It is now considered a fact that artificial intelligence (AI) will play an increasingly important role in service and marketing. But it is not yet quite clear just how quickly and to what extent this will happen. There are already countless more or less sophisticated approaches. The following five examples show what AI is already making possible in marketing and what may be yet to come.
In dialogue with AI
An increasing number of companies are relying on chatbots with artificial intelligence to handle their customer service faster and better than possible on the phone. Bots are now supporting simple requests involved in buying products or booking trips and tables. The next development will include making AI Conversational Chatbots more interactive and personal. They will be able to individually address customers and quickly answer requests. These bots will “learn” from each customer conversation and thus deliver increasingly better results. In combination with predictive analytics, self-learning software will be able to anticipate consumer behaviour and desires to provide customers with matching information or the desired answer right on the landing page.
AI says “Welcome!”
Wal-Mart is using facial recognition technology to combat theft and Kentucky Fried Chicken is welcoming its customers with menu recommendations generated by AI as part of a pilot project in China. In the future, customers in shops, restaurants or hotels may be identified via automatic facial recognition and served according to their preferences. The robot receptionist pepper took up his job in a London company in mid-2017 and welcomes visitors among other things.
A focus on customers
Artificial intelligence is already helping people manage marketing campaigns more precisely. Big Data Analytics pertaining to consumer interests can be used to identify people as they move through the internet and communicate with them in social networks, shopping portals and other websites. Studies have shown that people addressed in this way are most receptive to this personalised advertising. This type advertising, which is referred to as hypertargeting, minimizes wastage and achieve the maximum advertising effect among the right target group. However, hypertargeting not only helps companies design their ads to be more targeted and therefore more cost-effective. Consumers benefit from the fact that they receive more relevant information or advertising messages. Self-learning technology will accelerate this development and provide companies with an increasing number of ways to identify and understand customer preferences. Hyper-personalization is the new magic word here! By the way, a good example of targeting is a campaign realised together with Messe Frankfurt, which has achieved outstanding results even without big data analytics.
Content creation: AI, please take over!
Artificial intelligence is already helping to produce simple texts. This is already working well for text that follows a strict set of rules. These include different types of reports, sports results, hotel descriptions or company earnings reports.
Associated Press has been using AI to create earnings reports since 2015 and short articles on baseball games since 2016. Artificial intelligence also makes it possible to compress and classify large amounts of text. In the future, this innovative technology will take on more routine tasks and activities that reproduce the same content including translations. AI-based programs also independently evaluate different sources and which type of wording works best within a target group. They adapt text accordingly based on this information. In the next step, such advanced solutions are to learn creative writing and create content for more complex matters independently using data and current events. This future has already begun. In 2016 text created by AI programs was submitted to the Hoshi Shinichi Literary award (Japan). Of 1,450 texts, 11 were apparently written by “machines” and one of them even made it to the second round of the competition.
AI forecasts customer behaviour
Behavioural predictions are probably one of the most important areas of application for artificial intelligence in marketing. As soon as it is possible to reliably predict how a customer will behave at any given time, the appropriate action can be triggered at exactly the right time. This has been working well in the form of recommendations for several years now, as the examples of Amazon and Netflix show. In as early as 2013, for example, Amazon achieved around 35% of its sales based on automatic product recommendations.
Netflix uses AI to recommend films and television series. Approximately 75% of all content watched in 2012 was based on this type of bot-generated recommendations. Artifical intelligence or at least fairly “smart” algorithms will make customer communication increasingly specific in the future. It is possible to determine individual contact intervals, for example, using behaviour-based predictions and display custom content on a website or shop display in real-time.
Virtually limitless possibilities
Self-learning programs will be indispensable in the marketing of the future. Initial applications and pilot projects are showing what may be possible. “Knowing what customers want before they even know”. This dream is as old as the idea of marketing itself and, step by step, artificial intelligence is bringing us closer to it. It is therefore all the more important for marketers to quickly learn about and understand the possibilities of this self-learning technology. Those who miss this opportunity will be passed by early adopters. Nonetheless, a critical approach is required. After all, the application of artificial intelligence also has disadvantages, which are increasingly being discussed? The discourse has begun and the central questions include the following: Do consumers really want all this? Is marketing crossing ethical or legal boundaries by using this technology? And what impact will this have on citizens, businesses and society as a whole? It is therefore particularly important that we take an in-depth look at this subject.