Mary Gabrielyan
September 22, 2025
27
minutes read
You don't need a technical background or million-dollar budget to succeed with programmatic advertising—just the right knowledge and strategy. This complete guide walks you through everything from basic concepts to advanced tactics.
Programmatic buys impressions one at a time, in real time, against precise audiences and contexts. That precision now underpins the bulk of digital spend: US digital advertising hit $258.6 billion in 2024, up 14.9% year over year, with programmatic alone reaching $134.8 billion (+18%).
Two shifts explain the urgency for 2026 planning. First, premium video has gone programmatic. Connected TV (CTV) continues to soak up budgets as major streamers add inventory and targeting options. Second, automation is spreading into channels that used to be hard to buy dynamically. Programmatic digital out-of-home (DOOH) is growing quickly and already represents more than a quarter of US DOOH spend, giving buyers on-the-fly control of screens in retail, transit, and city centers.
Privacy remains a live issue, but the ground rules have shifted. Google has stepped back from deprecating third-party cookies in Chrome, but the long arc still points to more consented, first-party data and contextual signals, even if cookie deprecation is no longer the near-term switch many expected.
Here’s what’s ahead: a definition of programmatic, the numbers that prove its value, format comparisons, a breakdown of platforms and buying models, performance-driving strategies, and what to expect in 2026.
Programmatic advertising is the automated buying and selling of digital ad inventory, executed by software that decides—in milliseconds—whether to bid on a single impression, how much to pay, and which creative to serve. Most trades happen via real-time bidding (RTB) auctions, but automation also powers private marketplace (PMP) and programmatic guaranteed deals. In short: no manual insertion orders, and decisions are data-driven at the impression level.
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Programmatic began in the early 2010s with open-exchange RTB for display, then expanded to curated PMPs, preferred deals, and automated guaranteed/direct to secure premium placements with negotiated terms—still delivered through programmatic pipes. Today it underpins nearly all US digital display buying (91.3% share in 2024) and has moved well beyond banners into video/CTV and digital out-of-home (DOOH). In 2025, US CTV ad spend is forecast at $33.35B; programmatic DOOH reached 26.4% of US DOOH spend in 2024.
How programmatic differs from traditional buying/display:
💡 For the linear and streaming TV planning toolkit, see TV media buying in 2025–2026: definition, process, costs, and winning strategies.
A quick summary before we dive in: programmatic concentrates spend where it can work hardest—using data to decide which impression to buy, automating the heavy lifting, exposing what’s happening in near real time, and tightening the loop between spend and outcomes.
Programmatic makes bid-by-bid decisions using audience, contextual, device, and time signals, then pairs those decisions with dynamic creative so each impression is as relevant as possible.
At a business level, strong personalization programs have been shown to lift revenue (≈5–15%) and marketing ROI (≈10–30%), which is why impression-level targeting and dynamic creative optimization are so valuable inside programmatic buys.
Retargeted programmatic ads also achieve click-through rates 10x higher than standard display, with 70% of consumers more likely to convert after seeing retargeted messages.
Automation replaces RFPs and manual insertion orders with software that plans, bids, paces, and optimizes across channels. That efficiency is one reason programmatic accounts for more than 90% of US digital display spend.
It’s also improving how much of your budget reaches real people: the ANA’s 2024 benchmark found 43.9% of every $1,000 entering a DSP now reaches consumers, up 7.9 percentage points year over year (an extra $79 per $1,000). Pair this with supply-path optimization—especially AI-assisted—to reduce hops and fees.
💡 Read more: Supply-side optimization with AI. A practical walkthrough for auditing supply paths, prioritizing higher-quality exchanges, and reducinh fees. You’ll leave with a simple scorecard and a pilot plan to tighten your routes.
Programmatic shows where ads run and how they perform in near real time, and industry standards strengthen that transparency:
Together, these tools help buyers verify supply chains, monitor quality, and optimize faster.
💡 Read more on why brand safety has to start on the supply side, not just with DSP filters: Safety in programmatic advertising.
Better targeting, automated optimization, and cleaner supply paths concentrate spend on working media.
The ANA’s 2024 study shows meaningful efficiency gains (more dollars reaching consumers) and sharp reductions in spend on made-for-advertising (MFA) sites, both of which support lower CPAs and stronger ROAS when combined with solid measurement.
These results stem from programmatic's ability to eliminate waste. Traditional advertising accepts significant spillage, showing ads to people outside the target demographic. Programmatic reduces wasteful impressions by ensuring ads only serve to qualified prospects.
Smaller advertisers particularly benefit from programmatic's democratizing effect. Previously, premium publisher inventory required massive minimum spends and long-term commitments. Now, a local business can access the same high-quality placements as Fortune 500 companies, bidding only on impressions that meet their specific criteria.
Programmatic spans every major digital channel and, increasingly, physical screens. Each format excels at different jobs—from efficient reach and remarketing to premium video attention, content-led engagement, screen-free moments, and location-aware presence. Use the notes below to match formats to your goal before you dive into the details.
Display refers to graphical ad units (e.g., 300×250, 300×600, 728×90, 320×50) and rich media that render within page content or app views across the open web and mobile apps. Buying is predominantly automated (as mentioned, about 91.3% of US digital display spend in 2024 transacted programmatically) with impressions auctioned in milliseconds and delivered via standard ad servers and SDKs.
Creative ranges from static images to HTML5 and expandable units; viewability and brand-suitability are verified through third-party measurement (e.g., Open Measurement SDK) and supply-chain transparency tools (ads.txt/sellers.json).
Within programmatic mixes, non-video display has gradually ceded share to video and native, but remains the broadest, most diverse inventory pool for addressable reach.
In fact, the web contains three times more banner inventory than video, providing unmatched reach for advertisers needing scale.
“Programmatic video” spans in-stream (pre/mid/post-roll) and out-stream (in-article, in-feed, interscrollers) units on web and mobile, plus CTV placements that run inside streaming apps on smart TVs and OTT devices.
CTV is the fastest-expanding segment: As mentioned, US CTV ad spend is forecast at ~$33.35B in 2025, with the vast majority of those dollars tied to video units in ad-supported VOD and FAST channels.
Technically, video ads transact via VAST/VMAP, with server-side ad insertion (SSAI) common on CTV to maintain stream quality; identity is often resolved at the household/device level, and completion rates are typically higher than web video due to lean-back viewing.
Inventory spans premium broadcasters, streamers, and long-tail apps, available through open auctions, PMPs, and programmatic guaranteed deals.
💡 Here’s what to read next to deepen your knowledge on programmatic, streaming, and CTV:
Native ads are rendered to match the host environment’s look and feel, using the OpenRTB Native spec (assets like headline, image, brand, CTA) assembled into in-feed units, content recommendation tiles, and sponsored listings. Their design aims for editorial harmony, which often results in longer attention and deeper on-page engagement than standard banners.
Budget has followed: US native ad spend is ~63.1% of total display in 2024, reflecting how much of display has migrated to integrated, feed-based placements across news, lifestyle, commerce, and social-like environments.
Programmatic native trades via the same pipes as display (DSP↔SSP) but with native-specific creative fields and rendering rules per publisher template.
Programmatic audio encompasses ads inserted into music streaming services, digital radio, and podcasts; delivery uses client- or server-side dynamic ad insertion to place pre/mid/post-rolls into live or on-demand audio.
The category is smaller than display and video but expanding: programmatic is set to claim ~30% of US digital audio services ad spend in 2025, roughly $2.3B, as supply scales across major platforms and networks.
Targeting commonly includes genre, show, mood, location, and device; creative formats center on 15s/30s audio spots, with companion banners on some players.
Podcast inventory mixes host-read and announcer-read placements, with the latter more readily traded through programmatic pipes.
Measurement blends impression logs with brand-lift and site-visit/coupon match methods suited to screen-off consumption.
Consumers spend 31% of their time with audio, yet the channel gets just 9% of ad spend—a massive gap, and a big opportunity.
DOOH covers digitized roadside billboards, street furniture, transit screens, and place-based networks (retail, gyms, offices, airports), now addressable via programmatic pipes.
Impression delivery is modeled from sensor/mobile panel data and proof-of-play logs, with buys often transacted on impression-based goals or share-of-voice against screen loops.
In the US, programmatic DOOH represented ~26.4% of DOOH spend in 2024 (about $850M, +34% YoY), reflecting rapid adoption of dynamic triggers (time, weather, events) and flexible dayparting across national screen networks.
Creative adheres to OOH constraints—large typography, high contrast, ultra-brief copy—with variant rotation by location or time to localize messaging at scale.
Programmatic runs on a small set of connected systems. On the buy side, DSPs decide what to bid and what to show; on the sell side, SSPs package and price inventory. In the middle, ad exchanges run the auctions, while data platforms (DMPs, CDPs, and clean rooms) supply the audience and measurement fuel.
A demand-side platform is the buyer’s control room: software that ingests bid requests from exchanges, evaluates them against campaign rules, and decides whether to bid, what price to bid, and which creative to serve.
At scale, bidding platforms routinely process >1 million bid requests per second—a useful benchmark for DSP decisioning capacity.
A DSP centralizes audience targeting, budgets, pacing, frequency management, and creative delivery, and it connects to data sources (first-party segments, contextual signals) as well as verification vendors for brand safety and viewability.
Modern DSPs also handle identity resolution (device/household graphs), log-level reporting, and optimization models that learn from impression, click, and conversion feedback.
On the sell side, a supply-side platform packages a publisher’s inventory, applies business rules (floors, blocks, priority deals), and exposes that supply to multiple demand sources through a unified auction.
SSPs enforce ads.txt/sellers.json authorization, pass privacy and consent signals, and provide yield tools such as dynamic floors and deal discovery (open auction, PMP, preferred, programmatic guaranteed).
They also transmit quality, viewability, and supply-path data so buyers and exchanges can make more informed decisions while publishers protect brand suitability and revenue.
In Q3 2024, Google AdX ranked #1 in U.S. web traffic (13% share) among SSPs, while Magnite led Roku CTV traffic (33% share)—an indicator of how share varies by surface.
💡 Learn about Smart Supply—optimized deal IDs, less waste, more reach
Ad exchanges are the marketplaces that connect DSP demand with SSP supply, normalize bid requests via OpenRTB, and clear auctions—typically first-price today—under tight latency constraints. They enforce deal terms, propagate brand-safety and supply-chain objects, issue win/loss notifications, and return ad markup to the publisher stack once a winner is determined.
Data platforms power targeting and measurement:
In IAB’s 2024 State of Data, 79% reported using or investing in CDPs, 77% in DMPs, and 66% in data clean rooms, reflecting where audience/activation stacks are standardizing post-cookie.
Programmatic isn’t a single auction—it’s a set of transaction types that balance scale, price control, and certainty in different ways. All of them run on the same pipes (Deal IDs, floors, priorities), but they differ in who can access the inventory, how prices are set, and whether delivery is guaranteed. Use the summaries below to understand how each model works before choosing the mix that fits your plan.
RTB is the open-exchange auction most people picture when they think “programmatic.”
An SSP broadcasts a bid request for a single impression; eligible DSPs evaluate it against targeting and pacing rules and return a bid within milliseconds. The exchange clears the auction (typically first-price today) against the publisher’s floor and any deal priority, then returns the winning ad markup to the ad server.
RTB offers the broadest access and fluid pricing, with transparency into domains/apps and supply paths via standards like ads.txt, sellers.json, and SupplyChain.
A PMP is an invite-only deal where one or more publishers expose specific inventory to a curated set of buyers.
Transactions still happen programmatically (usually via a private auction with dynamic pricing), but the seller controls who can bid, what inventory is included, and the floors/suitability rules.
PMPs are often packaged by context, audience, or format (e.g., a CTV bundle across premium apps) and traded via Deal IDs, giving buyers clearer placement quality and often higher win rates than the open exchange.
Preferred deals are 1:1 agreements at a pre-negotiated fixed CPM that grant the buyer “first look” access to a publisher’s inventory.
The buyer can choose to take or pass on each eligible impression; if they pass, it typically flows to a private or open auction.
There’s no delivery guarantee, but the price is stable and the priority is higher than general auction demand, all executed through programmatic pipes under a Deal ID.
Programmatic guaranteed (also called automated guaranteed) is a reservation: the buyer and seller agree upfront on price, volume, dates, and targeting, and the platform automates trafficking and delivery.
There’s no auction for that reserved supply—impressions are held for the deal and paced to meet the guarantee, with cancellation and makegood terms defined in the agreement. Because it uses the same ad-tech rails, PG keeps the convenience and reporting of programmatic while providing the certainty of a direct IO.
Among large U.S. advertisers in Q1 2024, programmatic channels +33% YoY overall; Premium Programmatic (PMP/PG) budgets +52%, outpacing Open Exchange +19%.
Programmatic is a millisecond handshake between supply and demand. Each time a page, app, or CTV stream loads, the publisher’s stack describes the impression, buyers evaluate it against their data and rules, an exchange clears the auction, and the winning creative renders—followed by verification and logging. The loop then feeds back into bidding and pacing so the next impression is decided with fresher signals.
These snapshots show programmatic in action across publishing, CPG, and nonprofit. Each pairs data-driven targeting with suitable inventory and creative, and reports clear outcomes to illustrate what success looks like in practice.
The team profiled a segment of “intellectually curious” non-readers, then mapped where those readers actually spent time online and what topics signaled receptivity. Creative lines were written to mirror those contexts—short, provocative prompts that clicked through to article excerpts and subscription offers. Bidding prioritized pages whose semantic cues matched the ad theme, so the same person could encounter very different messages depending on the story they were reading. The campaign delivered 64,000 paid subscriptions with a 25:1 payback on estimated LTV and revealed more than five million previously unseen, retargetable users—evidence that contextual signals plus sharp creative can unlock incremental audience at scale.
💡 Read more: The Economist: Raising eyebrows and subscriptions
Kellogg shifted buying into a programmatic stack and made “viewable impressions” the currency, optimizing toward placements consumers could actually see. With unified controls for frequency, pacing, and creative rotation, impression quality rose and wasted spend fell. Reported viewability moved into the 70–80% range, and audience matching improved two to three times over prior methods, reflecting cleaner supply paths and stronger placement curation. The change reorganized the plan around attention, which in turn lifted downstream performance signals.
💡 Read more: Kellogg dishes up offline sales with programmatic buying
The charity connected a live case feed to digital OOH networks so screens could update by geography and time, showing the most relevant appeal in the places it mattered. Triggers such as proximity to transport hubs, commuting peaks, and local events informed which creative variant appeared on which screen. Proof-of-play logs and response tracking showed reported success rates rising from roughly 50% to about 70% on featured cases, illustrating how fast, context-aware updates on public screens can change real-world outcomes.
💡 Read more: How charity Missing People is saving lives by moving to programmatic
Before you set budgets or choose platforms, align on outcomes and guardrails. The steps below give you a practical sequence: define goals and KPIs, select the right buying stack, run a focused learning sprint, and build a durable data foundation.
Clarify what success looks like before you buy a single impression. Pick one primary outcome per campaign (for example, incremental sales, qualified leads, new subscribers, brand lift) and list only the handful of metrics that prove progress toward that outcome. Then lock a baseline: what performance looks like without the new spend, over a recent, representative window. This gives you the “delta” you’ll report against.
Match the platform to your channels, identity needs, and transparency expectations. A practical way to do this is a scorecard with weighted criteria, then a small pilot to validate claims in the wild. Look for broad, high-quality inventory access; the ability to activate your first-party data safely; and controls that let you shape bidding, pacing, and creative delivery without guesswork.
💡 Explore Smart Supply—AI Digital’s way to cut fees, block IVT, and maximize impact.
Treat the first 6–8 weeks as a learning sprint, not a forever setup. Write a short learning agenda that states the questions you need answered, the hypotheses behind them, and the evidence that will confirm or reject each one. Design clean A/Bs: one variable at a time, enough impressions to reach significance, and a clear stop/scale rule. Keep a simple operating cadence so optimizations don’t drift.
Anchor your programmatic plan in consented, well-governed first-party data. Make it easy for customers to share information with clear value exchanges, unify that data in a CDP, and define durable audience segments with consistent rules for entry, exit, and refresh. When collaboration is needed, use clean rooms to match audiences with publishers or retailers without exposing raw PII.
This starter framework keeps teams aligned on outcomes, reduces waste early, and builds the data foundation you’ll need for sustained performance.
Winning with programmatic comes down to matching the right audience, message, and moment—then repeating that match at scale with clean data and clear rules. The plays below focus on segmentation, context, pacing, and coordination across channels so results compound rather than scatter.
Strong segmentation starts with consented first-party signals, clear entry/exit rules, and creative that reflects intent—not demographics. Use the steps below to build durable, mutually exclusive segments you can trust in optimization.
Context is a durable targeting signal that doesn’t rely on user IDs, and brand safety/suitability keeps ads in environments that fit your standards.
Impact fades when the same person sees too many identical ads; sequencing turns exposures into a story rather than repetition. The steps below help you set sensible caps and move people through a clear narrative.
Retargeting converts warm intent; lookalikes expand reach by finding people who resemble your best customers.
Omnichannel works when audiences, creative, and measurement share the same spine. The notes that follow show how to coordinate channels so each touch reinforces the last.
Programmatic’s scale and speed come with trade-offs: invalid traffic, stricter data rules, uneven inventory quality, and the risk of letting automation outrun creative. The sections below define each issue and offer practical fixes you can bake into planning, buying, and measurement.
The challenge: Automated buying attracts bad actors: bots, spoofed domains, and resold inventory that adds fees without value. Even with progress, fraud risk remains.
We’ve proven that certification works: the industry saved more than $10 billion in 2023 alone from fraud. — Mike Zaneis, CEO, TAG
What works:
The challenge: Consent rules limit tracking and data sharing. Google’s April 2025 decision not to deprecate third-party cookies in Chrome paused one disruption, but enforcement of GDPR/CCPA continues and privacy expectations are rising.
To tackle data quality challenges, it’s crucial to adopt AI, machine learning, and media mix modeling — Angelina Eng, VP Measurement & Addressability, IAB.
What works:
💡 Learn more: In a cookie-less world: new challenges and opportunities
The challenge: Waste from low-quality or “made-for-advertising” supply and opaque chains erodes ROI. The good news: quality controls are improving. The ANA 2024 Programmatic Benchmark found an additional $79 per $1,000 now reaches consumers versus 2023, and MFA spend fell from 15% to 6.2%.
Without more substantial improvement to CTV transparency, the long tail of ad buyers won’t be playing there. — Eric Schmitt, Research Director, Gartner
What works:
💡 Read more: Rethinking the value proposition of DSPs in today’s programmatic
The challenge: Algorithms optimize delivery, but weak creative stalls performance. Multiple studies show creative quality is a primary driver of sales impact. Reserach indicates creative can account for ≈47% of sales contribution; strong creative dominates outcomes, while weak creative shifts results to media factors.
What works:
💡 Explore how GenAI is changing creative media.
Measurement in programmatic is a telemetry system wrapped around every impression. Ad servers, SDKs, and verification tags record exposure, interaction, and outcome events; platforms aggregate those events into metrics that align with how people move from seeing an ad to taking action. Standards bodies define the common denominators so numbers mean the same thing across sites, apps, and devices.
The funnel frames how metrics relate to behavior: exposure comes first, engagement follows, actions mark value, and efficiency links spend to those outcomes. The items below move in that order.
Instrumentation is the shared plumbing—SDKs, schemas, and definitions—that makes metrics interoperable across web, app, CTV, and audio.
Programmatic uses complementary methods that answer different questions: paths to outcome, causal lift, long-run contribution, and people-based reach across channels:
This taxonomy groups metrics into layers that describe exposure, engagement, conversion, efficiency, and delivery integrity. Read top to bottom, it shows how media moves from being seen to creating value:
Measurement systems run against baselines. Teams establish a reference period, collect comparable data each week, and report movement relative to that baseline. Definitions are standardized up front—viewability rules, attribution windows, IVT filtration—so results from different partners line up. Periodic calibration happens through scheduled lift studies and routine model refreshes for MMM, while learnings flow back into audience definitions, creative libraries, and supply curation to keep the next cycle better than the last.
The next phase is about maturing the operating model, not inventing a new one. Expect deeper use of data and automation in creative and bidding, tighter links between digital and “traditional” screens, carbon-aware planning to trim waste, and continued movement toward programmatic as the standard way media is traded.
Generative AI is moving from experiments to everyday tooling: rapid concepting for variants, automated copy and visual swaps for segments, and predictive signals feeding bid strategies.
In McKinsey’s 2024 survey, 65% of organizations reported regular gen-AI use, nearly double the prior wave—momentum that’s now tempered with governance: the 2025 follow-up shows firms instituting formal human review of AI outputs before use.
Expect your playbook to pair DCO and creative versioning with clear review standards and measurement that isolates creative lift from bidding effects.
💡 Read our take on AI: The Future is Now: How AI Digital Embraces AI Technologies
The wall between digital and “traditional” channels keeps shrinking.
eMarketer projects CTV to overtake linear TV ad spend by 2028—a shift driven by ad-tier launches and addressable delivery.
In out-of-home, programmatic is now a material share of buying, which continues double-digit growth into 2025. Planning will increasingly treat TV and OOH as programmatic surfaces with audience, context, and timing controls similar to web and mobile.
Carbon accounting is entering briefs and QBRs. GroupM’s omnichannel carbon calculator (built with Scope3 data) gives planners emission factors by channel and aims to halve emissions per impression by 2030, enabling optimization on performance and footprint. Scope3’s research has quantified digital advertising’s emissions and, in 2025, reported that lower-carbon supply paths can maintain or improve effectiveness when buyers curate inventory and reduce wasteful hops.
Expect “green media” requirements in partner RFPs and supply-path policies that down-weight high-emission routes and low-quality MFA inventory.
Programmatic is already the standard for display—and it’s spreading across channels. As mentioned throughout the article, programmatic captured 91.3% of US digital display ad spend in 2024, and programmatic display ads grew about 3× faster than non-programmatic.
With CTV and DOOH adopting similar pipes, most campaigns in 2026 will default to automated, data-driven transactions, reserving manual buys for exceptional cases. Teams that win will combine curated supply, clean measurement, and disciplined creative testing—treating programmatic as the operating model, not a tactic.
Programmatic is essential in 2026 because it buys media the way marketers actually plan: one impression at a time, with data deciding the who, where, and how much. It delivers scale across display, video and CTV, audio, and DOOH; it provides live controls for targeting, price, and safety; and it has matured with better transparency, cleaner supply paths, and stronger measurement. As privacy expectations rise, programmatic’s mix of first-party data, contextual signals, and automated optimization gives teams a practical way to grow reach and outcomes without wasting budget.
In short: use programmatic as your operating model, not a side tactic. Build the plan around data, quality supply, disciplined testing, and clear accountability.
If you’re looking for actionable recommendations, here’s your go-to checklist:
☑️Center on first-party data: codify consent/value exchange; unify IDs in a CDP and sync durable segments to the DSP with clear suppressions/burn windows.
☑️Enforce clean supply: prefer direct paths and require ads.txt, sellers.json, and SupplyChain on every deal.
☑️Use curated access when quality matters: PMPs/curated marketplaces with viewability (and, if used, attention) floors.
☑️Audit SPO quarterly: cut hops/partners that add cost without performance.
☑️Run a standing learning agenda: short, written hypotheses for audience, frequency, and creative.
☑️Test in tight sprints: simple A/Bs; promote winners to always-on budgets.
☑️Prove causality regularly: at least one incrementality (lift) test per quarter for major tactics.
☑️Make creative a performance lever: maintain refreshed variants per segment; sequence messages; cap cross-channel frequency.
☑️Use DCO selectively: only where signals are strong, with human review before launch.
☑️Standardize measurement: one viewability/IVT spec and shared attribution windows across partners.
☑️Triangulate results: platform attribution for direction + lift tests for causality + MMM for long-run contribution.
☑️Report deltas vs. baseline: tie optimizations to ROI/CPA targets, not vanity metrics.
Adopt these habits, and programmatic won’t just spend efficiently; it will become a system that compounds learning, improves creative impact, and drives reliable growth across every channel you use.
Talk to AI Digital. If you want a DSP-agnostic partner that pairs brand-safe supply with clear, cross-platform buying, we can help through our Open Garden model and managed service—built to align optimization with your KPIs and give you full visibility across channels.
Get in touch to request a quick programmatic health check—supply-path review, KPI map, and a focused test plan tailored to your goals.
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Inefficiency
Description
Use case
Description of use case
Examples of companies using AI
Ease of implementation
Impact
Audience segmentation and insights
Identify and categorize audience groups based on behaviors, preferences, and characteristics
Automated ad campaigns
Automate ad creation, placement, and optimization across various platforms
Brand sentiment tracking
Monitor and analyze public opinion about a brand across multiple channels in real time
Campaign strategy optimization
Analyze data to predict optimal campaign approaches, channels, and timing
Content strategy
Generate content ideas, predict performance, and optimize distribution strategies
Personalization strategy development
Create tailored messaging and experiences for consumers at scale
It automates buying so you can reach specific audiences at scale, control price and placement in real time, and optimize toward measurable outcomes. The result is less waste, better transparency, and faster learning across channels.
Programmatic media is digital ad inventory bought and sold automatically by software—one impression at a time—using data to decide who sees which ad and how much to bid. It runs across formats (display, video/CTV, native, audio, DOOH) via auctions (RTB) and negotiated programmatic deals (PMPs, preferred, programmatic guaranteed), replacing manual RFPs and insertion orders with real-time, data-driven delivery and measurement.
Define business goals and KPIs, choose a DSP or partner that fits your channels, and start with small test campaigns. Use first-party data and contextual signals, set brand-safety and frequency rules, measure with consistent standards, then iterate based on results.
You usually pay on a CPM basis, with prices varying by format, audience, and quality (e.g., CTV and high-impact placements cost more than standard display). Budget for media, data/tech fees, and verification—then monitor effective CPM and CPA/ROAS to judge value.
Automated platforms (DSPs connected to SSPs/ad exchanges) buy individual ad impressions in real time across display, video/CTV, native, audio, and DOOH. It uses data (first-party and contextual) for targeting and creative selection, transacts via RTB, PMPs, preferred deals, and programmatic guaranteed, and runs with guardrails for brand safety, frequency, and measurement (viewability, IVT, ROAS/CPA).
Many Google Ads placements (Display Network, YouTube, some Discovery formats) are bought programmatically through Google’s systems, and Google’s DV360 is a full DSP for open-web and CTV buys. Search ads use their own auction but still rely on automated, auction-based delivery.
