By nature, the digital marketing landscape evolves significantly each year, with advances in technology, changes in consumer behaviour and the macroeconomic environment changing how marketers approach the gathering of marketing insights, web analytics and the development of marketing strategies.
Staying ahead of the curve in these areas gives marketers a significant competitive edge over those who are not, allowing for the use of technology, techniques and practices that help them market and cater to the needs of web users and consumers in the present.
As we look ahead into 2025, let’s highlights some key marketing insight and analytics trends, and how these will shape marketing strategy development this year, and in the years to come.
More Advanced Web Analytics and AI Integration
In 2025, expect to see an emphasis on more advanced approaches to web analytics that cater to evolving business needs, aided by the integration of AI and machine learning into day-to-day marketing operations and data analysis.
Web analytics platforms, like Google Analytics 4, are drawing on AI and machine learning capabilities to bring AI-driven insights and data analysis support in-platform, which assists with reporting and predictive data analysis, helping marketers uncover trends that they may have otherwise missed and predict the intentions of users.
GA4’s Analytics Intelligence brings in-platform insight search, automated insight generation and predictive insight capabilities, integrated seamlessly into GA4’s reporting interface. Whilst valuable, these capabilities are currently restricted to top-level analysis, unable to cross-reference data between reports, utilise wider contextual data or suggest why marketers could be seeing the trends uncovered.
It’s likely that these capabilities will improve in 2025, alongside the development of the overarching AI and ML models used to power them, with the potential to offer more behavioural insight. This would allow marketing teams to directly leverage the insights gained to fuel the decision making that shapes a marketing strategy, so consider keeping a close eye on how these capabilities expand.
GA4’s Analytics Intelligence features, providing in-platform insights and anomaly detection.
Standalone AI tools, like OpenAI’s ChatGPT, were a hot topic across all fields in 2024, with digital marketing being no exception. As more marketers use these tools to improve the efficiency of everyday tasks, but also analyse and query the data gained from marketing activity, these tools can also help steer the decision-making behind a marketing strategy. Aside from significantly reducing the time it takes to analyse large datasets and begin the process of understanding the why behind the trends marketers see, these tools can apply contextual and behavioural input to the data shown, providing marketers with further decision making and marketing strategy support.
An Enhanced Approach to Personalisation
Personalising the interactions that users have with a brand is arguably essential for digital marketing success, particularly as consumers now have a strong preference for brands that make efforts to personalise their experiences. With greater insight into the behaviours behind user and consumer trends, driven by AI, marketers should look to incorporate a greater degree of personalisation into their marketing strategy in 2025, with tailored experiences that cater to the current and potential future intentions of their users.
More accurately predicting the actions of users, thanks to in-platform predictive insight capabilities and AI, can help create predictive audiences for personalised advertising that steer users towards making desirable actions, based on previous engagement. Tailoring content, offers and ads to users, perhaps before those users are even aware of their own intent to perform an action, can set a marketing strategy apart from the rest, and have lucrative results if executed well. Accurate and privacy-centric data collection, alongside behavioural insights that supplement the data collected, are key to making this approach to personalisation effective.
Predictive audience capabilities in GA4
Going one step further, leveraging real-time user data and AI to delve into the preferences and intentions of users can fuel hyper-personalisation. Demographic, behavioural, contextual and predictive insights are combined to create highly personalised experiences for users, which can include individually tailored messaging and calls-to-action inside of ads, content and web experiences. Whilst personalisation at this depth requires the know-how, volume of data and technical infrastructure to make it effective, taking aspects of hyper-personalisation and incorporating into a marketing strategy on a smaller scale can still be valuable.
Regardless of the approach to personalisation, the goal should be to be personal without being invasive, especially in a climate where consumers are increasingly cautious of how their data is used. Keeping this in mind not only builds trust, but encourages ongoing engagement and customer loyalty, primary factors behind the need for personalisation in the first place.
Increasing Importance of Data Protection and User Privacy
Underpinning all analytics and insights trends is the increasing weight being placed on data protection and user privacy. Regulators are implementing stricter guidelines for the collection, storage and use of online user and customer data, third-party cookies are facing an inevitable phase-out, and consumers appear to be proactively making more decisions that favour their online privacy.
In 2025, marketing strategies should have the privacy of users and the protection of their data at the centre, incorporating data collection and marketing practices that don’t only adhere to the bare minimum, but actively reassure users and customers that their data is being handled correctly. This includes asking users for their consent to data collection, making it clear how their data is going to be used, and adopting future-proofed data collection practices that take evolving regulatory and consumer expectations into account.
This not only establishes trust but upholds the same ongoing engagement and customer loyalty as the effective use of personalisation. If users and customers believe they can trust a brand to handle their data correctly, a trust-gap between brand and consumer that has grown wider in recent years, they’re more likely to continue engaging with that brand.
Google now requires the collection of consent signals from users to ensure data passing through Google’s platforms was collected with the required permissions.
Data-Driven Decision Making
By placing an emphasis on data-driven decision making within a marketing strategy, having data to support the decisions made rather than relying on intuition alone, a strategy will be more targeted, efficient and impactful.
Whilst there is nothing inherently wrong with understanding the preferences, behaviours and needs of an audience through experience, context or direct exposure, especially when working face-to-face with an audience in say a retail setting, having analytical data that supports what is believed to be true about an audience can ensure that any critical strategic decisions made have a positive return. This is especially important when optimising marketing budgets, adjusting advertising bidding strategies, and measuring the return on those budgets, as examples.
Whilst increasing regulatory scrutiny and altering consumer behaviour in 2025 will make it more challenging to collect granular or enough user data, making it tempting to act without the data to fully inform a decision, making decisions in a calculated manner should still be a priority. As above, AI can help here, with in-platform capabilities helping to uncover insights that may have been missed within a dataset, and standalone models making data analysis and insight generation more efficient.
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