Search CPCs on AI and ML terms have gone up every quarter for two years because every funded competitor is chasing the same demand. Connected TV builds category awareness with the executives and buying committees who never see your paid search ads at all.
The Problem
Paid search on AI terms is now a bidding war you can't win on budget alone
Every AI and ML company with a Series B or later is bidding on the same generic terms – "AI platform," "machine learning tool," "AI for [use case]." CPCs on these terms have climbed for two straight years because supply of qualified traffic hasn't grown as fast as the number of funded competitors chasing it. Marketing teams respond by narrowing to long-tail terms, which caps volume, or by outspending competitors, which caps margin. Neither move fixes the actual problem: demand is finite and everyone is fishing in the same pond.
The buying committee is bigger than the technical evaluator
Enterprise AI purchases rarely get decided by the engineer who found you on Hacker News or a dev blog. CFOs approve the budget, CIOs sign off on security and integration risk, and business unit leaders decide whether the use case matters enough to prioritize. Most AI companies have a content and paid strategy built entirely around the technical buyer's channels – technical SEO, developer communities, X – and zero presence with the executives who actually sign. Those executives watch streaming television. They do not read your changelog.
Performance-marketing attribution kills brand channels before they work
AI and ML marketing teams are usually built by people who came up on last-click dashboards – cost per MQL, cost per demo, cost per opportunity. Connected TV doesn't produce a clean click to attribute. Teams that apply the same weekly attribution model to CTV that they apply to paid search will see a channel with no direct conversions and cut it inside a month, usually before the brand lift has had time to show up in organic search, direct traffic, or sales cycle velocity.
Every AI company sounds identical, and thirty seconds on a big screen exposes it
"AI-powered," "intelligent automation," "next-generation machine learning" – these phrases show up in nearly every AI company's homepage and every AI company's ad copy. On a search ad or a landing page, vague positioning survives because the viewer is already searching with intent. On a streaming ad with no click available and a viewer who wasn't looking for you, vague positioning just reads as noise. CTV forces a real point of view about what the product does and who it's for, and most AI companies haven't written that point of view down yet.
How We Help
Assessment starts with the paid search cost curve, not the CTV plan. We pull the CPC and CAC trend on core AI and ML keywords over the last 12-18 months and check whether performance channels are still producing efficient growth or just producing growth at a rising cost. We also map the actual buying committee for the product – who approves budget, who owns security review, who signs – against the channels currently being used to reach them.
Strategy for the companies where CTV fits centers on two decisions: who to target and what to say. Targeting runs through household-level data rather than individual identifiers – matching first-party account lists and firmographic data to streaming inventory through a demand-side platform, layering contextual placement on business news and industry-relevant programming, and building lookalike audiences off closed-won accounts rather than website visitors.
Execution runs through creative first, inventory second. A streaming ad that repeats the homepage copy wastes the placement. We build creative around one concrete claim the audience can hold onto after thirty seconds, tested across a small set of variants before scaling spend. Inventory selection depends on where the target buyer actually streams – ad-supported tiers on major streaming apps, addressable buys through a demand-side platform, and FAST channels with business or news programming skew, rather than a blanket buy across every available app.
Measurement is where most AI companies break CTV before it gets a fair test. We build geo-lift and incrementality tests – holding out matched markets and comparing search volume, direct traffic, and pipeline velocity between exposed and unexposed regions – instead of hunting for a last-click conversion that CTV was never going to produce.
What we deliver
- Channel readiness assessment – CAC trend analysis on core paid search terms plus a buying committee map to determine if CTV timing is right
- Household-level targeting plan – DSP audience strategy built off account lists, firmographic match, and closed-won lookalikes rather than individual retargeting
- Category positioning and creative concepts – a specific, defensible claim the brand can own on a 15 or 30 second spot, distinct from generic AI messaging
- Incrementality measurement framework – geo-lift test design and a monthly reporting model tracking branded search, direct traffic, and account-level pipeline velocity
CTV doesn't replace your paid search program – it's what you run once paid search stops being cheap. The AI companies still winning efficient CAC on generic keywords don't need this yet. The ones watching CPCs climb every quarter do.
Our Methodology
Our 90-day CTV sprint for AI and ML companies starts with the readiness assessment in the first 2-3 weeks – the CAC trend review, the buying committee map, and an honest call on whether CTV timing makes sense right now. If it does, weeks 3-6 build the targeting plan and creative concepts in parallel: DSP setup and audience matching on one track, message development and a small creative variant set on the other. We do not go to full production on unvalidated messaging – creative gets tested in market on limited spend before we scale it.
Weeks 6-10 run the first live flight with the geo-lift test structure already in place, so we're measuring incrementality from day one instead of retrofitting a test after the fact. By week 12, we have a first read on branded search lift, direct traffic movement, and any shift in sales cycle velocity on target accounts, plus a clear recommendation on whether to scale the buy, adjust targeting, or pull back. This is not a set-and-forget media buy – the strategy gets revisited every month against what the incrementality data actually shows.
How We Work
The first 30 days are the readiness call and the build – this is where we decide together whether CTV is the right move and, if it is, get targeting and creative into production. Days 30-60 run the first flight with the measurement framework live. Days 60-90 bring the first incrementality read and a scale-or-adjust decision. Most CTV engagements run 4-6 months minimum, because a single flight rarely produces a clean enough signal to make a permanent budget call – brand channels need more than one cycle.
You need a marketing lead who can approve creative and a finance or RevOps partner who can pull CAC and pipeline data for the account-level analysis – we don't need a dedicated media buyer on your side, we bring that. We work directly with whoever owns the budget decision, not through a layer of account management. Weekly check-ins during the build and flight periods cover creative status, DSP delivery, and any early signal. Monthly reviews are where the incrementality data gets presented and the scale/adjust/kill decision gets made together.
What clients should expect: this is a brand investment with a measurement discipline attached, not a performance channel with next-day conversion data. If your team needs weekly conversion numbers to justify the spend, CTV will frustrate you regardless of who runs it. If your team can hold a monthly view and trust an incrementality test over a last-click number, this works. We tell you within the first assessment which camp your organization is in.
If your AI or ML company has saturated its paid search ceiling and needs the economic buyer to know who you are before your AE ever gets on a call, creative and media built for that specific gap is worth a conversation.
- Lower blended CAC as paid search efficiency improves once branded and category search demand grows
- Shorter sales cycles on named accounts exposed to the campaign, driven by executive-level familiarity going into the first call
- Category ownership of a specific claim, rather than generic AI positioning that blends into every competitor's messaging
- A validated incrementality measurement model the team can keep using for future brand spend decisions
If your ai / machine learning company needs connected tv advertising leadership, we should talk.
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Frequently asked questions
How much does a CTV advertising engagement cost for an AI or ML company?
Strategy, creative, and measurement setup typically runs $15K-$30K for the initial build, separate from media spend. Media budgets for a meaningful test usually start around $40K-$60K per month, since CTV needs enough volume to register in a geo-lift test – smaller buys don't produce a reliable read.
How long before we see results from a CTV campaign?
Creative and targeting build takes 4-6 weeks before the first flight goes live. Once live, branded search and direct traffic lift are the earliest signals and typically show up within 30-45 days of sustained delivery.
How does CTV integrate with our existing paid search and content programs?
We build CTV as a layer on top of what's already running, not a replacement. Accounts and website visitors exposed to CTV creative get routed into distinct retargeting sequences in paid search and LinkedIn, and we track whether CTV exposure correlates with lower CPCs on branded and category terms over time.
What makes Winston Francois different from a media buying agency for this?
A media buying agency will place the buy and report impressions and reach. We build the readiness assessment first and will tell an AI company not to run CTV if paid search is still efficient or the buying committee doesn't justify it.
How do you measure ROI on CTV when there's no click to attribute?
We use geo-lift and incrementality testing – holding out matched markets and comparing branded search volume, direct site traffic, and account-level pipeline movement between exposed and unexposed regions. This isolates the effect of the CTV spend from everything else happening in the market.
What stage of AI or ML company is the right fit for CTV advertising?
Companies past Series B with real budget – typically $150K or more available for a first meaningful test – and a buying committee that includes non-technical executives are the right fit. Seed and Series A companies still building product-market fit are almost always better off putting that budget into paid search, content, or outbound, where the feedback loop is faster and cheaper.
