Series A to growth-stage AI and ML companies burn budget bidding against VC-funded competitors on terms that never convert. We build accounts that find buyers, not researchers, and tie every dollar to pipeline.
The Problem
CPCs on AI category terms are inflated by funded competitors
Every well-capitalized startup is bidding on the same head terms, so search ads for AI categories now cost a multiple of what they did two years ago. Funded companies are willing to lose money on each click to grab share, and on a smaller budget you pay the inflated price and still lose the auction on position. The fix is not bidding harder; it is finding the specific, lower-competition queries that signal a real buyer.
High-intent buying searches drown in curiosity traffic
Most searches around AI and ML are people learning, not buying. Someone typing a category term might be a developer reading docs, a student, or an analyst, and only a tiny fraction is a budget holder ready to evaluate. Broad match and loose keyword lists pull in all of it, so your cost per signup looks fine while your cost per qualified opportunity is a disaster.
The conversion is a signup, and the sale is six months away
For most AI companies the paid search conversion is a free trial or a product signup, not revenue, and the sales cycle for a technical platform runs long through security review, model evaluation, and procurement. Optimizing the account to a signup teaches the algorithm to chase cheap signups that never become customers. Without feedback from later sales stages, the bidding flies blind.
Branded and non-branded blur in a category that keeps renaming itself
Your product name, the category name, and competitor names all shift every few quarters as the space rebrands itself. Branded search looks cheap and efficient, but a lot of it is demand you already created and would have captured for free. Non-branded is where incremental growth lives and where the waste hides, and most accounts cannot tell you which is which.
How We Help
We start by separating buyers from browsers in your keyword set, auditing search terms against what converts to a sales conversation rather than a signup, and cutting the queries that pull in researchers, students, and developers reading documentation. Most accounts shrink before they grow.
Then we rebuild conversion tracking around the real funnel. A product signup is a leading signal, not the goal, so we pass later sales stages back into the ad platforms as conversion values to push the bid algorithm toward accounts that progress, not signups that stall. For product-led companies, we score signups by activation and usage before treating them as a win.
We handle the inflated-CPC problem by going where the funded competitors are not. The head terms are an auction you lose on budget, so we build the account around the long tail, the problem-aware queries, and the comparison searches against named competitors, where intent is sharper and cost is lower. Branded and non-branded get split into separate strategies with their own budgets.
We run the account against pipeline and revenue, not platform-reported conversions. We connect spend to your CRM so the number that matters is cost per qualified opportunity and eventually cost per closed deal, even when that deal lands two quarters after the click. Every dollar should trace to a buying signal; if it cannot, it gets cut.
What we deliver
- Search-term audit that splits buyer intent from curiosity traffic and cuts the waste
- Keyword strategy targeting long-tail and competitor-comparison queries where CPCs are not inflated
- Conversion tracking rebuilt around signups, activation, and downstream sales stages
- CRM-connected attribution from click to qualified opportunity to closed deal
- Separate branded and non-branded structures with distinct goals and budgets
- Weekly account management tied to cost per qualified opportunity, not platform conversions
In AI and ML paid search, the cheapest signup is usually the most expensive customer. Optimizing to the conversion the platform can see (a signup) trains the algorithm to chase exactly the traffic that never reaches a sale. The accounts that win pass real sales-stage data back to the bid algorithm and accept a higher cost per signup to get the buyers that actually close.
Our Methodology
We work in a tight loop: instrument, measure against revenue, then cut and reallocate. Before touching bids, we make sure the account can tell a signup from a qualified opportunity and that both flow back to the platform; an account that cannot measure the right outcome cannot be optimized toward it.
From there we run weekly reviews on a small set of numbers that map to your funnel: cost per qualified signup, signup-to-opportunity rate by keyword theme, and cost per opportunity split by branded versus non-branded. We move budget toward the themes that produce pipeline, re-auditing search terms and competitor names on a regular cadence as new entrants and rebrands change the auction.
How We Work
We run as your paid search team, not a vendor that disappears after setup. The engagement starts with an audit of your account, your conversion tracking, and how spend maps to pipeline in your CRM, which surfaces where the waste is hiding before we change a single bid. From there we own keyword structure, bidding, conversion configuration, and the attribution plumbing back to your sales data, and you get a named operator who knows your funnel rather than a rotating pod of junior buyers.
We report on the numbers that tie to revenue, and we report honestly: if non-branded is not producing qualified pipeline, we say so and cut it rather than dressing up a platform conversion number. The incentives are aligned, because we optimize toward your sales outcomes, not a media-spend percentage, on a monthly retainer scoped to your account and separate from the platform media budget.
- Lower cost per qualified opportunity as wasted curiosity traffic gets cut
- Clear attribution from paid clicks to signups and downstream pipeline
- Branded and non-branded measured separately, with incremental spend identified
- Bid algorithms optimizing toward accounts that close, not signups that stall
- A weekly view of which keyword themes produce revenue and which only produce clicks
If your ai / machine learning company needs paid search (sem) leadership, we should talk.
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Frequently asked questions
How much does paid search management for an AI company cost?
Management is a monthly retainer, typically $8K to $25K per month depending on the size of your account, the number of products and regions you run, and how complex the attribution back to your CRM needs to be. That fee is separate from the media budget you pay the platforms directly. We do not take a percentage of media spend, because that rewards spending more rather than producing pipeline.
When will we see results from paid search?
Click and signup data moves within the first few weeks, so you see early signals on cost per signup quickly. The number that matters most, cost per qualified opportunity, depends on your sales cycle, and for a technical AI platform with a long evaluation and procurement process you should expect a couple of months before the pipeline picture is reliable. We report the leading signals weekly so you are not flying blind in the meantime.
What does it take to connect paid search to our CRM and product data?
We need conversion events from your signup flow and sales-stage data from your CRM, whether that is HubSpot, Salesforce, or another system. The setup passes signups into the ad platforms as conversions and feeds back later stages, such as qualified opportunity or closed deal, as conversion values. For product-led companies we also pull activation and usage signals so a signup is scored before it counts, and we handle the configuration.
Why are we different from a typical search agency?
Most agencies optimize to whatever conversion the platform can see, because a signup is cheap to manufacture and a stalled signup is invisible in those reports. We optimize against your sales pipeline instead, which means we will cut spend and shrink an account when the traffic is not producing buyers. We are operators who have run growth inside companies, so we treat your budget the way an owner would.
How do you measure ROI when the conversion is a signup and not a sale?
We treat the signup as a leading indicator, not the finish line. The real measure is cost per qualified opportunity and, where the data allows, cost per closed deal, traced from the original click through your CRM. We score signups by activation and usage so the bid algorithm learns which keyword themes produce accounts that progress and which spend actually turns into revenue.
Is paid search a good fit for a company at our stage and budget?
Paid search fits AI and ML companies that have real buying intent in the market, a working signup or trial flow, and the ability to feed sales data back from a CRM. It is a weaker fit if nobody is searching for what you do yet, in which case demand generation and content come first. The opening audit tells you honestly which case you are in before you commit budget.
