Ask The MarTech Matrix

What is MarTech?

MarTech (marketing technology) is the stack of software brands and agencies use to plan, execute, measure, and optimize marketing — from your email platform and CRM to attribution tools, ad platforms, personalization engines, and AI-driven creative. The category has exploded: the MartechMap now tracks 14,000+ tools. Most marketers use 20–50 of them, and the work is less about picking individual tools and more about getting them to talk to each other.

How do brands choose the right MarTech vendor?

Start with the business problem, not the category. Most vendor selection fails because the buyer started with “we need an attribution tool” instead of “we don’t know which channels actually drive new customers.” Once the problem is clear, three filters matter: does it integrate with your existing stack, can you see real outcome data (not just vendor case studies), and is the team behind it people you’d want to work with for the next three years. Skip the analyst-grid theater. Talk to actual customers.

What’s the difference between MMM, MTA, and incrementality testing?

Three measurement approaches, three different questions. Marketing Mix Modeling (MMM) uses statistical regression on top-down data to answer “what’s working at the macro level?” Multi-Touch Attribution (MTA) uses user-level data to answer “which touchpoints contributed?” — but it’s been gutted by privacy changes and walled gardens. Incrementality testing runs controlled experiments to answer “would this conversion have happened anyway?” Most sophisticated programs use all three: MMM for budget allocation, incrementality for validation, MTA only where the data is clean.

What is incrementality testing in marketing?

Incrementality testing isolates the true lift of a marketing investment by comparing exposed groups to controlled holdout groups. The classic version is a geo holdout — turn ads off in a matched region for 4–6 weeks, then measure the gap in conversions vs. the region where ads stayed on. The harder it is to fake, the more reliable the answer. ROAS and last-click attribution can’t tell you what would have happened without the ad. Incrementality can. The trade-off: it’s slower and requires teams to give up some near-term spend to learn.

How can brands measure marketing without third-party cookies?

Three plays, used together. First: invest in first-party data — accounts, email, loyalty, on-site behavior, anything you own outright. Second: use modeled data — MMM and incrementality don’t depend on individual-level cookies. Third: use clean rooms and ID partnerships — Ads Data Hub, Amazon Marketing Cloud, and walled-garden audiences let you measure within their environment without exporting individual data. The brands winning treat measurement as a portfolio of methods, not a single source of truth.

What is connected TV (CTV) advertising?

CTV advertising places video ads on streaming services delivered through internet-connected TVs — Roku, Fire TV, smart TVs, gaming consoles, and apps like Hulu, Disney+, Tubi, Pluto. Unlike linear TV, CTV is addressable: brands can target specific audiences and measure outcomes with digital-style tracking. The ecosystem is fragmented across dozens of platforms and inventory sources, which is why working with experts who have direct publisher relationships matters more than just plugging into a DSP.

What is programmatic DOOH (digital out of home)?

Programmatic DOOH is the automated buying of digital out-of-home media — billboards, transit displays, gym screens, gas-pump TVs, restaurant menu boards — through demand-side platforms. The screens are connected, the inventory is dynamic, and ad serving can be triggered by location, weather, time of day, traffic data, or audience proximity. The format works for awareness at scale and increasingly for performance when paired with mobile retargeting and footfall measurement.

How does AI personalize eCommerce experiences?

AI personalization works across three layers: discovery (which products to surface based on intent signals), presentation (site copy, hero images, and product order per visitor), and post-purchase (replenishment, cross-sell, retention triggers). The brands getting it right segment shoppers into 8–20 high-confidence cohorts and serve each a tuned version — pure 1:1 personalization is expensive, fragile, and rarely measurably better than tight cohort targeting.

Why is ROAS misleading, and what should performance marketers measure instead?

ROAS measures revenue against ad cost but ignores three things: incremental contribution (would the customer have bought anyway), gross margin (a 4× ROAS at 20% margin loses money), and lifetime value (a discounted first purchase can have great ROAS and terrible LTV). The fix isn’t to throw ROAS out — it’s to layer profit-based metrics (contribution margin per acquisition), incrementality lift, and payback period on LTV alongside it. Optimize against profit, validate against incrementality.

How can eCommerce brands use UGC at scale?

User-generated content at scale isn’t about reposting customer photos — it’s about building a creator network you can brief, source from, and measure. The brands winning treat UGC like a content engine: a steady-state roster of creators producing on-brand assets tested across paid social, email, PDPs, and retention. The investment pays back when UGC outperforms studio creative in paid (which it usually does) and reduces creative production cost per asset.

How can brands improve eCommerce site speed and conversion?

Three places to look. Core Web Vitals: largest contentful paint, interaction to next paint, cumulative layout shift — get these green and Google rewards you with rankings. Time to interactive: the moment your site is actually usable, not just visible — heavy images, third-party scripts, and bloated frameworks are the usual culprits. Edge delivery: moving rendering closer to the user via CDN-level personalization can cut mobile load time in half. Every 100ms shaved correlates with measurable conversion lift.

What is “Complete the Look” merchandising?

Complete the Look (CTL) shows shoppers full outfits or coordinated product sets instead of individual items — across PDPs (“here’s what works with this jacket”), landing pages (seasonal looks, trend stories), and ad creative. For apparel and home goods, CTL drives higher average order value, lower returns, and clearer brand storytelling. The technology side maps trends, color theory, and brand-specific style rules to your live product catalog.

Have a different question?