Performance Marketing That Actually Performs
With 15+ years of hands on experience running paid campaigns across Google, Meta, and TikTok, I know what separates profitable ads from wasted budget. I combine deep platform expertise with data science to build campaigns that scale across search, social, video, and shopping.
I offer fixed PAYG packages charged by the hour or a commission based model where my income depends on my success, ensuring measurably better performance.
Channels deliver the data, data science delivers the insights, and the budget moves to where it earns the most.
Unlock a Premium Performance Marketing Arsenal
Partner with me and receive over £2,500 worth of powerful research, execution, and automation tools, completely free.
Where ad budgets go to die
Most ad spend buys clicks, not customers
Paid ads are the fastest way to burn money when nobody is watching the right numbers. Budgets quietly leak, agencies optimise for the metrics that flatter their reports, and the line from spend to actual revenue never gets drawn.
- Vanity metrics, not sales
- Impressions, clicks and likes look busy on a dashboard while the only number that pays the bills, profit per pound spent, goes unmeasured.
- An agency paid to spend more
- When the fee is a percentage of budget, spending more is the incentive, whether or not it actually works for you.
- Set and forget waste
- Campaigns left on autopilot keep paying for search terms, audiences and placements that never convert.
- No line to revenue
- Tracking that was never wired up properly, so you can guess what worked but never prove it, and never double down with confidence.
Why me
15+ years of spend, run by the person who reads the data
I am Georg. I have run paid campaigns across Google, Meta and TikTok for 15+ years, and I pair that with real data science, so every pound is measured against profit, not applause. My income can even ride on your results. One person on the tools and on the hook, not a junior burning your budget to hit an agency target.
The Difference
Good and bad performance marketing look the same from outside
Both run on Google, Meta or TikTok. Both produce dashboards full of numbers. The difference is what happens around the ads: what gets measured, what gets questioned, and what evidence budget decisions are based on. That difference is data science, and it decides whether your ads compound or burn.
How budgets get burned
- Campaigns set up once, then left running on autopilot
- Optimised for clicks and CTR because they are easy to present
- Platform dashboards treated as the truth about revenue
- Budget split by gut feeling or by last year’s plan
- A hand made PDF report at the end of the month
- Nobody asks which sales would have happened anyway
This is the industry default. It feels like marketing, it reports like marketing, it just does not earn like marketing.
How ads compound
- Tracking strategy first, so every euro is measurable ↗
- Optimised for revenue, margin and customer lifetime value
- Own tracking that cross checks the platforms instead of believing them
- Budget follows marginal returns, shifted week by week
- Dashboards that build themselves, live for every level ↗
- Incrementality tested: holdouts show what the ads truly add
Every one of these runs on data science. That is not a coincidence, it is the whole point.
Agency vs Me
What you get from an agency, and what you get from me
Agencies are not evil, they are built for scale: dozens of accounts per manager, standard playbooks, monthly reporting cycles. That structure is exactly what caps your performance. Here is the honest comparison.
Reporting
Typical agencyA monthly PDF, assembled by hand, quietly eating a chunk of the retainer
With meLive dashboards for every role, updated by themselves, open any time See how reporting works
KPIs
Typical agencyImpressions, clicks, CTR and whatever the platform calls a conversion
With meRevenue, margin, LTV and what is provably incremental
Budget decisions
Typical agencySet quarterly, defended in meetings
With meShifted weekly along marginal ROAS and seasonality forecasts
Tracking
Typical agencyThe platform pixel, taken at its word
With meServer side, consent proof, first party, cross checked against your backend
Who runs your account
Typical agencyA junior you never meet, juggling forty accounts
With meMe. The person you talk to is the person inside the account
Contract
Typical agencySix to twelve months with notice periods
With meMonthly. And it starts with a free workshop See how the workshop works
Ownership
Typical agencyAccounts and data sometimes live with the agency
With meEverything is yours: accounts, tracking, data. If we part, it all stays with you
Multi Platform Expertise
One Strategist. Every Major Ad Platform.
Running ads on a single platform limits your reach. I plan, launch, and optimise campaigns across Google, Meta, and TikTok so your budget goes where your customers actually are.
Google Ads
Search, Shopping, Display, Video, and Performance Max campaigns built for intent driven traffic and measurable conversions.
- Search & Shopping Ads
- Performance Max Campaigns
- YouTube & Video Ads
- Display & Remarketing
Meta Ads
Facebook and Instagram campaigns designed around audience targeting, creative testing, and full funnel attribution.
- Awareness & Reach Campaigns
- Dynamic Creative Optimisation
- Retargeting & Lookalike Audiences
- Conversion & Lead Gen Campaigns
TikTok Ads
Short form video campaigns that capture attention, drive engagement, and convert younger and trend driven audiences.
- Spark Ads & In Feed Video
- Interest & Behaviour Targeting
- TikTok Shopping Campaigns
- Creative Performance Analytics
Beyond the Big Three
Every other channel worth your ad spend
Google, Meta, and TikTok are the core, but profitable audiences live far beyond them. These are channels I run when the numbers say your paying customers are there. And the list is not the limit: 15+ years of campaign data tell me where buyers actually come from, and that is exactly where we advertise.
Spotify Advertising
Audio and podcast ads to reach engaged listeners during commutes, workouts, and work hours.
Amazon Advertising
Sponsored Products, Brands, and Display Ads to capture high intent shoppers on the world's largest marketplace.
Snapchat Ads
AR lenses and vertical video ads to reach Gen Z and millennial audiences that other platforms struggle to engage.
LinkedIn Ads
B2B targeting by job title, company, industry, and seniority. The only serious channel for most B2B sales motions.
Quora Ads
Intent driven ads on high quality Q&A content. Strong for SaaS, finance, education, and considered purchases.
Microsoft/Bing Ads
Lower CPCs and older, higher income audiences. Works particularly well for B2B and finance verticals.
Twitch Advertising
Video and display ads inside live streams. Unmatched for gaming, tech, and young male audiences.
And many more
Reddit, Pinterest, Apple Search Ads, native networks, podcast sponsorships, influencer whitelisting: if your paying customers are there and the margins work, I will run it and measure it.
Not sure where your customers are? That is the first thing we find out. Book the free workshop
Beyond the Obvious
The tactics big companies use and most advertisers never touch
Search and social are table stakes: everyone runs them, so nobody wins with them alone. The advertisers who pull ahead use tactics that never appear in a standard agency playbook. Notice the pattern: every single one runs on data science.
Incrementality Testing
Geo holdouts and switchback tests reveal which sales the ads actually caused. The grown up answer to “would they have bought anyway?”
Value Based Bidding
Predicted lifetime value flows back into the auction, so platforms bid for your best future customers instead of whatever clicks cost the least.
Data science insideServer Side Tracking
First party events, Consent Mode and server side APIs keep measurement working while browser tracking crumbles under privacy rules.
Marginal ROAS Budgeting
The last euro matters, not the average. Budgets move to wherever the next euro earns the most, recalculated continuously.
Data science insideForecast Based Pacing
Spend rises into strong periods and pulls back before soft ones, driven by seasonality models instead of a static monthly cap.
Data science insideCreative Testing Matrices
Hooks, formats and angles tested systematically with proper statistics, so winners are proven, not guessed.
Brand Cannibalisation Tests
Pausing brand keywords in test regions shows how much of that shiny ROAS you were buying from yourself.
Attribution Triangulation
Platform claims, analytics, post purchase surveys and models compared against each other, because no single source tells the truth.
Data science insideAll of this is exactly what the data science page describes, applied to paid media. That is why the two services are inseparable. Explore the data science behind it
Data Science Meets Paid Media
Smarter Campaigns Through Data Science
Most marketers optimise by gut feeling. I use statistical models, first party data analysis, and automation scripts to find the signals that actually move the needle, then build campaigns around them.
First Party Data Activation
I help you build and activate your own customer data for targeting, segmentation, and personalisation across every platform.
Predictive Analytics & Testing
From Bayesian A/B testing to predictive LTV models, I use real statistical methods to make better decisions faster.
Custom Attribution & Reporting
I build attribution models that reflect your actual customer journey, not just last click defaults. Clear dashboards, no vanity metrics.
My Data Driven Process
From Strategy to Scale. How I Work.
Every engagement follows a structured, data driven process. I cover every stage from initial research and tracking setup through to creative execution and ongoing optimisation, ensuring nothing gets lost between strategy and results.
Discovery & Strategy
I start by understanding your business, your margins, and your audience. Market analysis, competitor research, and persona mapping lay the groundwork for campaigns that hit the right people at the right time.
Tracking & Measurement Setup
Before spending a single pound on ads, I make sure your tracking is airtight. Server side tagging, conversion APIs, UTM frameworks, everything documented and tested so we know exactly what is working.
Campaign Build & Launch
I build campaigns across Google, Meta, and TikTok tailored to your goals, whether that is lead generation, eCommerce sales, or brand awareness. Every ad, audience, and bid strategy is set up with purpose.
Optimisation & Testing
Once live, I continuously test creatives, audiences, and bidding strategies. A/B tests are run with statistical rigour, not guesswork. Budget shifts where the data says it should.
Reporting & Insights
You get transparent, real time reporting that focuses on the metrics that matter: ROAS, CPA, LTV, contribution margin. No fluff, no vanity metrics, just actionable numbers.
Scale & Expand
When we find what works, we scale it. New platforms, new markets, bigger budgets, all backed by the data that proved the approach first.
What You Receive:
- Multi Platform Campaign Management: Campaigns built and managed across Google Ads, Meta Ads, and TikTok Ads, all coordinated under one strategy.
- Full Funnel Ad Coverage: From top of funnel awareness on TikTok and Instagram to bottom of funnel search and shopping ads on Google. Every stage covered.
- Tracking Setup & Housekeeping: Server side tracking, conversion APIs, and GA4 configuration included. If your current setup is messy, I clean it up for free.
- Creative Strategy Support: Ad copy, audience segmentation, creative briefs, and landing page recommendations tailored for each platform.
- Advanced Data Analysis: Custom dashboards, attribution modelling, and statistical testing that go far beyond what standard ad platforms provide.
- Cross Platform Budget Optimisation: I shift spend to whichever platform and campaign is delivering the best results, so your total budget works harder.
My data driven approach removes the guesswork from your paid media. Every campaign decision is backed by real numbers, and every pound is tracked from click to conversion.
A Proven, End to End Approach
By combining multi platform expertise with robust tracking and advanced data analysis, I deliver a complete performance marketing service. Strategy, execution, measurement, and optimisation, all handled by one person who understands the full picture.
The Cherry on Top
Winning German Speaking Customers with Authentic, Localised Campaigns
Born and raised in Austria, half a lifetime in Britain: I run native level campaigns in both German and English speaking markets. If you ever want to expand across the DACH region, that expertise comes built in, no second agency needed.
What your data allows
Everyone promises growth. Here is what your numbers can actually carry.
Pick your industry, your traffic, your customers, your history and your budget. The planner runs the same sample size, budget and forecasting arithmetic I use before any engagement and tells you which stage you are in, what is statistically possible there, and what I would actually do with you. No email, no form, just the maths.
Your numbers
Industry
Clean historical data
Past paid campaign data
Monthly ad budget you could commit
Touchpoints you already have
Your stage
Foundations
No statistical tests yet. Best practice, clean tracking and channels that cost time rather than money carry the growth, and a small paid budget is for learning with kill rules, not for deciding.
Website tests
- Conversion rate
- 2 %
- measured from your numbers
- Visitors per variant to detect a 20% lift
- 21,110
- One A/B test on your traffic
- not in any useful time
- Tests a month at 20% lift
- 0
- 2 by 2 multivariate test in four weeks
- not yet
Nothing statistical is possible on your traffic yet. A change that doubles your conversion rate would still be invisible in a test, so this stage is about applying what is known to work and growing the traffic, not about testing.
Paid campaigns
- Assumed cost per conversion
- £30
- Conversions a month at your budget
- 10
- What that count can decide
- a signal, with a margin of error above 40%
- Days to 30 conversions
- 90
- Days to 100 conversions
- 300
- Learning budget before a channel is judged
- £1,500
- Kill rule for a losing ad
- 150 clicks without a conversion, about £120, and the ad goes
Your budget is below the learning budget for this channel. Spend it to learn about creative and audiences with kill rules, and treat every cost per acquisition you see as a rough signal, never as a decision.
Forecasting
Next month, roughly
Under six months of data supports a level forecast with a wide band and no seasonality. Expect errors of 25 to 40% or worse. A direction, re forecast monthly.
Growth curve
With no tests possible the curve is flat until the traffic grows. Best practice still moves the number, it just cannot be measured as a test yet.
What I actually do with you at this stage
- Tracking that counts each order once and attributes it sensibly, so the data is clean when the traffic arrives.
- The conversion fundamentals from 15+ years of accounts, applied without waiting for a test to confirm them for you.
- Channels that cost time rather than money, and the direct routes above where they fit your industry.
- A small paid budget run on brackets and kill rules so it teaches something without pretending to decide anything.
15+ years of growth, performance marketing and data science work, from well before the AI hype, are the prior that makes the small stages productive and the big ones honest. Nothing here assumes you already have the data. It assumes you want to know what you can do with the data you have.
Assumptions: 95% confidence and 80% power for tests, a two week to four week window, one win in three at a 6% real lift per completed test, and illustrative late 2026 UK and DACH costs per conversion by industry. Your competition, product, geography and season move those costs, which is exactly what the workshop pins down.
The Fears
Every fear you have about performance marketing is justified
Burned budgets, opaque agencies, lock in contracts, reports nobody understands. That is not paranoia, that is the industry standard. Here is how each fear is handled when you work with me.
“We tried ads once and burned money.”
Almost always a measurement problem, not a channel problem. We start small, define kill rules upfront and only scale what proves itself with real numbers.
“I have no idea what the agency actually does all month.”
Every change is logged and every number lives in a live dashboard. You see exactly what I see, at any time of day.
“The contract locks us in for a year.”
My terms are monthly. If the numbers do not convince you, you walk. The results are the retention strategy, not the notice period.
“The reports are jargon nobody reads.”
Insights arrive as one plain sentence you can act on, with the statistics behind it if you fancy a look.
“Who owns the accounts and the data?”
You do. Your ad accounts, your tracking, your data. If we ever part ways, everything stays with you, fully documented.
“How do I know the ads add anything at all?”
Performance is measured against modelled baselines and holdout tests, never against the platform praising itself.
Still cautious? Good. Caution is a data driven trait.
That is exactly why we start with a free workshop, followed by two weeks of real work on me: plans, forecasts, tracking review and honest numbers, no strings attached. If I am the wrong person for your case, I will say so and point you to someone better suited.
Where Numbers Speak Louder Than Words
The Impact in Numbers
My data driven approach consistently delivers measurable results across Google, Meta, and TikTok, from higher growth rates to lower acquisition costs. Here is a snapshot of what you can expect:
- Average Growth Rate
- 30%
- Ad Spend Savings
- 25%
- Peak Campaign Budget
- 450k
- Average Daily Budget
- 39k
- Cost Savings Through Automation
- 20%
- Conversion Rate Increase
- 35%
- Cost Per Acquisition Reduction
- 30%
- Campaign Turnaround
- 50%
Ready to Scale Your Paid Media?
Whether you are running ads on Google, Meta, TikTok, or all three, I can help you get more from every pound. Contact me for a free consultation and let's build a performance marketing strategy that actually delivers.
AI writes the code. Who is responsible for it?
Budget follows the tracking. If the tracking is wrong, so is every decision
Ad platforms will happily optimise towards a broken conversion event. The expensive part of performance marketing is not the ads, it is being sure what they caused.
Conversions that count the wrong thing
Every conversion is wired, named and tested end to end, from click to the record in your system, before a pound is spent against it.
Breaking consent law to get a number
Front end tracking gated by consent, server side events renamed without it, no audience ever built from someone who said no. Legal advice turned into code.
Reports that flatter the agency
You own the accounts, the data and the dashboards. Spend, cost per lead and revenue are reconciled against your books, not the platform's version of events.
Where AI builds, where I decide
Low risk: AI builds, I glance
- Layouts and styling
- Forms and validation
- Boilerplate off the critical path
- Seed data, scripts, docs
Medium risk: AI drafts, I edit
- Edge cases for the tests
- Review as a second reader
- Refactoring under green tests
- Release notes from the tests
Critical path: I decide, AI advises
- Architecture and data model
- Money, tax, payments
- Authentication and permissions
- Every verified critical path
The lower the blast radius of a mistake, the more AI builds alone. The higher it is, the more it advises while a person with a name on the contract decides, reads and tests.
Why that costs you less, not more
- Account manager
- Project manager
- Designer
- Developer
- QA
- One accountable engineer
- AI on the low risk work
Agency team
Me, with AI
The hours for layouts, forms, scaffolding and documentation have collapsed, and that saving is in my package prices. The hours for judgment, architecture and proof have not, and that is what you pay for. One person, no hand-offs, no coordination overhead, and more tests than before because writing them is no longer the expensive part.
What you can check, not just read
- Tests you can read in plain language in your client hub
- Critical paths verified and frozen behind approval
- A release register and an audit log
- Code, data and infrastructure in your name
AI changed who writes the code. It did not change who answers for it.
How every engagement runs
Enterprise discipline, one person
Anyone can promise quality. I run every engagement through systems that prove it: a real client portal, legal clarity before work begins, and evidence for every release. This is what working with me actually looks like.
Your own client portal
Every client gets a seat in the Keferboeck Hub: onboarding, documents, dashboards and live project links in one place. Structured from day one, so nothing important ever lives in a lost email thread.
Legal clarity before work begins
Contracts, terms and insurance documents live in a portal vault. Signed versions are locked forever, every view and download is logged, and onboarding includes a formal review and acceptance step, with the option to hand it straight to your legal team.
Every release documented
Production releases are versioned, timestamped and written up: what was added, what changed, what was removed. You can always answer the question "what exactly went live, and when", because the record exists.
Tests gate every release
The full TDD and BDD suites must pass before anything reaches production, and the runs are recorded as evidence, with coverage tracked. A release that has not proven itself does not ship.
Verifiable by third parties
Critical business logic, how a calculation works, which legal documents a signup binds, is written up in plain language, approved by you, frozen at that state, and exportable as a PDF in English and German for your auditor. Changes reopen the approval, so the record never drifts from reality.
Security tested
Major production releases get web application security testing on top of the automated suites, grounded in formal offensive security training. Systems that hold customer and payment data deserve nothing less.
Insured, properly
A comprehensive insurance package is in place through the broker JMG: professional indemnity, public liability, employers liability and cyber cover. The insurer knows explicitly that my systems handle accounting grade workloads for SaaS products, loan interest and repayment calculations included, so exactly that work is covered.
And if I fall under a bus?
Everything is documented: architecture, decisions, processes, tests and the code itself, all written for the next person to pick up cold. If anyone else ever needs to take over, for any reason, the handover is instant and smooth. No key person risk, no vendor lock in, no hostage code. Very few agencies can honestly offer that; almost no freelancer can.
The other side of that coin: I play a central role in every project and I take responsibility for it. I do not vanish the moment a better offer turns up. The setup is simply built to change as you grow. When the workload gets massive, parts of what I do can move in house, your team owns the day to day, and I focus on whatever challenge matters at that stage of the growth cycle. That is the plan working, not a breakup.
How working with me runs, in full