AI is no longer a futuristic pipedream. Across all sectors we see different branches of artificial intelligence enhancing product and service offering, from medical treatment to agricultural production. In the context of marketing, brands are increasingly allocating budgets to AI solutions that drive personalised advertising experiences. But when it comes to ROI, are some marketers missing a trick?
Our recent research into AI investments in the UK and the US found that marketers are spending on average 15% of associated departmental budgets on AI. We spoke to 400 marketers across the UK and US, discussing data handling practices and personalisation. The picture shows significant AI uptake among brands to ensure that the right ads are shown to the target consumer at the right time, and on the right device.
For those who were measuring their AI outcomes, 31% said the most valued ROI metric was impact on sales. This was followed by 29% who placed greatest emphasis on ROI in innovation, whilst 21% prioritised ROI in advertising.
Clearly, the jury is out with regards to what data brands should be capturing regarding the value that AI is adding. But the research also revealed that in spite of marketers’ enthusiasm to embrace data-driven solutions, as many as 33% said they were unable to measure the impact of these investments. The issue here is that for AI to be properly effective, it has to be attributable, maintain control and undergo rigorous measurement. Without assessing its performance, how can marketers’ make informed decisions about how to invest over time?
Is AI technology measurable?
The beauty of AI is that it is built on data points. This technology is inherently measurable when fully integrated across digital campaign execution. AI solutions should have a control group and an exposed group that directly measures the uplift as a result of the AI’s targeting activities. And over the course of the campaign, data collection means that AI can optimise towards not only content personalisation, but delivery of ads too.
Our research also found that 7% of marketers most valued employee productivity as a metric for evaluating AI investment. Brands seem to be focusing much more on how this new technology can drive sales revenue, rather than how it can enhance employees’ own productive capacity. It is certainly worth approaching AI investments first and foremost as a way to increase revenue and ideally market share, rather than just worker productivity.
Brands should only make an investment – in any innovation – if they can demonstrate a tangible benefit. Whilst the majority of brands are able to prove this for their AI investment, some marketers are still missing out. When this new technology is paired with a robust attribution model, the true value of AI is within easy reach.