Next-Gen Synthesis: Data and AI

I rarely get the opportunity to attend industry events these days. Most of the time, my client services colleagues at CRMT Digital have more pressing reasons to attend than me. Last week was one of those rare exceptions. I was able to secure a ticket to Anticon in London, and a slot opened up in my calendar, allowing me to attend. If you listened to technology vendors at the conference, then AI is the only trend anyone seems to care about. It's the one feature every marketing technology vendor in the exhibition hall was trying to sell. There was plenty of talk about AI in the breakout sessions too, but it was not the most prominent topic.

Beyond AI

Most marketing operations professionals working on the frontlines still have far more pressing concerns than integrating cutting-edge technology into the tech stack. The same old challenges around organisational alignment, funnel velocity and data quality remain top of everyone's agenda. AI is undoubtedly exciting, and a topic that everyone is monitoring for new developments. However, people are only interested if it solves one of their day-to-day challenges, and so far, it's not clear that Generative AI technology will do that.

Now, this is not a particularly important disconnect, but it's one technology marketers need to be aware of. There is certainly plenty that AI can do, particularly when it comes to data. However, for B2B marketers, the primary use cases for Generative AI remain content generation and media optimisation. It can definitely drive down costs and improve efficiency, but ultimately, few B2B organisations are generating the high volume of content needed to justify the expense of an in-house LLM. Instead, for operations teams, AI resources are going towards more intelligent usage of machine learning and predictive AI in order to improve campaign targeting and lead quality.

The Data Question

If there was one takeaway from Anticon, it is that data is now central to everything marketing does. There was plenty of discussion around the importance of personalisation in improving campaign performance, as well as lots of talk about how changing B2B buyer behaviour is affecting the roles of both marketing and sales throughout the funnel. Having a clear understanding of the customer is essential to meeting both these challenges, and that requires investing in the right technology and processes as well as executing the right go-to-market strategy.

Customers have more control over the buying cycle than ever. They expect to engage with companies on their terms and not on yours. Hence the expansion of the so-called 'dark funnel' and the reluctance of B2B buyers to engage with sales outreach. People expect brands to track buying signals and personalise the customer experience. There are plenty of anti-tracking technologies out there, so if people are allowing marketing to track their online behaviour, it's because they want the personalised experience.

Finding the Blend

Data is used for more than just optimising the buyer journey though. It's also needed to measure business outcomes, which in turn justifies further investment in marketing. That requires data, particularly analytics data, to be both accurate and comprehensive. Manual approaches to data management are no longer sufficient. As such, there is intense pressure from both customers and internal stakeholders for marketers to improve their data management game.

Data quality has become a hot topic partly because people's expectations around data have shifted. Automation is essential, and AI is increasingly being pitched as the next generation of enterprise automation. Among executives, AI is seen as the technology that can deliver improved data insights. To reflect this, there is a much broader demand for propensity models and predictive segmentation than in the past. Previously, such techniques were restricted to large enterprises, but now they're trickling down to SMEs as well.

AI has an important role to play in meeting the much-discussed personalisation challenge, both as a technology and as a process. Marketing databases are used for so much more than in the past. Better data usage has the potential to transform buyer experiences in line with increasingly stringent customer demands. Marketers can meet those increased expectations by optimising their technology, data and processes to put the customer first, but only if marketing operations can find the right blend of capabilities.