What Is AdTech? How Paid Advertising Works End to End

AdTech means advertising technology: the software and systems used to buy, sell, deliver and measure advertising. Start with the job each system performs, then trace how an ad opportunity becomes a delivered ad and a measured business outcome.

AdTech, short for advertising technology, is the software, infrastructure, data systems, and technical standards used to plan, create, buy, sell, deliver, verify, measure, and optimize paid advertising. Programmatic advertising and real-time bidding are part of AdTech, but neither term covers the whole category.

At AdManage, we work in one of the layers those diagrams often leave out: the campaign-operations work that turns approved creative and media decisions into accurately configured ads. That vantage point matters because it reveals a more useful way to understand the industry. By the end of this guide, you'll be able to map the full advertising system, tell its overlapping acronyms apart, and identify which kind of technology solves which problem.

Which Part of AdTech Are You Asking About?

These are roles rather than one-product labels. A single vendor may cover several layers, and a tool name alone does not explain which responsibility it owns.

The shortest useful definition: AdTech is the operating system behind paid advertising, from the first campaign plan to the final measurement and billing record.

This guide explains the ecosystem by responsibility, then works through an open-web auction, platform differences, measurement and practical stack selection. AdManage is included with our role as the publisher disclosed.

How AdTech Supports the Full Advertising Lifecycle

Think about a single advertisement before it becomes an impression. Someone plans a budget and audience. A creative team produces files and copy. An operator maps those assets to campaigns, placements, URLs, and tracking. Buying and selling systems decide where the ad can run. Serving technology delivers it. Privacy systems govern which data and signals may travel. Verification tools inspect quality. Measurement systems assign credit and estimate impact. Finance teams reconcile costs.

That is one lifecycle, but it contains several distinct jobs.

The same lifecycle can involve different systems depending on the inventory, buying method and channel. Not every ad is bought in an open real-time auction.

That job-based view also exposes the first common category error: the work of advertising and the technology of advertising aren't the same thing.

AdTech vs. MarTech vs. Programmatic vs. AdOps

These terms overlap, which is why a neat one-line boundary usually falls apart under scrutiny.

The simplistic version says AdTech is paid and MarTech is unpaid. That doesn't hold. A CDP can activate an audience into paid media, and an AdTech platform can contain customer-data or automation features. A better distinction is organizational: AdTech centers on advertising execution and monetization, while MarTech centers on broader marketing and customer relationships.

Programmatic is a method, not the entire landscape. It uses software and rules to automate buying, selling, allocation, or execution. RTB is narrower still: an impression opportunity is offered and evaluated in real time.

All RTB is programmatic, but not all programmatic is RTB. OpenDirect exists specifically for automated guaranteed direct sales without an RTB auction, while Google's deal-term documentation distinguishes auction, fixed-price, and guaranteed structures.

AdOps is the human and operational discipline that makes the system work: validating creative, configuring campaigns, checking permissions, managing naming and URLs, troubleshooting rejections, and reconciling mismatched numbers. AdTech supplies the systems. AdOps applies them.

Once those terms are separated, another misconception becomes visible. There isn't one universal advertising supply chain.

How AdTech Works Across Three Advertising Environments

The same advertiser can buy an open-web display impression, a Meta feed placement, and a sponsored retail-search result. All three are advertising. All three use AdTech. Underneath, they work differently.

1. The Open Web and Open Internet

Independent publishers expose inventory through publisher ad servers, SSPs, exchanges, header-bidding systems, direct deals, or some combination of them. Advertisers may buy through DSPs, agencies, managed services, or direct integrations.

This is the environment where OpenRTB, the detailed OpenRTB 2.6 specification, and the associated AdCOM data model matter most.

2. Walled Gardens

Google Search, Meta, TikTok, and similar platforms usually control the user environment, inventory, identity signals, auction logic, optimization, interface, and reporting. Advertisers configure campaigns through the platform's UI or API. They don't ordinarily submit a standard OpenRTB bid into a Meta feed or Google Search auction.

Native campaign-management APIs let advertisers manage supported objects inside their platforms. They should not be confused with the real-time bidding protocols used in an open-web auction.

3. Retail and Commerce Media

A retailer can combine shopper data, sponsored listings, display and video inventory, off-site activation, in-store screens, and transaction reporting. Access can be direct, managed, self-service, or programmatic. The IAB's retail-media curriculum covers on-site, off-site, in-store, CTV, and DOOH placements, which is a much wider frame than sponsored search alone.

One campaign can cross three operating environments without using the same auction, identity, reporting, or verification model twice.

That is why the industry has so many components. Each box solves a narrower job inside one or more of these environments.

The Core AdTech Components and What They Do

Demand-Side Platforms and Other Buy-Side Systems

A demand-side platform (DSP) helps advertisers or agencies evaluate and buy media opportunities across available supply. It can apply targeting, pacing, frequency, creative eligibility, inventory controls, and bidding logic. A DSP is not automatically the place where creative is produced or where causal business impact is measured.

Search and social platforms are also buy-side AdTech, but they aren't conventional independent DSPs. They provide access to inventory inside their own environments and may bundle buying, serving, optimization, identity, and measurement.

An agency trading desk is a service and operating layer that buys programmatic media using one or more platforms. Amazon's agency trading desk explanation correctly treats it as a team or managed service, not another exchange.

SSPs, Ad Exchanges, Ad Networks, and Ad Servers

A supply-side platform (SSP) helps publishers make inventory available, set floors and access rules, manage deals, filter buyers, and improve yield.

An ad exchange supplies transaction and auction infrastructure. An ad network traditionally aggregates or packages inventory and resells access under commercial terms. Modern companies may combine SSP, exchange, network, and managed-service functions, so the label on a homepage doesn't always reveal the actual economics.

A publisher ad server manages inventory, direct-sold line items, priorities, pacing, forecasting, creative delivery, and final allocation. An advertiser ad server focuses on the advertiser's creative, rotation, tracking, and cross-publisher reporting. Both can participate in the same delivered ad while representing different parties.

Data, Identity, Privacy, and Clean Room Systems

A DMP traditionally stores pseudonymous audience profiles for media targeting, often around cookies or device identifiers and shorter retention. A CDP builds more persistent profiles from first-party customer data and known relationships. A CMP collects or manages privacy choices and sends related signals.

A data clean room is a controlled environment for approved matching or computation with restricted raw-data access. It isn't automatic anonymization, proof of consent, or a compliance certificate. Current interoperability work includes PAIR, ADMaP, and the IAB Tech Lab's work on secure matching and measurement.

Verification, Transparency, and Measurement Systems

ads.txt and app-ads.txt let publishers and app developers declare authorized sellers. sellers.json and the SupplyChain object help buyers see sellers and intermediaries in a path. These standards improve authorization and transparency. They don't guarantee that traffic is human, an impression is viewable, or a campaign is effective.

Verification systems address viewability, invalid traffic, malware, brand safety, and brand suitability. Measurement systems address delivery, attribution, lift, reach, frequency, MMM, and reporting. Those are related jobs, but they answer different questions.

Creative Management and Campaign Operations Systems

Creative management, DCO, asset libraries, feeds, localization, approval, bulk launching, naming, UTMs, and QA sit before and around media buying. They turn decisions into executable campaign objects.

That layer is easy to overlook because it doesn't own the auction. Yet a media plan cannot produce an impression until the assets, destinations, settings, identities, and tracking have been configured correctly.

Now we can follow the best-known part of the system without mistaking it for the whole.

How Real-Time Bidding Works in an Open-Web Ad Auction

An accurate RTB explanation can still be readable. The useful version has ten steps.

1. A media experience creates an ad opportunity. A page, app, stream, or player identifies a potential placement.
2. The publisher starts monetization logic. That may involve an ad server, header-bidding wrapper, SSP, mediation layer, direct line item, or deal-specific path. Not every opportunity becomes an open-auction request.
3. A bid request is assembled. In OpenRTB, it can contain format, dimensions, floor, currency, site or app context, device information, privacy signals, deal IDs, supply-chain data, and tmax, the available response time.
4. Eligible buyers receive it. Routing can depend on geography, format, contracts, deals, privacy, quality, capacity, and technical compatibility.
5. Each DSP checks campaign eligibility. It evaluates targeting, creative approval, pacing, budget, frequency, deal rules, predicted value, and bid strategy.
6. The DSP bids or declines. A response can include price, creative information, advertiser domain, deal ID, and rendering or notification fields.
7. The sell side filters responses. Late, malformed, ineligible, below-floor, blocked, or incompatible bids can be removed.
8. Auction and ad-server rules select a candidate. The highest eligible programmatic bid may win its auction, but the publisher ad server may still compare it with guaranteed campaigns, sponsorships, direct line items, or other demand.
9. The ad still has to render or play. A win isn't yet a served, measurable, or viewable impression.
10. Events, reports, billing, and optimization follow. Different systems may record the request, bid, win, serve, render, view, click, conversion, revenue, and invoice at different times.

Trace the Handoff When Advertising Numbers Disagree

Start with one object or event and agree the question. A bid, a win, a rendered impression, a click, an attributed conversion and a paid order are different records.

Keep the original report settings and compare matching periods before concluding that a system is wrong. A discrepancy log makes the next investigation concrete; it does not turn an attributed conversion into proof of incremental revenue.

A simplified object map looks like this:

Request: id -> imp[] -> format + floor + deal -> site/app -> device -> privacy -> supply chain -> tmax
Response: id -> seatbid[] -> bid[] -> impid + price + creative + advertiser domain + deal

OpenRTB 2.6 now receives rolling, date-coded, non-breaking updates rather than waiting for a simple 2.7 release. Google's Authorized Buyers platform ended support for its proprietary RTB protocol in 2025 and continued updating its OpenRTB extensions in 2026, as recorded in the Authorized Buyers release notes.

And no, every auction doesn't take exactly 100 milliseconds. Google's RTB test guidance documents request-specific deadlines from 80 to 1,000 milliseconds depending on format and auction type.

How First-Price Auctions and Price Floors Work

In a simplified first-price auction, the winner pays its submitted price. Google's move to a unified first-price auction for non-guaranteed demand made bid shading more important: buyers try to bid below their maximum estimated value without losing too many auctions.

Publishers can use floors to set minimum acceptable prices. Prebid's floor documentation explains both static and dynamic approaches.

How Header Bidding Changes Publisher Auctions

Header bidding lets a publisher ask several demand partners for bids before or alongside the main ad-server decision. It can increase competition and visibility, but it adds latency, consent coordination, duplicated supply paths, discrepancy risk, and maintenance. It now runs client-side, server-side, in apps, and in video environments, as the Prebid introduction makes clear.

The biggest correction is simple: “highest bidder wins” is a shortcut, not a reliable description. Once filters, floors, deals, quality, priority, and rendering are included, price is only one condition of delivery.

Why Programmatic Advertising Is More Than Real-Time Bidding

Programmatic describes automation. The transaction can still be auction-based, fixed-price, reserved, or direct.

So the accurate sentence is: programmatic advertising automates buying and selling; some programmatic transactions use impression-level RTB, while others automate fixed-price or guaranteed direct deals.

That distinction matters even more once we leave open-web display, because each channel uses a different combination of auctions, direct access, SDKs, content systems, and measurement rules.

How AdTech Works Across Search, Social, CTV, Retail, and More

In paid search, the platform owns the query surface and auction. In paid social, the platform also controls most of the environment, from audience eligibility to reporting. That means a campaign-management tool can automate setup through an API without becoming the auction itself.

In apps, SDKs and operating-system policies become central. A mobile measurement partner may connect campaign interactions with app installs and post-install events, but only within the permissions and privacy frameworks that the device and platform allow.

CTV introduces ad pods, server-side insertion, household-level identity, duplicate reach across apps, and uneven signal quality. The IAB's CTV measurement guide documents this fragmentation, while the Open Measurement SDK program and the IAB's OM SDK overview show the effort to standardize measurement across mobile, video, and connected TV. Video delivery also relies on standards such as VAST.

DOOH breaks the browser mental model. IAB Tech Lab's OpenRTB guidance for DOOH notes that screens vary in size and setting, connectivity can be intermittent, and impressions may be modeled from one-to-many screen plays. Podcast measurement has its own distinction between downloads, audience, and ad delivery in the podcast measurement guidelines.

Creator advertising adds content licensing, identity authorization, paid amplification, affiliate measurement, and brand safety to the stack. AI search and conversational advertising add another emerging surface, but forecasts and experiments aren't yet one settled transaction standard.

The channel changes the plumbing. Privacy changes which signals can move through it.

Why There Is No Universal Cookieless Advertising System

The old story said third-party cookies were disappearing and one privacy framework would replace them. The 2026 position is messier.

• Safari has blocked third-party cookies by default since 2020, documented in WebKit's full third-party-cookie blocking announcement and broader tracking-prevention overview.
• Firefox's Total Cookie Protection rollout partitions cookies by site, alongside Enhanced Tracking Protection.
• Chrome’s third-party-cookie controls differ from Safari and Firefox. Check the current browser policy and user settings instead of assuming one universal cookie-removal timeline.
• Changes to proposed privacy APIs also affect the available integrations. A browser proposal, supported interface and deployed measurement method are different things.

Apple's privacy and data-use rules require permission through App Tracking Transparency before covered cross-app or cross-company tracking and access to the IDFA. Apple also rejects fingerprinting and the idea that hashing creates a loophole.

Privacy Rules Operate Across Six Layers

1. Law: GDPR, state privacy laws, children's privacy, and sector-specific rules.
2. Browser: Cookie isolation, storage controls, link protections, and anti-fingerprinting.
3. Operating system: ATT, advertising identifiers, and privacy-preserving attribution.
4. Platform policy: Audience restrictions, data access, advertising terms, and measurement limits.
5. Consent and preference signaling: CMPs, TCF, GPP, and GPC.
6. Technical governance: Data minimization, retention, access control, clean rooms, encryption, and contracts.

The Global Privacy Protocol transports privacy and consumer-choice signals. It doesn't determine the correct legal basis. California's Attorney General says covered businesses must honor Global Privacy Control as a valid opt-out request. The EU's Digital Services Act adds ad-transparency and targeting restrictions, including protections for children and sensitive data in covered circumstances.

Why Identity Matching Does Not Equal Permission

Deterministic matching connects known relationships, such as an authenticated account or customer-provided identifier. Probabilistic matching infers a likely connection from patterns. Contextual advertising targets the environment rather than a known person. First-party audiences come from a direct relationship.

None of those labels automatically grants unrestricted use. “First-party” describes where data came from. “Deterministic” describes match logic. “Hashed” describes a transformation. It doesn't describe permission. Purpose, contracts, policy, and law still apply.

And even when data can be used, the next trap is assuming that every recorded event represents the same degree of exposure or impact.

How an Ad Impression Moves From Opportunity to Outcome

Opportunity -> request -> eligible bid -> auction win -> served -> rendered
-> measurable -> viewable -> attentive exposure -> interaction -> conversion
-> attributed outcome -> incremental outcome

Each arrow can fail.

Served means a system recorded delivery under its own counting rules. Rendered means the ad began appearing or playing. Measurable means the measurement system received enough valid information to assess a property such as viewability. Viewable means the impression met an agreed threshold.

Viewability is an opportunity-to-see measure with format-specific standards. It is different from a recorded serve, attention, a click or a business outcome.

Check the applicable measurement standard and implementation for the format. A viewable impression does not establish that someone paid attention.

Attribution decides where to assign credit. Incrementality estimates whether advertising created an outcome that would not otherwise have occurred.

Attribution may use last-click, view-through, or platform-specific models. Incrementality uses holdouts, geo experiments, lift studies, causal models, or MMM. Google's Meridian documentation describes a causal-inference MMM approach using geo-level data, controls, response curves, and prior information.

Why Metric Denominators Matter

Google's CTR definition is clicks divided by impressions. TikTok's basic metric documentation includes both click-based and impression-based conversion rates. A report that says “conversion rate” without naming its denominator is incomplete.

Suppose five million served impressions are 80% measurable and 70% of measurable impressions are viewable:

Measurable = 5,000,000 x 0.80 = 4,000,000
Viewable   = 4,000,000 x 0.70 = 2,800,000

Only 56% of served impressions are both measurable and viewable. That still doesn't prove 2.8 million people consciously noticed the ad.

ROAS has a similar interpretive limit. It divides attributed revenue by spend. It isn't profit because it leaves out product cost, returns, fulfillment, payment fees, discounts, and other variable costs.

Measurement quality is not a side issue. It changes how much of the market's apparent scale is actually useful.

How Big Is the AdTech Market?

The IAB and PwC reported **294.6 billion** in U.S. internet advertising revenue for 2025. The same [IAB revenue report announcement](https://www.iab.com/news/digital-ad-revenue-climbs-to-nearly-300b-as-iab-celebrates-30-year-anniversary/) reported 117.7 billion for social, 114.2 billion for search, 81.6 billion for display, 78.0 billion for digital video, 63.4 billion for commerce media, 2.9 billion for podcast, and 162.4 billion for programmatic.

Don't add those categories together. Social video can appear in both social and video, for example. The research is based on company-reported and public data, and PwC doesn't audit every supplied figure.

WPP Media's 2026 midyear forecast projected $1.3 trillion in global advertising revenue excluding U.S. political advertising, with Alphabet, Meta, and Amazon controlling 57.6% outside China. That is a forecast, not completed-year actuals.

In Europe, the IAB Europe AdEx Benchmark reported roughly €131 billion in 2025 digital-advertising revenue. The IAB's 2026 U.S. buyer outlook surveyed more than 200 brand and agency buyers and forecast 9.5% spend growth. Again, a buyer survey forecast isn't the same evidence as revenue actuals.

Where the Programmatic Advertising Dollar Goes

The ANA's Programmatic Media Supply Chain Transparency Study examined 21 advertisers and estimated that 36 cents of each dollar entering a DSP reached an ad effectively delivered to a consumer.

It would be wrong to say AdTech companies simply took the other 64 cents in fees. The gap also included low-quality inventory, non-viewable delivery, invalid traffic, duplicated supply paths, data and verification costs, and inefficient buying. It was a study sample, not a universal audited ratio.

That mix of scale, concentration, and opacity helps explain why AI interfaces and regulatory scrutiny are arriving at the same time.

How AI Is Changing AdTech

Machine learning already supports bidding and budget allocation, outcome prediction, contextual classification, fraud detection, anomaly detection, creative selection, feed enrichment, recommendations, and reporting. Generative systems add copy, image, video, and natural-language workflow interfaces.

“Agentic” systems aim to perform multi-step work: interpret a brief, discover capabilities, configure campaigns, select approved actions, monitor outcomes, and produce records. The IAB Tech Lab's AAMP initiative is developing foundations, protocols, and trust mechanisms for this emerging layer.

That doesn't mean agents have replaced DSPs, operators, or media buyers. Standards can define how software asks for and performs work without making every vendor's models, controls, or business logic identical.

Why AdTech APIs Need Date Stamps

Campaign-management APIs change over time. Check the current release notes, supported version and deprecation date for the integration you actually use rather than treating a version listed in an evergreen article as permanent.

A campaign-management API and an RTB protocol solve different jobs. Record which interface, operation and version the implementation actually depends on.

How Vertical Integration Changes AdTech

The U.S. District Court's Google adtech opinion distinguished open-web display technology from closed platform environments. The Department of Justice summary described the ruling as a victory in the publisher ad-server and ad-exchange markets.

In Europe, the Commission’s AdTech case page documents its 2025 decision and fine. The competition question concerns roles across the chain, rather than treating all advertising products as the same market.

The practical lesson isn't “large platforms are one thing.” It is that a single company can own inventory, identity, buying tools, selling tools, auction logic, and measurement. Platform reporting and independent verification are therefore different evidence models.

For a buyer, all of that complexity leads to a more grounded question: which exact job does a proposed tool perform?

How to Choose an AdTech Stack Without Paying for Overlap

Start with the job, not the acronym or the vendor's preferred category.

1. Identify the Advertising Environment

Are you operating in paid search or paid social, the open web, apps, CTV, retail media, publisher monetization, DOOH, audio, or several at once?

2. Define the Problem the Tool Must Solve

Is the constraint planning, creative production, campaign setup, buying, selling, serving, identity, consent, verification, measurement, optimization, reporting, or finance?

3. Identify the Media Transaction

Do you need a native platform auction, open RTB, a private marketplace, a preferred deal, programmatic guaranteed, a direct insertion order, or a managed retail service?

4. Audit Data Sources and Permissions

What data enters the system? Who collected it? Which identifiers are used? How are consent, retention, deletion, and access enforced?

5. Decide What Needs Independent Verification

Delivery, viewability, invalid traffic, brand suitability, conversion, lift, reach, frequency, and billing aren't interchangeable evidence needs.

6. Calculate the Full Cost of Ownership

Include media markup, percentage-of-spend fees and subscriptions, data, verification, managed service, minimums, overages, storage, API access, implementation, staff time, and migration.

7. Inspect Campaign Operations Controls

Look for campaign previews, templates, naming and UTM controls, approvals, permissions, retry handling, partial-failure reports, audit logs, idempotency, exports, and account limits.

8. Check Whether You Can Test Incrementality

Holdouts, lift tests, geo experiments, stable baselines, MMM exports, and test-control reporting matter when the business question is impact, not just credit.

9. Plan for Platform and API Changes

Check API cadence and deprecation windows, data portability, creative portability, documentation, contract exit terms, and the fallback manual workflow.

Practitioner discussions show why these questions matter. AdOps contributors openly say the labels are loose and sometimes describe the ecosystem as layers of middlemen. Others seek books and terminology resources or discuss end-to-end AdTech pain. Those are anecdotes, not representative studies, but they reflect a consistent procurement need: make every product prove its job and boundary.

The same applies to product reviews. A G2 review page for Madgicx and Trustpilot reviews surface buyer concerns about learning curve and reliability, while vendor pages from Smartly, Hunch, Hunch's comparison content, Madgicx, Adnova, and Motion show that creative, optimization, bulk launch, and intelligence products sell different primary jobs.

This is the point where the missing campaign-operations layer becomes commercially important.

Where Campaign Operations and AdManage Fit in AdTech

Buying technology is only one part of AdTech. Before an auction can evaluate an ad, someone has to turn assets and decisions into valid campaign objects.

That work includes:

• Matching creative to accounts, formats, and placements.
• Applying copy, landing pages, calls to action, names, and tracking parameters.
• Preserving existing identifiers or social proof where the platform supports it.
• Previewing, approving, scheduling, and launching many variations.
• Handling permissions, rejections, retries, and partial failures.
• Keeping the structure consistent across buyers, brands, markets, and accounts.

Operational work includes checking inputs, preparing objects, reviewing identity and tracking, publishing, and reconciling the result. The workload can span several platforms and teams.

More creative output creates additional preparation and review work. It does not by itself establish more profitable advertising.

Before buying another tool, measure the repeated task and the handoff it would change. Compare actual outputs, exceptions and review effort.

AdManage sits in this advertiser-side activation and operations layer. Our public homepage positions the product around bulk ad launching and ad management across supported native platforms. The public documentation covers product workflows, while pricing and the comparison hub describe the commercial model and category positioning.

More specifically, the public content connects AdManage to ad creative naming conventions, UTM governance for Meta ads, alternatives to working entirely in Meta Ads Manager, bulk uploading Meta ads, scaling creation across social platforms, launching from Google Sheets, deciding how many creatives to test, and the build-versus-buy implications of the Meta Ads API.

Google's own bulk-upload documentation shows that native bulk workflows are a genuine form of AdTech too. The distinction is scope: a campaign-operations product attempts to standardize execution across supported systems, while a native tool remains authoritative inside its own platform.

AdManage is not a DSP, SSP, exchange, publisher ad server, clean room, independent verification service, or universal attribution system. It doesn't decide the correct strategy, guarantee a winning creative, or make every supported platform equally deep. It helps teams execute approved decisions with more consistent structure and less repetitive setup.

That boundary is the value proposition. It lets experienced media buyers keep strategic control while treating human memory and manual clicking as the poor control systems they actually are.

A Practical Definition of AdTech

AdTech is not a row of acronyms between an advertiser and a publisher. It is the full set of systems that prepare an ad, configure a campaign, allocate media, deliver creative, transmit privacy choices, verify quality, measure outcomes, and improve the next decision.

Our practical test is simple: map every tool in your stack to one job. If two tools claim the same job, investigate overlap. If a critical handoff still depends on copy-paste, memory, or one person's script, you have found an operational gap. If a platform claims attribution, ask whether it can also test incrementality.

That map won't make AdTech simple. It will make the complexity legible, which is far more useful.

Frequently Asked Questions About AdTech

What Does AdTech Mean?

AdTech stands for advertising technology. It includes the software, infrastructure, data systems, and standards used to create, buy, sell, deliver, manage, verify, measure, and optimize advertising.

How Is Programmatic Advertising Different From AdTech?

Programmatic advertising is narrower than AdTech. It automates parts of media buying, selling, or allocation, and RTB is one programmatic transaction method.

Is Google Ads Considered a DSP?

Google Ads is an advertising platform with automated bidding and access to Google inventory and partners. It isn't usually classified as a conventional independent open-internet DSP. Display & Video 360 is closer to the traditional enterprise DSP category.

Is Meta Advertising Programmatic?

In the broad sense, yes: software automates targeting, ranking, delivery, pacing, and optimization. But Meta doesn't ordinarily use the same independent DSP-to-SSP-to-exchange path as open-web programmatic advertising.

How Do DSPs and SSPs Differ?

A DSP works for the buyer by evaluating media opportunities and submitting bids or buying decisions. An SSP works for the seller by making inventory available and controlling access, pricing, deals, quality, and yield.

Have Third-Party Cookies Disappeared?

No. Safari and Firefox heavily restrict cross-site cookie use by default. Chrome retained user choice in regular browsing and blocks third-party cookies by default in Incognito, while several proposed Privacy Sandbox advertising APIs were retired in 2025.

What Counts as a Viewable Impression?

For standard display, the common baseline is at least 50% of pixels in view for one continuous second. For video, it is generally 50% for two continuous seconds. Viewability indicates an opportunity to see the ad, not proof of attention.

What Role Does AdManage Play in AdTech?

AdManage fits in the advertiser-side campaign-operations and activation layer. It helps teams prepare, standardize, preview, and bulk launch campaigns across supported native platforms. It isn't an exchange, DSP, or publisher monetization system.