Artificial intelligence (AI) is also taking the world of marketing by storm, whether it’s in data analysis, online marketing, classic advertising or digital asset management. Successful marketing uses emotions, tells stories and sparks desire. So how can a machine help with this? We show you a few examples of AI being used successfully.
‘You may also like…’: recommendations have become so widespread and accepted in online shops that we don’t even realize that they’re based on AI technology. Often, recommendations are presented in the form of a banner with the aim of offering added value for the shop user. Ideally, they may bundle several suitable products together to create good-value packages. The shop operator awakens a new need in the user, increasing turnover.
‘Hello. How can I help you?’ Companies can use chatbots to make their customer service cheaper and quicker. They can also help to increase product demand, acquire new customers and retain existing customers. Chatbots simulate conversation with human users. They provide answers to questions by analyzing keywords and processing sentences from real conversations. Some chatbots come across a little dopy and falter at seemingly simple questions. They vary in intelligence, and constantly learn from the input they receive.
Personalization is an important success factor in digital marketing when it comes to long-term growth in conversation rates. Personal messages create trust and make you stand out from the excess of information available to us today. But many marketers believe they understand their customers from the outset and can easily put themselves in their shoes. They’re sadly often wrong. It’s better to trust the data, and AI-supported personalization leaves nothing to chance.
Last year, a campaign by supermarket chain Real received a great deal of attention and scepticism: cameras in 40 branches recorded customers’ eye contact and analyzed this based on age and gender among other factors. The aim of this facial recognition? Recognizing what the customers were interested in and reacting with suitable calls to action, advertising and offers.
We’ll admit that creative writing is still a bit of a reach right now. Machines struggle with humor, irony, metaphors and original word play. But they are good at obeying strict rules: the Californian job portal TalentSonar uses artificial intelligence to automatically generate politically correct job advertisements.
In all these examples, content plays a major role. Be it the automation of campaigns, personalized customer contact, chatbots or recommendations in an eCommerce store. Clearly organizing, saving and making this data available is a key challenge. Only when it is available in a clear structure can the true potential of AI be harnessed. DAM forms the core of any content strategy by providing countless integration options with other systems. Using various interfaces, the content is distributed across docked third systems such as websites, online stores and social media platforms.
Digital asset management needs clear structures, cohesive keywords and data categorization - a dreary and time-consuming task for employees to complete manually. AI can take care of the hard work: especially in large libraries, it can create and file meta data for existing and new content. It recognizes objects automatically and tags them accordingly. Specializing in similarities, AI can find similar files and images, finding duplicates and decluttering data libraries. It can even recognize faces and scenes.
Much of this technology is still in its infancy. But the potential for the marketing teams of tomorrow is already clear to see; and many companies are already using AI. Especially when it comes to applications that use lots of content, DAM can contribute to a greater degree of automation and make everyday life easier for marketers with AI-supported features.