Costs climbed and lead quality fell.
What we did
- Rebuilt campaigns by intent + match type
- Added offline-conversion import for true ROI
- Tightened negatives + landing pages
Result Lower cost per qualified lead with cleaner signal to the platforms.
Demand + Content
Paid Advertising
Paid advertising should drive measurable business results, not just traffic.
What it is
A system, not an on-switch.
We build and manage paid campaigns across Google, Microsoft, Meta, and the emerging ad placements inside OpenAI's ChatGPT, focused on lead quality, efficient spend, and consistent performance improvement. Now that this inventory has opened up, we deploy ChatGPT/OpenAI ads to put your offer inside the AI assistant your buyers ask before they buy.
Core services include
- ChatGPT and OpenAI Ads (OpenAI's self-serve Ads Manager, in beta), an emerging placement we're set up to run as access opens, reaching buyers inside the AI assistant they now use to decide
- Cross-engine media buying, Google and Meta run as one funnel, with OpenAI placements included where they fit
- Paid Search & Paid Social Management
- Audience & Targeting Strategy
- Ad Creative & Messaging
- Landing Page & Conversion Support
- Reporting & Optimization
Definition
What is Paid Advertising (PPC / Paid Media)?
Paid advertising is buying placement on search engines, social platforms, and ad networks so your offer reaches the right people at the moment they're deciding, with every dollar tracked against real business outcomes rather than clicks alone. You pay the platform per click or per impression to show ads to a targeted audience, and success is measured by the leads, calls, or sales those ads produce.
How it works
We set up and run campaigns across Google, Microsoft, and Meta, matching keywords, audiences, and creative to buyer intent, plus the emerging ChatGPT/OpenAI ad placements as a controlled test line, then tie each campaign to conversion tracking so we can see which spend actually produces qualified leads. From there it's continuous work: cutting the queries and audiences that waste budget, scaling what converts, and improving landing pages so the traffic you pay for turns into results.
Who it’s for
Businesses that need predictable, near-term demand and any team tired of paying for traffic that never becomes revenue; the fitting outcome is qualified leads, sales, and inbound calls at an efficient, measurable cost per result, not raw traffic or impressions.
In practice
A service company running broad, untracked Google Ads is spending on clicks that never call. We tighten the keywords to high-intent searches, add negative keywords to stop wasted spend, wire up call and form tracking, and route clicks to a focused landing page, so the same budget starts producing tracked phone calls and booked jobs the owner can trace back to specific campaigns.
What we manage.
- ChatGPT / OpenAI Ads (beta)
- Google Ads
- Microsoft Ads
- Meta Advertising
- Local Services Ads
- Retargeting Campaigns
See if Paid Advertising is the right move for your team.
Request a free quoteSee it in action
From Google to ChatGPT, every dollar accountable.
Paid Media Console, Your Brand
Google · Microsoft · Meta · ChatGPT, last 30 days
CHANNELSPENDCPLQUAL%Google Search$9.8k$2768%Meta$6.4k$3457%Microsoft Ads$4.2k$3161%ChatGPT Ads BETA$2.6k$2671%Display paused$0, ,
Paused display budget now funds the ChatGPT pilot, 41 qualified leads at $26 CPL, the most efficient channel three weeks running.
Illustrative example, styled to show the kind of output we deliver.
Selected work
Representative engagements.
Profitable acquisition from accounts built around intent and clean measurement.
Broad campaigns burned spend on junk clicks.
What we did
- Geo + schedule tightening
- Call tracking + form tracking
- Tighter ad-to-page match
Result More booked jobs from the same monthly budget.
Examples are anonymized to honor client NDAs and edited to illustrate typical scope, outcomes vary by market, budget, and starting point.
How & why it works
We feed the algorithm what a good lead is.
Modern ad platforms bid automatically, but they only optimize toward the outcomes you send back to them. We close that loop by piping real sales data, not just form fills, into Google, Microsoft, and Meta so their bidding models learn to buy the traffic that actually becomes revenue.
- Define the true conversion eventBefore spend scales, we set the target the platform optimizes toward: a qualified lead or closed sale, not a raw form submit. We stand up conversion tracking through GA4 and the platform tags, wire Enhanced Conversions for Leads (hashed email/phone), and confirm every event fires once with a value attached.
- Import back-end outcomes (OCI)We connect the CRM to Google's Offline Conversion Import and Meta's Conversions API so a lead that becomes a $4k deal is fed back with its real value. Smart Bidding then learns which keywords, audiences, and creatives produce closers; not the cheap clicks that never buy.
- Structure accounts around intent and marginSearch-term reports and the query stream drive weekly negative-keyword sculpting so budget stops leaking to irrelevant searches. High-margin, high-intent products get their own campaigns and tROAS/tCPA targets; broad match is only trusted once the conversion signal is clean and audience signals are seeded.
- Let bidding train, then hold it accountableWe give algorithmic bidding (tCPA / tROAS / value-based) a stable target and enough conversions to exit the learning phase instead of resetting it every few days. Creative and landing-page variants run against the same audiences so we isolate what moved performance.
- Test incrementality, not just attributionPlatform-reported ROAS over-credits demand that would have converted anyway. We run geo holdout or conversion-lift tests periodically to measure incremental revenue, then reallocate budget toward the channels and campaigns that genuinely add sales.
Worked exampleA B2B services company spending ~$12k/month on Google Search, judging results by cost per form fill.
- Connected their CRM via Offline Conversion Import so only Sales-Qualified Leads (SQLs), not every form, were sent back as the optimization event, each stamped with its pipeline value
- Rebuilt Smart Bidding around Target CPA on SQLs and added 60+ negative keywords from the search-term report to cut spend on job-seeker and DIY queries
- Seeded first-party customer-match audiences as bidding signals and split high-value service lines into their own campaigns
- Over ~90 days, raw lead volume dipped slightly while SQLs rose modestly and cost per SQL fell roughly 25–30% at the same budget; a geo holdout confirmed the lift was incremental
Why it works
Automated bidding is only as smart as the outcome data it is trained on, optimize to form fills and you buy volume; optimize to closed revenue and you buy customers. Feeding qualified, valued conversions back into the platforms compounds because each week the model has better examples of who converts, so the strategy is designed to drive down cost per qualified lead as the same budget is steered toward higher-intent auctions; a trend we typically see when data quality and market conditions support it. And measuring incrementality rather than trusting last-click attribution keeps spend on the traffic that would not have converted without the ad.
FAQ
Questions, answered.
We run Google (Search, Performance Max, Demand Gen, YouTube), Meta, LinkedIn, Microsoft, and the emerging ads inside ChatGPT and OpenAI placements as those inventory options open up. We do not just pick one channel and hope. We map each platform to where your buyers actually are and where the unit economics work, then concentrate budget there instead of spreading it thin. For example, a B2B account might get the bulk of spend on LinkedIn and Google Search while we use OpenAI placements as a controlled test line rather than the main bet.
Media spend goes directly to the platforms and is always yours, billed to your own ad accounts so you keep ownership and history. Our management fee is separate and is usually a flat retainer or a percentage of spend depending on account size and complexity. As a rough guide, paid search and social programs tend to make sense starting around a few thousand dollars per month in media, because below that there is not enough data to optimize against. We will tell you honestly if your budget is too low to get a real signal before you commit.
You own all of it. We build campaigns inside your Google Ads, Meta Business Manager, and LinkedIn accounts, and the pixels, conversion actions, and audiences live in your properties, not ours. If we stop working together, nothing gets switched off and nothing walks out the door. For example, your GA4 setup, Google Tag Manager container, and server-side tracking stay fully in your hands with documented configuration so any team can pick it up.
We tie campaigns to revenue events, qualified leads, pipeline, and cost per acquisition rather than vanity metrics like impressions or generic click counts. That means setting up proper conversion tracking, offline conversion imports from your CRM where possible, and consent-compliant measurement so the numbers hold up. We report on cost per qualified lead and return on ad spend, and we are clear about which conversions are leading indicators versus closed revenue. If tracking is not trustworthy, we fix that before we scale spend, because optimizing on bad data just loses money faster.
The first few weeks are audit, tracking setup, account structure, and creative and landing page review, then we launch and let the platforms gather data. Most accounts need roughly 30 to 60 days of live spend before the algorithms and our optimizations settle into a reliable cost per acquisition, and longer for considered, high-ticket purchases. We actively manage throughout, adjusting bids, budgets, audiences, and creative weekly rather than setting it and forgetting it. Expect early learning, honest mid-course corrections, and a clearer performance picture by the end of the first quarter.
Let’s make it measurable.