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AI – The New Normal in Digital Marketing

Which marketing professional wouldn't want to have an AI-assistant that handles all the complex challenges and replaces more than just a pocket calculator?

August 13 2021Björn Radde

AI offers great potential in marketing

AI’s (Artificial Intelligence) capability to collect and analyses vast quantities of data in record time is also a big advantage in marketing. Many of us have already encountered AI in product searches, online shopping processes and out-of-home advertising. It is already providing guidance at many touchpoints along the customer journey with personalized content, product recommendations and dialogue with virtual assistants such as Hallo Magenta, Amazon Alexa or the Google Assistant. The latter uses RankBrain, a machine learning-based search engine algorithm, to increase search result precision. 

Success factor AI

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One reason for companies not planning to use AI is, in addition to the cost factor, that very few of them consider the current AI concepts to be mature enough for productive use according to Digital Dialog Insights 2019, a survey of 100 experts. Nonetheless, three-quarters of respondents believe that AI will be highly relevant in their marketing activities. This relevance stems from the fact that companies can only offer products that customers really want if they have an in-depth understanding of them. The faster they achieve that understanding and the more detailed it is – with the help of AI if necessary – the bigger their competitive advantage. 

The digital world expands the potential applications for AI. For one thing, the number of people with internet access is increasing all the time. According to Global Digital Report 2020 more than 4.5 billion people or almost two-thirds of the global population now use the internet. In Germany there are 78 million internet users, which is 93 percent of the population. Another key development is that consumers – including Germans – are buying more things online. Machine-to-machine connectivity, i.e. the Internet of Things (IoT), is also evolving, and the costs for computing and storage capacity have declined to an all-time low. AI needs data, and there are plenty of data to be found in online marketing, although just collecting and storing customer data isn’t the entire story. To use that data productively you need effective AI-supported analyses, and you have to stick to the principle of quality over quantity.

Personalization is becoming the norm

Intelligent, voice-activated virtual assistants in smartphones and speakers (e.g. Hallo Magenta) are a big trend right now. They provide shopping tips for the next holiday and reminders about upcoming birthdays. But they can also perform request-triggered support task such as “Hello Magenta, put product X on the shopping list” or “… call person Y”. In the future virtual assistants will be capable of informing users that their fridge needs restocking and then order the necessary supplies. Vast amounts of money are being invested in the development of voice systems such as chatbots. AI technology is learning to understand natural language texts, and solutions to improve the customer experience with support hotlines (e.g. Semasuite, T Systems) have already been introduced. 

The more time-independent and personalized the customer journey is, the more likely the customer is to purchase a product or be satisfied with a service. AI also accesses data on customer behavior, and factors such as place, time, device and weather. It uses this information for processes such as dynamic creative optimization – where ads change in real-time according to the shopper’s preferences and browsing history. These user-specific ads are compiled by algorithms to contain the most relevant set of visual and text components. 

The fate of AI is in our hands

AI solutions analyze data, language and images to learn how human vision recognizes products, for example (AI Vision, T Systems). This makes it possible to perform automated quality inspections or route customer enquiries to the right support partner. In the future we may well have AI in cameras analyzing gender, clothing and accessories to adapt out-of-home advertising. A person walking down the street carrying bags of supermarket shopping might see a barbecue ad, while another is shown the perfect handbag for their outfit. 

Customers in shops and restaurants, especially in China and the USA, are increasingly being served with the help of AI technology. Chinese KFC branches are equipped with AI technology that recommends personalized menus to customers based on estimated age and mood. And US supermarket giant Walmart has long been using AI for theft prevention purposes. With these applications it is important to respect data privacy and ensure compliance with data legislation. There is also an intense debate on a number of ethical challenges surrounding AI, and what it should and shouldn’t be allowed to do. In marketing, customer trust is an essential commodity. The fate of AI technology is in our hands. It will only deliver long-term advantages to the customer if we use it responsibly. 

Good Ads over Bad Ads

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On the internet AI can protect users from irrelevant and inappropriate ads. For example, if we come across a website with recipes and a food ad is displayed to us, we perceive it positively. On the other hand, if we’re reading an article about a road accident and a car advert is displayed in the side bar, we perceive it negatively. Cognitive targeting can be used to prevent the display of inappropriate ads. AI analyses the website in real time to establish brand fit, i.e. the display of ads that are suitable for the target audience and content, as well as brand safety to ensure that ads are not placed in the context of or adjacent to unsuitable content.

Users do not have to be tracked and their identity doesn’t have to be known for cognitive advertising. It simply makes sure that the ads shown are relevant, are not perceived as annoying and are GDPR-compliant. Cognitive and contextual targeting are currently under consideration as alternatives to traditional cookies. These are very promising technologies because they gear the advertising to the website being visited, rather than past visits or purchases. 

Predicting customer behavior

 We’d all love to be able to see the future. With the support of an AI technology called predictive analytics it actually is possible for marketing teams to predict the future, at least to some extent. What needs do which customers have and when? Increasingly, customers expect 24/7 access to products. Predicting shopping behavior is becoming more and more important for both consumers and retailers. And AI supports that. Amazon has actually gone one step further and is planning to dispatch products to customers before they’ve even decided to buy them. 
The cars of the future are likely to be mobile shopping centers. It’s quite possible that self-driving customer vehicles will take themselves off to the retailer to collect products instead of them being delivered by parcel carrier – or drone. Inactive customers are always a challenge to online retailers because reactivating them is a complex and time-consuming process. It would be infinitely better if the retailer could predict when the customer will become inactive and mobilize them at that time. 

Skills and trust are a must

Consumers are becoming more demanding in their expectations. They prefer AI-supported convenience, precision and 24/7 availability of products, information and services. Without AI, marketing will fall short of future customer expectations. Also, as more companies embrace AI, the market players that don’t will be left trailing far behind. Modern enterprises will introduce AI and machine learning to achieve the transformation into technology-driven players. Many sectors are experiencing an digital transformation boost. Now it’s up to them to take advantage of the associated opportunities. 
AI experts play an important role when it comes to the human factor. The larger the volume of data and the more diverse the applications, the more specialists are needed. Marketing and sales teams also need appropriate training in translator skills so that everyone in the organization can translate problems into AI applications and utilize the results.

About the author
IM-Radde-Björn

Björn Radde

Head of Digital Marketing, T-Systems

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