From Chaos To Clarity: Transforming Marketing Attribution With AI & Machine Learning
By Laurence Carton
Data is the lifeblood of modern business. Data-driven insights reveal what customers expect, how they behave and what they purchase. For marketers, it is the bedrock for analysing past campaign performance. Surfaced insights should, in theory, guide smarter, more cost-effective future activations. It’s no surprise, then, that almost three-quarters of UK businesses now prioritise data collection.
But while collecting data has never been easier, using it effectively is another story. A 2023 survey found that 80% of marketers gather more data than they know what to do with.
Outdated attribution models are a major contributing factor to this gap between information and insight. Take last-click attribution. All credit goes to the final channel that secures the conversion, masking the influence of other channels on the customer journey.
Picture the scene: someone sees a billboard promoting a sunny holiday flight destination on their morning commute. Later that day, they spot a carousel ad for the airline on Meta and make a purchase through that. Brands relying on last-click attribution will perceive Meta to be the most impactful channel, leaving the impact of the awareness-driving OOH placement to be overlooked.
For marketers to truly understand which channels drive incremental performance, they need to unlock the full potential of their data, including datasets that have historically been siloed or disconnected. And this is where AI-powered measurement can paint a clearer picture.
Evolving Beyond Fragmented Data
One reason marketers have historically defaulted to last-click attribution is simply because it’s easy. Platform dashboards like Meta and Google Ads, as well as their preferred CRM system, make lower-funnel activity quick to access and simple to interpret. However, convenience comes at a cost. The metrics associated with these bottom-of-the-funnel activations are often inflated.
At the same time, the explosion of available data has made it increasingly difficult for humans to track meaningful signals. Spend, impressions, audience behaviours, as well as variable factors such as real-world events, weather and the Consumer Price Index – all of these can shape marketing performance. Not only are these signals complex; but manually untangling an outcome’s cause and effect has become an uphill, if impossible task.
Consider a real-world example. A car-sharing brand experiences a spike in weekend rentals. While marketing activity may play a role, it’s unlikely to tell the full story. More free time on Saturday and Sunday will have driven demand. Increased availability of more desirable vehicles could have an impact, the same of which could be said for warmer weather.
In short, different factors will have contributed in different ways, with traditional attribution models providing limited visibility of how each nuance moved the needle.
AI-powered measurement provides some much-needed clarity. Real Impact, Tug’s causal-based modelling product, uses machine learning to identify relationships across all contributing data points, removing guesswork (and more importantly, bias) from the equation.
Accurately Proving ROI
A key reason for switching from traditional modelling to an AI-powered solution is its ability to address one of the most common challenges facing CMOs today: convincing the CFO of the marketing’s ongoing value. According to Deloitte, the pressure to demonstrate the impact of marketing activity on financial outcomes is the leading concern for leaders in this role (64%).
Real Impact solves this by linking previously disconnected datasets, as well as incorporating your own backend data. It doesn’t matter if a campaign’s KPI is to drive traffic to a landing page, generate conversions or boost engagement for a particular product. The platform can measure true ROI with confidence.
Just as importantly, Real Impact isolates individual channels, allowing you to experiment with new campaigns. This subsequently empowers marketers to optimise activity based on evidence, rather than relying on gut instinct. Of course, the accuracy of this depends on using robust data.
Looking beyond individual campaigns, AI-powered measurement platforms like Real Impact instil confidence in marketers when the time comes to present insights and recommendations to the CFO. Activities that may have previously been relegated down the list of priorities, such as awareness campaigns, can now be shown to have a measurable impact on business outcomes.
All of this allows for smarter decision-making and more precise budget allocation, enabling marketers to unlock additional investment and divert spend to the channels that will have the optimal impact on the brand’s performance.
Want to hear how Real Impact can drive incremental performance for your marketing? Reach out to us here – our team is happy to answer any questions you might have.
Related Articles:
