About me
I studied Chemistry at the University of La Laguna and worked briefly as a chemist. From there, I worked as a data analyst in Gdynia, Poland, covering Latin American and European markets, sold B2B SaaS in Galway, and joined Expedia to work on the Spanish market. In 2020 I found my place in performance marketing, and I have focused on paid acquisition ever since.
I like working from data, building clear processes, and testing ideas quickly.
I have lived and worked in Ireland and Poland.
Learning and community
In 2026 I completed "Small Business on Social Media", a course run by La Laguna City Council, and built connections with local content creators.
Outside work, you'll find me hiking, growing plants, swimming at the pool, or out with my dog, Goofy.
Experience
Senior Media Buyer and team lead, The Red Club
January 2026 to August 2026, remote
Search-arbitrage acquisition across 60 countries on Meta, Taboola and Outbrain. Managed 3 direct reports and 1 indirect report.
Senior Media Buyer and team lead, Alegro AI
May 2023 to November 2025
Launched paid acquisition from zero and scaled to a peak of over €220K a month, mainly on Google Display, with Meta, TikTok and native. Mentored up to 3 media buyers. Travelled to Amsterdam in June 2023 to meet Visymo, a monetisation partner.
Business trip to meet Visymo, Amsterdam, June 2023 Media Buyer, Explorads
October 2022 to April 2023
Built Google Ads and Display accounts from scratch, ran tests, and gave feedback on tracking. Joined the company's annual meeting in Dubai in February 2023.
Explorads annual meeting, Dubai, February 2023 
With colleagues and the company's directors Team Lead, Performance Marketing, Pearch Digital
May 2022 to October 2022
Set up the native operation on Taboola and Outbrain with 3 direct reports. Joined the company's quarterly meeting in Dublin in 2022.
Pearch Digital quarterly meeting, Dublin, 2022 Digital Media Buyer Specialist, adoclic advertising
July 2020 to April 2022, Tenerife
Native and display campaigns, search arbitrage and lead generation on Taboola, Outbrain and MGID.
Team celebration at the adoclic office Market Associate, Expedia Group
January 2018 to March 2020
Spanish market. Led email marketing and proof-of-concept projects, coordinating more than 25 contributors (project coordination, not line management). Co-organised team events in November and December 2019.
November 2019 
December 2019 Events I co-organised with my team at Expedia.
SDR to Sales Executive, SiteMinder
January 2017 to November 2017, Galway
B2B SaaS sales for hotels, including product demos.
Data Analyst, Refinitiv
May 2015 to January 2017, Gdynia
Market data for Latin America, Spain, Portugal and Romania.
Education: Degree in Chemistry, University of La Laguna
The Red Club, January to August 2026
Turning a loss-making search-arbitrage programme profitable, then scaling it
ROI from −62% to +17% in three months, with daily spend scaled from €90 to €2,300+.
Senior Media Buyer and team lead, managing 3 direct reports and 1 indirect report. Meta was the main channel, with Taboola and Outbrain alongside.
Read the Red Club caseShow less
The situation
A search-arbitrage (RSoC) programme: we bought traffic on Meta and native platforms and earned revenue from search ads on partner pages. It started at about €90 a day and was losing money: in April, ROI was −62% and only 7% of days were profitable. The goal was to grow spend without giving the margin away.
What I did
- Structured the account by vertical and country, with a naming standard (country, keyword, platform, device, campaign type, channel) so anyone on the team could read performance quickly and act on it.
- Tested at volume: 4,046 campaigns, about 3,700 of them tests. Around 13% of the campaigns that spent became profitable, so budget moved to those and the rest were cut early.
- Scaled winners by adding new creatives to winning keywords, extending to other devices and countries, and testing related angles with broad targeting. I stopped scaling when new angles came back at breakeven.
- Tested Max Value against Target ROAS bidding in Meta after noticing a partner using it. On the right niche it improved profit by about 25%.
- Convinced a partner to give us a test domain. The same campaigns went from barely breakeven to 120% ROAS.
- Pushed back on a request for 100 new campaigns a day. With most new campaigns failing at that stage, that volume would have burned budget, so I proposed building a profitable base first and scaling as the success rate improved.
Results
Daily spend on the programme Hover or tap for details
Monthly figures are average spend per day. "Late Aug" is the average of the last week of August.Account ROI by month Hover or tap for details
A 7-day period in August
What carries over: the same loop of testing fast, reading the data honestly, scaling winners and cutting losers works for any paid acquisition goal, whether that is sales, leads or sign-ups.
Scale came from a controlled process, not from raising budgets. Most tests fail, so the system has to find the few winners fast and cut the rest before they cost too much. The market with the most spend, the US, was losing money; the most profitable markets were smaller ones that were easy to overlook.
The Red Club, 2026
Catching tracking problems before they cost money
Found a partner tracking bug that affected all of their clients, before the partner did.
In arbitrage, revenue is reported by the monetisation partner. If their tracking breaks, you are spending blind.
Read the tracking caseShow less
How I spotted it
I compared Meta conversions against the partner's reported conversions and noticed a small drop in revenue that did not match what the ad platform showed. I escalated it twice. The partner investigated and found a bug that was affecting all of their clients.
Handling a reporting outage
- When the partner's revenue reporting stopped while campaigns kept spending, I cut budgets on the weakest campaigns first.
- Paused campaigns close to breakeven after two days without reliable data.
- Prepared campaigns in advance so we could relaunch quickly, then recovered spend in phases once the data was trustworthy again.
- Used a minimum conversion threshold per channel and country before trusting a signal, so decisions were not made on noise.
Tracking QA is part of media buying, not someone else's job. Checking pixels, conversion events, postbacks and attribution against a second source is what protects the budget.
Alegro AI, May 2023 to November 2025
Launching paid acquisition from zero and scaling to over €220K in a single month
~€207K profit at ~21% ROI over 12 months, with €222K spend in the peak month.
Senior Media Buyer and team lead. Mentored up to 3 media buyers and was the team's main point of contact for about 6 months. Google Display was the main channel, alongside Meta, TikTok, Taboola and Outbrain, with short periods on Google Search and Performance Max.
Read the Alegro AI caseShow less
The situation
New paid acquisition accounts starting from €0. The goal was to find profitable keywords and angles quickly, then scale them.
What I did
- Started with market research: checked what competitors were running in the Google Ads Transparency Center, looking for patterns in their ads and angles.
- When a pattern appeared, searched Google and analysed competitors' landing pages to find the keywords they were targeting.
- Expanded keyword ideas with Google search suggestions and Keyword Planner.
- Used partner data from Visymo on which keywords were getting the most traffic, with revenue per click (RPC), revenue and reported conversions, to decide what to launch first.
- Launched paid acquisition accounts from €0, tested them to profitability, and handed stable channels over to new specialists.
- Ran performance reviews, training and issue resolution for the team, and set KPIs and optimisation processes.
- Created an issue-report template for the IT team (error, description, how to reproduce, suspected cause, priority) so problems were fixed faster.
Results
My share of the team's profit, November 2024 to March 2025 Hover or tap for details
The largest share of team profit every month in this period.
12-month figures cover November 2024 to November 2025, excluding one month with a reporting adjustment.
What carries over: I start with research, not guesses. Competitor ads, search demand and partner revenue data decide what gets tested first.
The Red Club, 2026
Cutting campaign creation from 70% of the working day to 20%
Campaign creation cut from ~70% to ~20% of the working day, with checks kept in place.
Testing at volume only works if launching campaigns is fast and consistent.
Read the workflow caseShow less
What I did
- Built a campaign-creation workflow with ChatGPT and Claude on my own, without the tech team.
- Added a tool that detects each keyword's language and assigns the right tags automatically.
- Kept the naming standard and pre-launch checks in place, so speed did not cost accuracy.
- Managed creative output of around 150 to 300 ad variations a day, using AI tools and briefs for designers.
Pearch Digital, Alegro AI and The Red Club
Leading and developing media buyers
Built a native team of 3 from scratch and turned a struggling team member into the top performer.
Read the leadership examplesShow less
Building a native team from scratch
As Team Lead at Pearch Digital (2022) I set up the native operation on Taboola and Outbrain with 3 direct reports who were new to native. I taught the basics (allowed images, verticals, how to launch) and left the creative style to them, then ran inspiration sessions. They were performing within a short time.
Turning around a struggling team member
I took on a team member who was struggling. I wrote how-to guides by email, started with a call on the basics, then held short daily task calls. They ended up outperforming the rest of the team.
Structure that helps a team move faster
Account structure by vertical and country, a shared naming standard, and a task-assignment structure for the IT team so requests were clear and prioritised.
How I work
- With incomplete data, I test several countries, verticals and creatives at once and use keyword tools and competitor activity as early signals. I only drop a vertical when all of its creatives have failed.
- I scale by expanding what already works: new creatives on winning keywords, new devices and countries, related angles.
- I explain the numbers when a target is unrealistic, and I bring a recovery plan when a target is missed.
Channels and tools
- Meta Ads
- Google Ads (Display, Search, Performance Max)
- TikTok Ads
- Taboola
- Outbrain
- MGID
- Search arbitrage / RSoC
- Pixels, conversion events and postbacks
- Looker Studio
- Excel / Sheets
- Monday.com
- Notion
- ChatGPT and Claude