Artificial intelligence (AI) has become indispensable in science. Ultimately it is able to analyze large amounts of data much faster than the human brain. By now, the systems have even progressed so far that they deduce appropriate conclusions and can act accordingly. Thus, the discipline has made breakthroughs in discovering correlations in research in various fields, marketing being one of them.
AI combines complex tools of marketing and enables a personalized and automated customer approach.
Independently it manages to decide on the time, channel, content and type of incentive, based on individual customer data. At the same time, the process can make possible changes and adjust the type and amount of incentives used to control campaign success. This eliminates the need for elaborate, manual segmentation of buyers into different groups with corresponding content and enables smaller companies to prevail against industry giants.
Many companies in the retail and eCommerce sectors are already using these AI technologies in marketing to some extent. However, a recent Forrester study, commissioned by Emarsys - Building Trust and Confidence: AI Marketing Readiness in Retail and e-Commerce finds that there's a gap between the potential of today's AI marketing solutions and their actual implementation in the enterprises.
Although the importance of AI solutions in retail marketing and e-commerce is well-known, it often fails to be implemented, the study reveals: 75% of respondents see the rapid progress in digitization as a problem, according to the study, and finding the right tool is another issue. Around half of the surveyed companies (54%) even claim to have no effective data management strategy in place: A sufficient database is usually given, but often collected in so-called data silos and not analyzed accordingly. Hence, instead of personalized "one-to-one" offers, customers receive the usual “one-to-many” offers, based on segmentation like age and gender. But since the offers are not tailored to the buyer, this type of customer communication leads in the long term to consumer frustration. The prejudice that AI technologies are just for analysts and scientists unfortunately still prevails, as some marketers can’t believe that there are AI tools they can easily and effectively use to fundamentally optimize marketing tasks.
Automated customer approach
With AI, however, the existing database can become a usable marketing tool: In fact, 92% of respondents see AI’s potential here, especially since 40% of marketers have problems with the personalization of their marketing campaigns and expect to create customer satisfaction and added value for users through AI marketing. The already collected data is evaluated by using AI to create intelligent marketing automation routes for a personalized, cross-channel response. Therefore, the majority (89%) of respondents believes that AI marketing enables a cross-channel, personalized customer approach in real-time, because AI can determine the timing, communication channel and content of the approach. AI marketing technologies act automatically and autonomously, and eliminate manual activities, such as grouping of buyers or deciding on the corresponding incentives. Consequently, marketers no longer work primarily operationally, but can concentrate on strategic tasks, like increasing customer satisfaction and buying incentives. Automated customer-facing processes simply enable them to invest their resources in campaign planning and strategy. Therefore, marketers expect AI to earn them a higher ROI (79%), to help them set up personalized real-time campaigns (61%) and create automated workflows (74%).
Ideally, for instance, every content published via all media and channels is targeted and brand-compliant and is consistently created according to the people and departments involved. But since they all have their own ideas, writing styles, different perspectives or priorities, there is the danger that conflicting information can be read on different channels, product names are used inconsistently or spelling mistakes creep into texts. This diminishes trust and weakens the brand.
In the flood of content, it quickly becomes clear that just human editing isn’t fruitful. Undoubtedly, only intelligent software can meet this challenge, which is why this task falls into the field of AI, the “discipline that deals with the attempt to reproduce a human-like intelligence”, to keep up with the competition in the future. But wouldn’t it be wonderful if machines could measure, how brand-conform and convincing a text is? Results provided in a fraction of a second, in a cost-effective way?
By Daniela La Marca