Client Results

Results we can put numbers on.

Every engagement starts with an audit. Ends with a number we can defend. The client owns every system we built — no dependency on our access.

−41%

Legal CPL reduction

Hindieh Law · Google Search + LSAs

+84%

Patient pipeline growth

US Wound Care · condition-specific funnels

5.4×

ROAS peak

DTC paid media engagement

71%

Cost-per-SQL reduction

B2B SaaS funnel rebuild

Named clients

Our work, on the record.

These clients gave us permission to use their name. Real business, real numbers.

Hindieh LawPersonal Injury & Criminal DefensePaid Media · Google Search + LSAsOngoing · 6-month snapshot

Dallas law firm · Google Search + Local Service Ads · competitive PI market · high CPCs

Personal injury Google Ads in Dallas is one of the most expensive markets in the country. We cut their cost per qualified intake by 41% without touching case volume.

The Situation

CPCs for personal injury keywords in Dallas run $40–$95. The firm was spending $18k/month and generating intake calls — but had no visibility into which campaigns were producing cases that settled versus volume that burned intake team time. Broad match on high-competition terms was eating the budget; LSA profiles were unoptimised and losing placement to firms with weaker actual reviews.

What We Did

We rebuilt campaign structure around case type and settlement likelihood — not raw call volume. Call tracking connected intake outcomes back to the specific ads that drove them. Spend shifted from broad "personal injury attorney" terms to case-specific, geographically tighter intent signals. LSA verification, review strategy, and profile optimisation pushed the firm into guaranteed top placement on high-commercial-intent queries.

“We'd been optimising for call volume. SearchTuners helped us optimise for cases that actually matter.”

— Managing Attorney, Hindieh Law

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−41%

Cost per qualified intake

same $18k/mo budget, sharper targeting

+67%

Monthly case inquiries

quality-filtered leads, not raw volume

4.2×

Return on legal ad spend

case value vs. total ad investment

94%

LSA top-3 position rate

held across primary practice areas

US Wound CareHealthcare · Wound CarePaid Media · Google Search + DisplayOngoing · 4-month snapshot

Wound care clinic network · Google Search + Display · dual audience: patients + referring physicians

Medical advertising has strict rules around health claims. We grew their qualified patient pipeline by 84% without touching a claim that couldn't be defended.

The Situation

Medical paid advertising requires working within Google's health policies while still reaching patients who genuinely need wound care. Previous campaigns were generic — "wound care near me" — with no separation between patients they could serve well and those who needed a different care level. Cost per inquiry was high, and the intake team was screening out more than 60% of contacts as unqualified. Physician referral traffic wasn't tracked separately from patient acquisition, so budget allocation was guesswork.

What We Did

We restructured campaigns around condition-specific intent — diabetic wound care, chronic non-healing wounds, pressure ulcer treatment — and built separate funnels for patient acquisition versus physician referrals. Each ad drove to a condition-specific landing page that pre-qualified the inquiry before the form. Referral physician outreach was layered via Display and tracked independently so budget could flow to the higher-ROI channel. Policy-compliant copy focused on care approach rather than outcome claims.

“The intake team went from screening out 60% of inquiries to closer to 20%. Same calls, much better fit.”

— Operations Director, US Wound Care

Visit US Wound Care

+84%

Qualified patient inquiries

condition-specific landing pages + intent targeting

−36%

Cost per new patient inquiry

better funnel filtering, less waste

3.1×

Physician referral pipeline

Display + referral-specific targeting

92%

Target-market impression share

across wound care search terms in service area

More results

Anonymized at client request.

Numbers are real. Industries and identities are not disclosed.

DTC E-CommercePaid Media90-day engagement

$85k/mo spend · Google + Meta · 2.1× ROAS · last-click attribution

Six months of increased spend. ROAS went nowhere. Turns out 38% of the budget was funding channels that never drove a single purchase.

The Problem

The marketing director had been telling the board ROAS was "stable." What she didn't know: 38% of monthly spend was cycling through social touchpoints that never influenced a purchase — they just happened to appear before a conversion that was going to happen anyway. Attribution was last-click only, so the channel that got the final click took all the credit. The channels doing the actual work got defunded. She'd been optimising the wrong thing for six months.

What We Built

We rebuilt attribution before touching a single campaign. A data-driven multi-touch model exposed exactly where spend was leaking. Within 14 days, ML bidding was live across Google Shopping and Meta — reallocating budget toward high-intent signals in real time. A structured creative testing cadence identified winning formats in the first two weeks. No budget increase. Just the same money going to the right places.

“"Stable ROAS" meant we weren't looking hard enough. The data was there the whole time. We just weren't reading it right.”

— DTC E-Commerce Client

5.4×

ROAS at 90 days

up from 2.1× at engagement start

38%

Wasted spend recovered

redirected to top-performing segments

14 days

To first optimization

ML bidding live within two weeks

+61%

Revenue per session

driven by creative and audience changes

Read the DTC playbook

B2B SaaSLead Funnels60-day engagement

$40k/mo on paid search · 40 demos/wk · 4% close rate · one-field form

40 demos a week. 4% close rate. The problem wasn't the pitch — it was who they were pitching to.

The Problem

Their sales team was running 40 demos a week and closing barely 4% of them. Not because the product was wrong — it wasn't. Because the "Book a Demo" button on the website booked a demo with literally anyone who clicked it: students, competitors, people who confused it with another product, companies with no budget. The AE team was burning most of their week on calls that were never going to close.

What We Built

We replaced the single-field form with a 5-step conversational qualifier. AI branching logic scored each prospect on company size, use case, and budget fit before a calendar slot was ever offered. High-intent leads went straight to an AE. Everyone else entered a targeted nurture sequence. CRM automation was rebuilt so every handoff arrived with full qualification context — no more AEs doing discovery on calls that should have been emails.

“The AEs came back after week one and said the calendar felt completely different. Same number of demos booked. Just people we actually wanted to talk to.”

— B2B SaaS Client

71%

Cost-per-SQL reduction

qualified demo cost vs. prior funnel

4.1×

Pipeline growth

qualified pipeline in 60 days

31%

Demo-to-opportunity rate

up from 4% pre-engagement

100%

CRM context coverage

every lead arrives with full qualification data

Read the B2B SaaS playbook

Home Services FranchiseAI Automation4-month engagement

14 locations · $120k/mo · spreadsheet bidding · 30+ hrs/wk manual work

Every Friday at 4pm, the marketing manager opened 14 spreadsheets and manually adjusted bids. She'd been doing it for two years.

The Problem

One Google Ads account per location. Budget decisions made weekly, by hand, from last week's data. By the time a change went live the weekend demand surge was already over. The marketing manager was spending 30+ hours a week on bid work that kept the engine running but left no time to actually grow it.

What We Built

We consolidated all 14 accounts into a single analytics layer and built ML allocation scripts that redistribute budget across locations in real time — weighing demand signals, local weather patterns, and each location's historical close rates. Routine bid adjustments became fully automated. The 30 hours freed up went to strategy work that was previously impossible to schedule.

“I was spending every Friday doing something a machine should do. I kept telling myself the hands-on approach was the value-add. It wasn't.”

— Home Services Franchise Client

3.8×

Blended local ROAS

across all 14 locations

52%

Management overhead cut

from 30+ hrs/wk to under 15

14→1

Reporting consolidation

one dashboard replacing 14 account logins

+29%

Lead volume

same total budget, smarter allocation

Read the Local & multi-location playbook

D2C E-CommerceWeb Performance12-week build

$85k/mo paid media · 68% mobile sessions · 6.8s load time · 71% bounce rate

They'd fired two agencies for underperforming campaigns. Nobody had checked that the site took 6.8 seconds to load on a phone.

The Problem

Mobile was 68% of their traffic and 31% of their revenue. Two agencies had been blamed for it and replaced. Before touching a single campaign, we ran a real-device load test on a 4G connection. The homepage took 6.8 seconds. 71% of mobile visitors were leaving before they saw a product. $85k a month in ads was pointing traffic at a site that was bouncing most of it before anyone could buy.

What We Built

A full Core Web Vitals audit traced the problem to an unoptimised image pipeline, render-blocking third-party scripts, and zero edge caching. We rebuilt image delivery with next-gen formats and lazy loading, moved product pages to server-side rendering, and deployed Cloudflare Workers for edge caching. LCP dropped from 6.8 seconds to 1.4 seconds on a real 4G device. Not a single ad was changed during the entire 12-week build.

“We'd spent two years blaming campaigns for mobile numbers. The problem was the website. We fired two agencies for something that was never their fault.”

— D2C E-Commerce Client

3.1×

Mobile conversion rate

on identical traffic and spend

1.4s

LCP on 4G

down from 6.8s before engagement

Lighthouse score

avg across all product page templates

−83%

Bounce rate

on mobile product pages post-launch

Read the DTC playbook

B2B SaaSAttribution & Dashboards3-week build

4 ad channels · Google Sheet reporting · 8 hrs/wk to update · budget on gut feel

They'd been cutting LinkedIn's budget for a year because last-click made it look bad. It was actually their best-performing channel.

The Problem

Four ad channels. A Google Sheet that took 8 hours to update every Friday. Budget decisions were made on last-click data and gut feel. LinkedIn looked bad on every report, so its budget kept getting trimmed. What they didn't know: LinkedIn was responsible for a disproportionate share of deals that actually closed. Last-click couldn't see it because LinkedIn touches happened early in the journey, long before the final conversion.

What We Built

We built a Clickhouse + dbt pipeline pulling data from every ad platform, Salesforce, and Stripe into a single source of truth. A custom dashboard showed MQL, SQL, and ARR attribution by channel, cohort, and campaign — updating every 15 minutes. In the first week of live data, LinkedIn showed the highest pipeline-to-ARR conversion rate of any channel at nearly half the cost-per-opportunity.

“First week of real attribution data was a genuinely uncomfortable conversation. We'd been punishing LinkedIn for a year for a problem that was our measurement, not their performance.”

— B2B SaaS Client

4.1×

LinkedIn ROAS revealed

previously underfunded based on last-click

8 hrs

Weekly reporting eliminated

live dashboard replaced the spreadsheet

$1.2M

Misattributed pipeline

identified in first 30 days of live data

3 wks

Build to deployment

from data spec to live production dashboard

Read the B2B SaaS playbook

All results reflect actual engagements and each client's specific starting conditions, market, and budget. Individual results will vary.

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