Machine learning is a versatile technology that is gradually being used successfully in more and more areas. Machine learning is arguably most highly developed in digital marketing, with personalized advertising at its center. The success of this technology in marketing is due not least to the fact that internet giants such as Alphabet with its Google search engine, as well as Facebook and Amazon, have driven it forward massively. For these corporations, machine-learning-based personalization of content and advertising is the foundation of their overwhelming success. A positive side effect: other companies of any size can already benefit from these developments today.
In digital marketing in particular, the conditions for the effective application of machine learning are usually excellent. Many companies already have correspondingly large databases containing valuable information about their customers. Since machine learning achieves better results the more data is available, using this technology is especially worthwhile in exactly these situations.
A prospect becomes a customer when they have the opportunity to purchase the perfect product for their needs at the right moment. The path a customer takes online before making a purchase — the so-called consumer journey — is the decisive playing field for machine-learning-based marketing. This consumer journey can be orchestrated in a tailor-made way based on the corresponding data.
There is a whole range of methods for ultimately achieving the most important goal — decisively increasing conversion rates.
Machine learning can generate an astonishingly accurate profile of new or returning users by analyzing existing customer data in combination with external data sources. By comparison with existing data, the machine learning application predicts the preferences and behavior of each user with increasing accuracy. The result is, for example, personalized advertising that ultimately enables companies to present the right offer to the customer at exactly the right moment. Most Amazon customers have probably already experienced for themselves how successful and useful this approach is — by buying a book or another product that was offered to them in the "Customers who bought ... also bought ..." section.
There is a whole range of elements of a perfect customer experience that can be optimized through applications based on machine learning:
Addressing exactly the right target group naturally increases the efficiency of marketing enormously. Predictive targeting with the help of machine learning puts all other strategies in the shade by far. Based on all available data known about the user, machine learning predicts the moment at which the probability of a purchase is highest. The unbeatable advantage of this form of targeting is that the application automatically "learns" when the perfect time has come to place the trigger. This strategy has proven to be up to three times more efficient than manual "triggering" methods.
Machine learning makes it much easier to predict which leads have the highest conversion rates in which situation. This is made possible by the wealth of data available about the potential new customer: from the data they leave behind when using your website, to information about the acquisition channel, to the user data gained through their account. This large abundance of important data allows accurate results through machine learning. Its use has increased conversion rates by up to 300 percent in many cases.
How do you correctly assess the long-term value of a customer? Will they simply renew a subscription, or does an attempt have to be made to retain them with a discount offer? How much revenue can I generally expect from my customer base in the future? Until now, all these questions could only be adequately assessed with the greatest effort, if at all. With machine learning, we now have a technology at our disposal that is capable of doing exactly that based on user behavior: delivering highly accurate forecasts. This can be enormously helpful, for example in pricing or long-term customer retention.
"Churn prediction" is about recognizing when a customer may be about to cancel their membership. Retaining existing customers is an important concern for every company — but the approach is usually not tailored to the customer. Machine learning can provide answers to questions such as whether customers can be retained longer with offers or discounts, or when it is worthwhile to contact the customer directly.
The use of machine learning thus makes it easier for our clients to develop effective mechanisms in digital marketing to take timely action with customers who could potentially be lost.
The example known from Amazon has already been mentioned above: machine learning can be used to learn more about the user's preferences and thus encourage them to buy additional products. Read more about machine-learning-based recommendations in a separate article.
Machine learning has long since become indispensable in digital marketing for many companies. The breathtaking successes of the big internet corporations are based to a large extent on advancing the machine learning applications listed above. Billions of US dollars have been invested for this purpose. The good news is that other companies can now benefit from this as well, since Google, Facebook and co. have done valuable groundwork here. Numerous technologies developed by these companies have now become available and affordable for other market participants. If you are considering incorporating machine learning into your marketing strategy, we are happy to provide you with our expertise.
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