Meet Lace Rogers our brilliant new Head of Analytics and Data

Written by Lee Colbran - 20 Jul 2022

Culture | 7 MIN READ

We caught up with Lace Rogers, who joined to head up our Analytics and Data team. We asked Lace about her career to date, her vision for the role, and what colleagues and clients can expect.

Headshot of Lace Rogers

I've always loved working with code and data and using this to build actionable processes, visualisations and insights. I love that every day brings a new challenge, and there is always something new to learn.


Lace Rogers, Head of Analytics and Data 

Firstly, welcome, Lace. It's great to have you here. Tell us about your career path to date and what made you enter the world of analytics and data?

I had a pretty unusual journey into analytics as I initially studied Gemology with the Goldsmith guild but moved into financial services, where I had the opportunity to work with data and code in a risk strategy team. I took a huge risk in 2014, moving into mobile apps (back when free-to-play apps were a relatively new concept) and managed everything from data and analytics to marketing to in-app promos. I've always loved working with code and data and using this to build actionable processes, visualisations and insights. I love that every day brings a new challenge, and there is always something new to learn.

What made you choose Fresh Egg as the next step in your career path?

It's a fascinating time to be in data and analytics. Fresh Egg is an excellent step for me to work in an agency with a broad range of services covering some attractive sectors alongside continuing to focus on the Google Marketing and Google Cloud Platform stacks. I also liked that while Fresh Egg has about 70 employees, there is still a hugely welcoming culture, and people genuinely love working at the company and together. The team are incredibly supportive and approachable, from the newest people to the most senior.

How do you stay on top of changes in the ever-changing world of analytics and data?

Google, Medium and Github are (categorically) my best friends for changes in coding and Google analytics, as there is a dedicated community of bloggers and specialists who share and are helping drive the development and knowledge of the tools we are using. Likewise, I'm also a great believer in the 'Hive mind'. No one team member can know everything but communicating and sharing changes and findings as a team and the wider community helps drive collective knowledge and development.

How has the world of analytics changed as a specialism during the last year?

It's growing by the day. With the onset of GA4, we're seeing teams pick up more technical skills on GCP and have the ability to tell a story with the data. Marrying app and web data together makes the data world more aligned with how customers use these tools. Most of all, I have seen great work and collaboration from people who are relatively new to the industry, which has helped shake us out of the comfort zone of Universal Analytics. I feel specialists, in general, are driving the charge forward in changing the perception of data and the way we use and look at data. 

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What impressed you during your interview process?

The interview process was a great experience and was smooth sailing from start to finish. The interviews were friendly, and the team immediately put me at ease, removing any of those pre-interview nerves. I was incredibly impressed with the communication with Emma, who heads up recruitment. Emma took me through the steps alongside and gave me plenty of support in preparing to start the role. I've been blown away by the onboarding process, which was incredibly organised and, despite being remote, helped me feel very much part of the team.

Other than Google Analytics, what is your go-to tool?

I would say BigQuery and Python, as these languages work seamlessly with the Google stack, especially with the frequent release of new features to make data engineering and analysis more manageable than ever. Additionally, the GA4 BigQuery dataset takes Google analytics analysis to a new level, allowing you to join data quickly and build in-depth, actionable analytics to propel companies even further in optimising their websites, apps, marketing and much more.

What do you consider to be some of the most significant client challenges with data?

We work in an industry which is moving fast, and as a result, clients can find it hard to keep abreast of these changes. Google Analytics 4 has fundamentally changed how we analyse web and app data, including what KPIs we track. Additionally, the tools available in GA4 are different, and this can be challenging to get used to, which is something as a team we are proactively supporting to help clients overcome. There are sometimes worries about how much these tools and changes will cost. Still luckily, tools such as BigQuery and Data Studio are incredibly cheap to use and can significantly reduce the time spent on mediating sampling and manual reporting.

How do you see analytics and data progressing in the future? What are you excited about?

The great thing is that we already have seen this change in the app development industry with Firebase, the pre-curser to GA4, where small companies can now build tools which would historically only be accessible to bigger organisations. These help drive optimisation and proactively utilise their data to automate intelligent solutions and save time in reporting. I'm excited to see even smaller clients become data-driven organisations and how much time we can save automating the manual stuff.

Adobe Analytics or Google Analytics 4 and why?

I'm a die-hard fan of Google Analytics 4, and this is because I've worked with Firebase when it first launched for mobile apps and have subsequently seen how much this has grown the data intelligence in the industry since 2016. My allegiance is partly because new features frequently drop, which reduces the friction between generating data and leveraging it.


The other primary reason is cost. GA4 is accessible to companies big and small, coupled with the low cost of data storage in GA4 and the almost free dataset. So, companies that may not be able to budget for Adobe can budget for GA4. The technology means complex analytics (which historically were inaccessible to these companies) are now available and will help organisations grow.

How do you see AI making a difference in data analytics in the future?

AI is already making a huge difference and is here to stay – but it might not be immediately apparent what you are using is powered by AI. The fantastic Auto-Generated Insights, anomaly detection, and the Ask Questions feature available on the GA4 UI are all powered by AI.

The machine learning capabilities for predictions are groundbreaking because you do not need a programmer to accurately predict your churn and spenders (I found these to be more accurate than predictions via my code). AI is also used extensively in Google Cloud Platform, even down to letting you know excess permissions for users.

In the future, I hope that AI will more seamlessly reduce manual insight and reporting to free up time for valuable, actionable insights and processes and make data more accessible to non-programmers and specialists.

Do your friends and family understand what you do for a job?

Luckily many of my friends know what I do, as I'm a little obsessed with data and don't stop talking about it (I have the mug to prove it). Those not in the know and my family believe my job is something to do with maths, fixing computers or building websites. So much so, I've now learnt to fix computers.

Your favourite way to eat an egg?

I am always a fan of a frittata, especially with extra chillis.

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