Every type of work
I actually do.

Full diagnostic of campaign structure, bidding logic, audience targeting, tracking setup, and wasted spend. The starting point for any serious improvement.

Reviewing what searches are actually triggering your ads. Uncovers wasted spend, negative keyword gaps, and new intent signals worth targeting.

Building keyword sets around real search intent, volume, and competition. Organised by funnel stage and match type from the start.

Mapping the intent behind search behaviour to campaign structure. Makes sure you are showing the right message at the right moment in the buying journey.

Understanding who else is bidding, on what terms, with what messaging. Identifies gaps and opportunities your current setup is missing.

Staying ahead of platform changes, new features, and market shifts that affect performance. No surprises. No missed opportunities.

Protecting your brand terms, managing CPCs, and maximising impression share against competitors bidding on your name.

Capturing high-intent demand through keyword strategy, match type architecture, and bidding logic built around real conversion data.

Intercepting high-intent prospects at the exact moment they are evaluating alternatives to you.

Prospecting, remarketing, and contextual targeting across the Google Display Network. Built to drive awareness and re-engagement efficiently.

Google's visual ad format across YouTube, Discover, and Gmail. Builds demand before someone is actively searching.

Full-funnel Google automation across all channels. Fed with the right signals, asset combinations, and bidding strategy so it actually performs.

Google's newest AI-powered campaign type. Early adoption, real testing. Knowing what it does well and where human strategy still leads.

Driving foot traffic and local conversions through location-based targeting, Local Service Ads, and store visit measurement.

In-stream, bumper, and skippable video ads across YouTube. Built around audience signals and creative hooks that hold attention past the skip button.

Product feed optimisation, merchant centre management, and shopping campaign structure built to maximise impression share and revenue per click.

Organising campaigns and ad groups in a way that gives the algorithm clean signals, makes reporting meaningful, and makes scaling logical.

Choosing the right balance of broad, phrase, and exact match to control spend, capture intent, and let the algorithm learn without wasting budget.

Grouping keywords and ads for maximum relevance. Tighter ad groups mean better quality scores, lower CPCs, and more controlled testing.

Allocating budget across campaigns, channels, and time periods based on performance data and business priorities. Not set and forget.

Building and maintaining negative keyword lists that stop budget from leaking into irrelevant searches. An ongoing discipline, not a one-time setup.

A structured approach to building negative keyword lists at campaign and ad group level. Stops irrelevant traffic, protects Quality Score, and keeps spend focused on intent that converts.

Excluding existing customers, recent converters, and low-value segments from prospecting campaigns. Keeps acquisition spend clean and prevents wasted impressions on people already in the funnel.

Letting Google optimise bids to hit a target cost per acquisition. Effective when conversion data is clean and volume is sufficient to learn.

Bidding toward a target return on ad spend. Used when conversion values vary and you want the algorithm optimising for revenue, not just volume.

Driving as many conversions as possible within a set budget. Best used in early learning phases before CPA targets are established.

Prioritising higher-value conversions over volume. Works with value-based bidding signals to attract the customers worth most to the business.

Full control over individual keyword bids. Used in low-volume accounts, new campaigns, or situations where automation does not have enough signal yet.

Manual bids with algorithmic adjustment for higher-probability conversions. A useful middle ground when moving from manual to fully automated.

Assigning conversion values that reflect real business value, not just event counts. Shifts the algorithm from chasing volume to chasing revenue quality.

Proactively adjusting bids around known demand peaks and troughs. Stops the algorithm from underbidding during your most important windows.

Regular review and action on what searches are triggering ads. Continuous refinement of what to chase and what to exclude.

Custom Google Ads scripts for automated alerts, bid rules, budget pacing, and reporting. Reduces manual ops and catches issues before they cost money.

Monitoring search volume trends and demand signals to anticipate shifts before they show up in your performance data.

Building the metrics that actually matter for your business. Not just CTR and CPC. Conversion rate by intent tier, revenue per impression, and more.

Structured experiments across copy, landing pages, bidding strategies, and audiences. Every test designed to produce a clear decision.

Channel mix strategy, budget allocation, and campaign calendar planning aligned to business objectives and seasonal demand patterns.

Excel-based forecasting models projecting revenue, ROAS, and CAC at different spend levels. Built so budget conversations happen with confidence.

Understanding how performance responds to spend changes. Identifies where you can scale efficiently and where you are already hitting diminishing returns.

A structured roadmap tying paid media to revenue goals. Channel prioritisation, budget phasing, and the milestones that tell you if it is working.

Identifying new markets, audiences, and channels ready to absorb spend. Built for businesses that have found what works and are ready to push further.

Full review of campaign structure, audience quality, creative performance, pixel health, and attribution setup. Starting point before any real improvement.

Using the Meta Ad Library and market intelligence to understand competitor messaging, creative formats, and positioning before building your own.

Understanding who your real buyers are on Meta, what content they engage with, and which signals indicate purchase intent before a single dollar is spent.

Mapping buyer intent stages to campaign types and creative formats. Makes sure you are meeting people where they are in the decision journey.

Staying ahead of Meta platform changes, algorithm shifts, and policy updates that affect campaign performance and targeting options.

Systematic review of competitor and category ads running in the Meta Ad Library. Informs creative direction before testing anything.

Reaching net-new audiences using interest targeting, lookalikes, and broad strategies. Built around creative that earns attention before asking for the click.

Sequential retargeting using pixel data and engagement signals to bring warm audiences back. Sequenced by recency and behaviour, not just a single ad.

Re-engaging lapsed customers and high-value prospects with message sequences that progress with each touchpoint rather than repeating the same ad.

Organising campaigns, ad sets, and ads in a way that gives the algorithm clean learning signals and makes performance data actionable.

Campaign budget optimisation, ad set budget allocation, and spend pacing across the funnel based on performance and business priorities.

Choosing between lowest cost, cost cap, bid cap, and value optimisation based on campaign objective, funnel stage, and conversion data quality.

Budget allocation across Meta campaign types, seasonal planning, and integration with broader cross-channel media strategy.

Modelling projected CPM, CPC, CPL, and ROAS at higher spend levels before scaling. Reduces the risk of scaling into inefficiency.

Testing how Meta performance metrics respond to spend increases. Identifies the ceiling before you hit it and waste budget finding out.

Identifying new audience segments, creative angles, and placement strategies ready to absorb spend once core campaigns are performing.

A structured system for producing, rotating, and testing creative. Moves creative decisions from guesswork to a repeatable process with clear winners.

Primary text, headlines, and CTAs built around the psychology of the scroll. Written to stop, engage, and convert without feeling like an ad.

Systematic rotation of creative assets to prevent fatigue and maintain performance. Knowing when to refresh, when to scale, and when to retire.

Structured A/B and multivariate tests across formats, hooks, and messaging angles. Every test produces a clear learning, not just performance data.

Reading creative performance data to understand what hooks, formats, and messages are resonating. Turns results into the next iteration of creative direction.

Building segmented audience lists using pixel data, first-party data, and engagement history. The foundation for both prospecting and retargeting precision.

Creating lookalike audiences seeded from your highest-value customers. The quality of the seed determines everything. Built to find buyers, not just traffic.

Customer list uploads, website visitor segments, video viewers, and engagement-based audiences. Used for both exclusion and precision targeting.

Full Meta Pixel implementation, event tracking, and Conversions API integration. Clean data in means better algorithm decisions and audience quality out.

Building the reporting columns that reflect your actual business goals. MER, revenue per lead, CLV-weighted ROAS — not just what Meta shows by default.