2024 Tech Predictions

With an ever-growing marketing technology landscape filling with generative AI tools, it can be daunting to assess where best to invest time to benefit your marketing efforts. Alongside this, over the coming months, regulatory changes and platform-specific developments will spotlight a sizeable functionality gap for many advertisers, emphasising the need to tighten up process and implement changes to data collection and processing in order just to stay abreast of bare minimum requirements.

Despite these potential challenges, this is in many regards a year of significant opportunity for brands: the ability of well-constructed tech stacks to be customised to your desired business outcomes, to provide actionable insights and activate consented customer data has never been more powerful.

AI told me to put it at the top of the list

The rapid rise of AI adoption will feature at the top of nearly all 2024 prediction pieces, let alone those with a specific data and technology focus.

Squarely concentrating on AI’s place in the marketing ecosystem, the proliferation of solutions is staggering. Just over 13,000 products across all marketing technology now comprise the MartechMap – an impressive audit compiled and maintained since 2011 by Chiefmartec and Martech Tribe. That landscape grew 18.5% in the last 6 months and just shy of three quarters of all new solutions were based on generative AI.

Whilst there is already a great deal of machine learning and AI built into many of the media platforms and analytics we manage and support on behalf of our clients, from a Technology Division perspective the greatest advances will be in the interactive and analytical aspects of AI when applied to large, combined data sets.

Underpinning our view on AI for the businesses we work with is always the necessity of not working in silos and a focus on bringing together as much data from disparate sources as possible to generate a comprehensive and coherent understanding of marketing efforts and customer engagement. Our engineering work over the past few years – constantly refining our processes for the collection, warehousing, and transformation of data – means that many of our clients will already be ideally placed to embrace the benefits of predictive analytics and explore new ways of engaging and accessing their combined data for business intelligence.

UA goes away

It’s been a rough period for people who enjoy Caramacs and outdated web analytics platforms. Cancellations abound. 1st July 2024 will mark the end of a staggered sunset process for Universal Analytics, with access to all properties scheduled to be removed.

We were preoccupied with migrations to Google Analytics 4 in the first half of 2023; this year, it may be a case of businesses focusing on what they want to do with their historic Universal Analytics data. For some it’ll be a simple case of storing what’s available should they need it for future reference. For others, their requirement may be more involved: if they started collecting data in GA4 more recently and need UA data to supplement some sort of view of year-on-year results, for example.

Has the dust of GA4’s ‘launch’ settled? Yes, to some extent, but this is a platform in flux: it’s still constantly on the move and plenty of updates will continue to be released that will impact how data is viewed and integrated into other platforms through 2024 and beyond. Once the comparisons between Universal Analytics and GA4 fully subside, it’s clear the latter’s privacy-first approach and flexibility for tracking and reporting web and app activity is something that should be embraced by marketers.

Still getting to grips with GA4? Read some of the thoughts of one of our Web Analysts gathered from a year of GA4 audits and training.

Get content with user consent

User privacy considerations are firmly in the spotlight now as UK businesses attempt to get to grips with current best practice and regulation and some high-profile goings on will be prominent at the start of the year.

The requirement for gatekeepers to comply with the DMA comes into effect in March 2024 in Europe and there is a likelihood of similar practices being adopted in the UK before long. In support of stronger consumer privacy protections, one of the changes Google will apply is making Consent Mode implementation for Google analytics and ad platforms cookies via your Consent Management Platform (i.e. the cookie banner on your website) a prerequisite for advertising activity to run as normal.

Consent Mode is a solution that allows Google tags – for Google Ads, Floodlights (Programmatic / DV360 activity) and Analytics to react to user cookie preferences. A website needs a consent management platform (such as OneTrust or CookieBot) in place that is already dealing with preventing tags for measurement from firing should a user opt-out of tracking.

As well as ensuring Google tags are privacy compliant in their use of cookies, Consent Mode introduces some additional tags that allows Google to continue to collect anonymous interaction data whilst respecting user choice not to be tracked. The key is not being able to identify an individual user and not storing any identifiable information. As an example, having Consent Mode in place allows brands to track conversions from ad campaigns based on aggregated and modelled data, rather than just blocking everything.

Google has also announced a renewed effort to block third-party cookies in Chrome (with over 60% market share for browsers) by the end of 2024. As such, collecting and transferring first-party data in a privacy-first and secure manner to help understand audiences for reporting, targeting and optimisation will grow in importance for effective marketing.

  • Read more about implications of Google’s third-party cookie deprecation here.

No party without first-party

Putting your consented first-party customer data to use for optimisation and targeting purposes for your marketing isn’t new, but the automated connection of CRM data to advertising and analytics platforms will have renewed focus for many brands in 2024.

Customer data connections and integrations are currently most often utilised in the attribution space – usually matching customer records against ad platforms for assigning credit back to campaigns where the conversions / transactions have happened offline or in-store. Examples of this include Meta’s Conversions API and Enhanced Conversions for leads. Google’s Data Manager was recently announced to be rolling out to Google Ads in early 2024, which will simplify setting up and maintaining the CRM connections needed for enhanced conversions and targeting strategies such as customer match. The release of user-friendly platforms and refined interfaces will be a common theme in activating first-party customer data in the coming year.

Indeed, as Retail Media’s growth continues as a post-cookie advertising solution into 2024, the quality of the systems that emerge around it to facilitate safe data collaboration between retailer and advertiser – alongside targeting and measurement considerations – will determine which providers are truly successful in this space.


It’s on the analytics side that we often see CRM data missing its potential for business intelligence. Particularly for businesses where transactions don’t happen on a website or app, having visibility of those most crucial customer touchpoints is vital for reporting and understanding the impact of marketing efforts. It is still rare for brands to connect their sales data up with ad delivery and investment data for this holistic view.

With increased use of data warehousing and centralised reporting there is potential to build some highly sophisticated Marketing Mix Models from combined ad platform, analytics, and other third-party data sources.

MMM as an aggregated approach of delivering business insights is having a resurgence as an excellent way to understand data from multiple streams when accurate user-level data is increasingly harder to obtain. Alongside this, the prospect of what can be done with these combined data sets using machine learning and AI, including factoring in external data on markets and the wider economy, will undoubtedly unlock a lot more CRM data transfer from businesses looking to stay ahead of the curve.