Interviews, insight & analysis on digital media & marketing

Learnings from the history of AI-powered personalisation

By Dave O’Flanagan, Chief Product Officer, Sitecore

For businesses looking to build a solid customer base, it’s become all about personalisation. Loyalty is driven by an experience economy where digital is the expectation and knowing what customers want at any given time is the standard. It’s become the make or break for brand reputation and those looking to stay competitive, particularly against a backdrop of ongoing cost-of-living challenges that has seen 65% of consumers stop making ‘treat purchases’.  More than ever, businesses need to be proving their value and investing in their digital experiences to make the lives of consumers easier.

Clearly, there is still more that can be done to transform how brands interact with customers – and generative AI may be the answer here. As much is being recognised by marketers – research we undertook revealed that over the next 12 months, 72% of marketers will prioritise spending on AI, with 69% believing it will allow them to create more personalised content and get closer to customers.

As marketers get ready to harness the power of AI, what can they learn from past iterations to unleash its full potential?

Setting the scene for ChatGPT

ChatGPT has dominated headlines across the technology industry since the beginning of the year, and we’re already seeing several organisations integrating the technology into their operations and offerings. From Google’s Bard launched in recent months, to the news that Instagram is reportedly testing an AI chatbot with 30 personalities users can pick from – brands across the board are joining the AI-race.

But chatbots aren’t new and neither is AI. Earlier iterations have seen AI deployed to predict consumer preferences by gathering and interpreting behavioural data, then suggesting content that’s in line with these. Elsewhere, AI has been used to supercharge search engines to provide more relevant search results for users by understanding intent and context behind the search terms. More recently, AI has been used to for virtual chatbots to autogenerate responses to common queries and interpret keywords to form likely answers. The priority here remains consistent across the board for marketers adopting these technologies: improving the efficiency of day-to-day processes, getting closer to the customer, understanding what they want and delivering the best outcome.

Then, enter generative AI. It’s provided brands with the ability to deploy more advanced chatbots trained off larger datasets than ever before. These are helping to generate new insights for marketers and better outcomes for customers, delivering deeply relevant content that enhances the personalised experiences customers are looking for.

The technology has moved fast, so marketers need to keep up. Yet, almost half (45%) don’t feel their marketing technology is currently equipped to use generative AI – a fatal downfall for brands looking to supercharge their customer loyalty. For marketers to keep pace with today’s fast-evolving tech landscape, they need flexible solutions that will allow them to respond with speed and efficiency.

Composability as a pathway to innovation

Previous martech solutions have existed in silos, preventing marketers from being agile to changing needs. Many companies have technologies in their stack that they don’t use, either because they are not fit for purpose, or they have outlived their usefulness but are tied to an integration that is too crucial to their business operations.

At the same time, deploying new solutions can be time-consuming and costly, which can be off putting for brands looking to adopt tech, leaving them stuck with a CX offering that falls short of today’s expectations. But the promise of generative AI is clear – 91% of marketers believe it will make them more competitive and three-quarters believe it will help them get closer to customers – and that requires the right platform to deploy it quickly and efficiently.

For brands looking to build a tech stack that works specifically for their business, and delivers what customers want, having flexibility is key. Composable solutions allow new innovations to be integrated into martech stacks seamlessly, meaning they can adapt and react to changing customer demands and the latest trends in tech almost in real time, without the concern of being trapped into a vendor’s ecosystem. Generative AI can be deployed at scale alongside existing open APIs and marketers can begin to create intuitive, engaging and personalised experiences that are truly relevant to their customers.

Crafting experiences of the future

Transformative customer experiences requires transformative tech. Generative AI is set to be a gamechanger here, helping to supercharge efficiency, personalisation and content at scale. Marketers are recognising this. But they need to leave legacy solutions in the past to move forwards and truly make full use of the technology. If we are to learn anything from the evolution of chatbots and AI, it’s that modern functionalities require a modern back-end tech stack to stay ahead.

Every brand has a different set of needs. No one tool can feasibly meet all of these. Composable solutions can help brands adapt to the accelerated pace of innovation, building tailored solutions suited specifically to their business. This makes implementing generative AI – and future innovations – seamless, allowing them to deliver experiences that meet customers’ needs and value for the business.