The excitement about artificial intelligence (AI) is contagious. Our imagination has been ignited to its potential in a wide range of fields. In marketing, however, many have concluded that the hype is just that: hype. There may be potential, they say, but it is far too hard to implement AI and see results, and many have just given up.

This is a shame, because AI has the potential to change marketers’ lives in a very real way. Some tools, of course, are best used by large companies, but there are a number than can be used by companies of all sizes, and which will make a big difference to how you contact new and potential customers, the action you take to drive a first purchase, converting single-purchase customers to repeat customers, and engage long-term customers more fully.

Making contact

Making contact with potential customers is very much about content in marketing terms. Content is what pulls in potential customers, and then keeps them looking. Many marketers would say that AI does not have much of a role in a content strategy, and this is certainly true if your content is focused opinion-type articles.

There are, however, technologies that can help with particular types of content. AI report writers can provide a reasonable summary of regular financial reports or routine data in a fairly human-sounding way. They can, therefore, supplement human content-writers by doing some of the more basic work. AI can also help to indicate other articles and content that readers might like. This uses very similar technology to the recommendations engine at Amazon or Netflix, pointing out other, similar articles.

These examples are ways in which marketers are using AI to make their lives easier. There are, however, also ways in which AI is changing how marketers need to work. These include both search tools and online advertising. These are probably the main ways in which people find information online, but the way that these tools are being used is changing. The arrival of AI-based intermediaries, such as personal assistants like Siri and Alexa, may alter how search is used. Marketers need to be aware of what is happening and ensure that their practice reflects this.

Ad placement is also becoming more scientific and may change in the wake of scandals about inappropriate websites. These are early days, but marketers need to keep an eye on what works and be prepared to change tactics relatively rapidly if necessary.

Drawing customers in and converting them to repeat customers

There are a number of ways in which AI will change the way that marketers work with customers pre-sales and to encourage repeat purchasing. Many of these are based around predictive modelling. There is more and more data available about customer behaviour, and models can predict future actions with increasing accuracy. This, for example, allows marketers to identify the most likely prospects, both for initial sales and future sales. Advertisements can also be targeted with increased accuracy.

More subtly, AI-type algorithms can be used to set prices more dynamically, so that only the most price-sensitive customers see discounts. This type of algorithm uses trait analysis to identify the customers most likely to respond to discounts and not to other incentives. This avoids the overuse of discounts, and therefore damage to profits. Personalisation more generally is also a growth area for AI use, responding to customers’ increasing demand for tailored services. AI allows customers to be given the most relevant content, or best offer for them, based on their previous behaviour and their stage in the buying process.

Chatbots are increasingly available at lower cost, and therefore to more companies. They can be used to handle simple queries online or via telephone. They are particularly helpful to respond rapidly to simple questions, and therefore keep response times low and customers happy.

Customer engagement and unusual partnerships

There are a number of ways in which AI-based analytics is useful in customer engagement. Predictive analytics allows companies to identify which long-term customers are most likely to leave. They can therefore target marketing more accurately at those customers – and also work out how best to engage with them again. More generally, AI-based techniques allow marketers to identify the best way to engage with each customer, personalising content and messages more effectively.

The key here is for marketers to work “together” with algorithms to drive better outcomes.

These very practical examples of how AI is already being used demonstrate that its use in marketing is more than just hype. The key here is for marketers to work “together” with algorithms to drive better outcomes. This new partnership will require marketers to be more imaginative in how their jobs are scoped and executed.