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It’s been somewhat of a fevered year for data and analytics.

Many marketers are still coming to terms with the move away from Universal Analytics to Google Analytics 4, as well as adapting to the ongoing deprecation of third party cookies, not to mention refining their first-party data strategies and exploring what opportunities may be presented by advances in machine learning.

So, to find out what they are hoping to see within their discipline in 2024, we spoke to three marketing measurement and analytics specialists  – Andrew Hood, CEO at Lynchpin;  John Clarvis, Data & Insights Director at The Kite Factory; and Kevin O’Farrell, Associate Vice President at Analytic Partners.

We also asked them (click to skip to):


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In one word, what are you hoping to see in your field in 2024?

‘Quality’ – Andrew Hood, CEO, Lynchpin:

“The increasing potential of ML and AI is not going to be realised without a focus on data quality throughout source pipelines. And with increasing focus on privacy in relation to digital data, (transparent) quality over quantity is becoming increasingly key.”

‘Bravery’ – John Clarvis, Data & Insights Director, The Kite Factory:

“It’s going to be a tough year, with a lot of pressure to turn analysts into conversion specialists. CRO is important, but analytics leaders need be brave enough to advocate for the long-term benefits of insight and analysis. Those that do will reap the benefits in 2025.”

Commercials – Kevin O’Farrell, Associate Vice President, Analytic Partners:

“I hope to see enhanced collaboration between marketing and commercial functions. In 2024, data, analytics, and measurement must be linked to a business’ commercial realities and used as a catalyst for business growth. CMOs must become the drivers of that commercial mindset and orchestrate future growth in line with financial business needs.

How does the tough economic climate, and business decision-making, filter down to the day-to-day challenges of the data analyst?

‘Fearful thinking’ – John Clarvis, The Kite Factory:

“Tough conditions breed fearful thinking and a focus on short term KPIs over long term brand building. There’s a lot of pressure on analysts in tough times to squeeze blood from a stone, which gets even harder a year down the line when the long-term brand damage has set in. The role can quickly switch from an insight oriented one to essentially a CRO role.  Analysts who prefer to look at the big picture tend to drop out at that point.”

‘Increased pressure’ – Andrew Hood, Lynchpin:

“Tough climates typically filter down to increased pressure and operational demand for data teams and this year has been no exception: trading and budgeting/forecasting cycles often increase in terms of frequency and urgency, and time to market for revenue generating or profit optimisation outcomes becomes all the more critical. Notably that increased pressure is not always matched with increased resource.”

The need for agility – Kevin O’Farrell, Analytic Partners:

“Businesses will have a lot on their plates in 2024. In what appears to be another year of volatile economic conditions, data analysts will need to be agile and flexible. To thrive, teams will need strong analytical and technical skills, with AI playing a crucial role in tasks like copy testing and measurement. However, regardless of the challenges you face, your fundamentals should not change. Stick to the elemental truths of marketing, avoid FOMO, and use scenario planning to stay agile and adaptable in an increasingly unpredictable future.

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How is the user/consumer’s relationship with data evolving?

LLMs and proprietary data pose new questions – Andrew Hood, Lynchpin:

“A lot of focus has been – quite rightly – on how consumer data is gathered and the transparency of that end of the value chain. Increasing visibility of the usage of models is shifting that focus more to how that data is being used and who ultimately benefits from that value: the saying used to be “if you are not paying for the product then you are the product”, but with the race to train LLMs with proprietary data it perhaps becomes less clear what that ultimate product actually is.”

Data consent has become the new ‘terms and conditions’ – John Clarvis, The Kite Factory

While there’s a sizable minority (18% of respondents in a September 2023 US study) of people who actively decline cookies or use a VPN (12%), I think to most people data consent is more of a hassle than a priority. It’s become the new “terms and conditions” for people to skim through before getting to the good stuff. There’s too much jargon and obfuscation for anyone not in the business to understand, let alone care about.

Is the shift to composable architecture changing the remit for data professionals?

The challenge is ‘maintaining good data consistency and governance’ – Andrew Hood, Lynchpin:

“A lot of data pipelines and models have typically been composable architectures for some time – the use of open source libraries and components as reusable building blocks for common use cases is nothing new for data professionals. As that approach is adopted in broader parts of incident stacks, it arguably just makes it easier to activate the data from those pipelines; the main practical challenge is maintaining good data consistency and governance when it’s being sourced from a less monolithic architecture.”

Composable makes it ‘easier to adapt’ – Kevin O’Farrell, Analytic Partners:

“With such rapidly changing business needs as a result of an evolving external environment, businesses must be able to plan ahead… Composable architecture makes it easier to adapt to changing data sources (important as retail media networks mature), regulatory changes, or emerging techniques. By being able to adapt their data software, businesses can build the most cost-effective and sustainable path forward.”

Surveys suggest the data skills gap is still evident. What more needs to be done to improve both data literacy and the number of specialists?

Hard coding and soft insight – John Clarvis, The Kite Factory:

“The skills of an Analyst and a Coder have been merging for the last decade, if you can analyse data in Python then it’s not a great stretch to start building web apps. The truth is that coders get paid a lot more than analysts, especially at junior levels, so obviously people tend to gravitate to coding. Businesses need to put their money where their mouth is if they want to increase the number of specialists.

“The biggest gap in skills I see is the hard coding skills and the softer insight skills. As analysts become more technical, they become less insightful.”

Training and careers focus – Kevin O’Farrell, Analytic Partners:

“Surveys reveal that the effective use of data requires more than just tools and AI; we still need human touch to fully leverage data. Analysts must be able to see both the big picture and the details – the ability to zoom in and out is a critical skill that is often overlooked.

“The UK has lower rates of basic data training skills (39%, according to a May 2022 study by Tableau and Forrester Consulting) than its neighbours France (48%) and Germany (58%), as well as the rest of the world (61%). Given the growing significance of data in various industries, there is a pressing need to enhance the skills of current employees and encourage students to pursue careers in this field.”

Just for fun, complete the phrase, data is the new…. ?

‘Oil’ (well, cookies are) – John Clarvis, The Kite Factory:

Maybe not data, but cookies are still like oil. Bad for everyone, unsustainable and need to be replaced with something that benefits everyone ASAP.

‘Metadata is the new data’ – Andrew Hood, Lynchpin:

“Data is the new data? Or specifically, perhaps metadata is the new data: everyone has plenty of data, but if we can’t successfully categorise its meaning then the information to data ratio can be lacking. And we’ll be feeding models increasingly unhealthy diets and reaping what we sow in that regard.

‘Still the new oil’ (beware the risks of mining it) – Kevin O’Farrell, Analytic Partners:

“Data is (still) the new oil. With unparalleled capabilities to drive innovation, economic growth and improve decision-making. However, to ensure responsible and sustainable data practices, we must understand both the benefits and risks associated with mining it, such as concerns about privacy, security, and ethical use.”

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