---
title: What is the Best Technology for Monetizing Video?
description: Discover the best video monetization technology for publishers, from ML-driven yield optimization to multiscreen delivery and revenue growth.
image: https://blog.ex.co/hubfs/2026%20Content/2026%20Blog%20Images/EXCO_Monetization-Blog_1200x630.png
---

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# What is the Best Technology for Monetizing Video?

 April 21, 2026 - by [Tammy Blythe Goodman](https://blog.ex.co/author/tammy-blythe-goodman)

![Video monetization ](https://blog.ex.co/hubfs/2026%20Content/2026%20Blog%20Images/EXCO_Monetization-Blog_1200x630.png "Video monetization ")

## A publisher's guide

With ad dollars shifting fast and AI disrupting search-driven traffic, video monetization has never mattered more — or been harder to get right. Here's what separates high-performing platforms from legacy tools, and what every publisher should evaluate before choosing a solution.

If you're a publisher or media owner asking "what is the best technology for monetizing video," you're asking the right question — and you're not alone. As digital advertising continues to consolidate around high-engagement formats, video has emerged as the premium inventory commanding the highest CPMs. But not all video monetization technology is built the same.

The difference between a legacy online video platform (OVP) and a modern, machine learning-driven solution can mean the difference between incremental revenue and transformational yield growth. This guide breaks down what video monetization technology actually does, what to look for when evaluating solutions, and how the best platforms in the market approach the challenge in 2026.

## **What does video monetization technology actually do?**

**At its core, video monetization technology connects your video inventory to advertising demand and optimizes the resulting revenue. But in practice, the best platforms do far more than serve pre-roll ads.**

Modern video monetization technology typically encompasses:

### **1. Yield optimization**

Real-time and predictive auction management that evaluates demand signals, bid dynamics, and inventory characteristics to maximize revenue per impression.

### **2. Contextual video matching**

Automatically pairing the right video content to each page, so that every placement is relevant — improving engagement, viewability, and advertiser confidence simultaneously

### **3. Multiscreen delivery**

Serving video and monetizing impressions consistently across web, mobile, CTV, and DOOH — with each environment's unique auction dynamics accounted for.

### **4. Demand source management**

Connecting publisher ad servers, direct campaigns, and programmatic demand in a unified stack — without requiring complex technical integrations.

### **5. Signal quality & data enrichment**

Standardizing and completing missing contextual signals on every bid request, so advertisers can accurately value your inventory — critical in CTV and DOOH where metadata fragmentation costs publishers premium demand.

## **Why machine learning is now the standard — not a bonus feature**

A few years ago, machine learning in video monetization was a differentiator. In 2026, it's the baseline requirement for any platform worth evaluating.

Programmatic video auctions are dynamic, high-speed environments where conditions change constantly. Win rates, floor prices, demand competition, and contextual signals all shift in real time. A static rules-based system — the engine underlying most legacy OVPs — cannot process and respond to this complexity fast enough to maximize revenue.

Machine learning models do something fundamentally different: they continuously analyze performance data across the entire publisher network, identify patterns humans could never detect manually, and make micro-optimizations across every auction. Over time, the system gets smarter, compounding the revenue advantage.

| *"A lot of what we do is using machine learning to power both the matching of a video to a page and all the decisioning and predictions that go into the programmatic auction that help with the revenue strategy."* — Shachar Orren, Co-founder & CRO/CMO, EX.CO |
| --- |

 

This dual capability — intelligent content matching paired with ML-powered yield optimization — is what separates the leading video monetization platforms from those still operating on legacy infrastructure.

## **The criteria that matter most when evaluating video monetization technology**

### **1. Does it optimize yield, or just serve ads? **

Many platforms call themselves monetization tools but are essentially ad servers with a video player attached. True yield optimization means the platform is actively working to improve your revenue on every impression — adjusting floors, evaluating demand competition, and enriching bid signals — not just passing requests to the highest available bidder.

### **2. How does it handle CTV and multiscreen? **

CTV now accounts for 80–85% of impressions traded programmatically, yet the CTV ecosystem remains fragmented — mismatched metadata, unreliable signals, and broken supply paths routinely cost publishers premium demand. The best platforms actively repair this infrastructure, ensuring data flows cleanly and consistently to buyers across every screen.

### **3. Can it scale video coverage across your entire site? **

Traditional editorial video typically covers only 20–30% of a publisher's pages — because manually produced video content is expensive and time-consuming. A platform that helps you scale video coverage across more pages (through AI-generated video, licensed content libraries, and automated content recommendations) directly expands your monetizable inventory.

### **4. What does integration actually require? **

Many enterprise OVPs require months of development work and significant upfront licensing fees. Leading modern platforms connect directly to your existing ad server without requiring a dev overhaul — and operate without fixed costs, making the ROI positive from day one.

### **5. Does it treat publisher revenue as the primary objective? **

This sounds obvious, but many video platforms are optimized for their own demand revenue — not yours. Publisher-first platforms are designed to maximize yield across all demand sources simultaneously: your direct campaigns, your programmatic partners, and additional demand the platform brings. Transparency into auction dynamics is non-negotiable.

## **What publishers are seeing with the right platform**

When publishers move from legacy OVPs to machine learning-driven video monetization technology, the results are measurable and often significant.

![What Is the Best Technology for Monetizing Video?](https://blog.ex.co/hs-fs/hubfs/2026%20Content/2026%20Blog%20Images/What%20Is%20the%20Best%20Technology%20for%20Monetizing%20Video%3F.png?width=1528&height=528&name=What%20Is%20the%20Best%20Technology%20for%20Monetizing%20Video%3F.png)

## **Why video monetization matters more than ever in 2026**

Two forces are reshaping the publisher revenue landscape right now — and both point toward video as the critical growth lever.

AI-driven traffic decline. AI-generated search summaries and zero-click discovery are reducing referral traffic to publisher sites by 20% or more. Written content is increasingly being scraped and summarized, reducing its ability to drive sustainable monetization. ([See our industry guide: “Navigating the AI Traffic Cliff”](https://content.ex.co/navigating-the-ai-traffic-cliff-ex.co)) Video, by contrast, is far harder to commoditize — the visual experience, pacing, and emotional impact of watching cannot be replicated by an AI summary.

Ad dollars shifting to digital video.As budgets continue to migrate from linear TV to connected TV, online video, and DOOH, publishers with strong video monetization infrastructure are best positioned to capture this spend. Those still relying on display-heavy strategies are competing for a shrinking slice of the pie.

Publishers who invest now in the right video monetization technology are not just protecting their current revenue — they're building infrastructure that compounds its value as the video advertising ecosystem matures.

## **EX.CO: Machine learning video monetization for media companies**

EX.CO is the machine learning-driven video technology platform built to maximize revenue for media companies across web, mobile, CTV, and DOOH. Trusted by media companies including Hearst Newspapers, Advance Local, The Arena Group, Ziff Davis, and PlayWorks, EX.CO's platform is designed around a single objective: publisher yield.

The technology includes a proprietary ML-powered yield engine, a contextual video recommendation system, an ad server purpose-built for video, a full online video platform (OVP) with no upfront fees, and multiscreen delivery optimized for CTV and DOOH programmatic complexity.

EX.CO has been recognized as Best Digital Video Monetization Program (Digiday, 2023), Best Video Platform (Digiday Media Awards, 2024), Best Sell-Side Programmatic Platform (Digiday Technology Awards, 2024 & 2025), Ad Tech Innovation of the Year (Convergent TV Awards), and Best Product or Service in the AI Features & Innovation category of the 2026 Webby Awards — with all recognition rooted in measurable outcomes for media owners.

For publishers looking to replace a legacy OVP, add CTV monetization infrastructure, or simply grow video revenue without additional development investment, EX.CO is designed to deliver results from day one.

### **Ready to see what smarter video monetization can do?**

Submit a form below to talk to our team about what video growth looks like for your specific inventory mix across web, CTV, mobile, or DOOH.

*EX․CO is the smarter video technology for media owners, harnessing the power of machine learning to maximize revenue across every screen.*

### Speak to an expert

## Recent posts

## About Tammy Blythe Goodman

Tammy Blythe Goodman is VP, Brand Marketing & Communications at EX.CO. Prior to joining EX․CO in 2022, Tammy managed global communications at Taboola, Innovid, and SpotX, respectively. She has an MFA in Film from Columbia University and a BA in Communications and Literature from American University. Tammy lives in New York City and is a proud rescue dog owner and passionate pluviophile.

[More posts by Tammy Blythe Goodman](https://blog.ex.co/author/tammy-blythe-goodman)

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