tools a company uses to run its marketing operations. Most stacks include tools across six categories: advertising and promotion, content and experience, social and relationships, commerce and sales, data management, and marketing operations.
How much do companies spend on MarTech?
According to Gartner’s 2023 CMO Spend Survey, marketing technology accounts for roughly 25.4% of total marketing budgets, making it the largest single line item ahead of paid media, labor, and agencies.
What is the MarTech “stack tax”?
The stack tax is the hidden cost of integrating and maintaining multiple MarTech tools. Gartner found in 2023 that marketing teams use only 42% of their MarTech capabilities on average, meaning a significant portion of software spend goes underused.
What is the difference between a CDP and a DMP?
A customer data platform (CDP) unifies known customer data across channels into persistent individual profiles. A data management platform (DMP) handles anonymous audience segments, primarily for advertising targeting. CDPs are suited for personalized one-to-one marketing; DMPs are used for broad audience buying at scale.