Personalization in marketing is a data-driven approach that provides customers with relevant information according to their interests, needs, and usage behavior. Based on the historical behavior, machine learning is used to determine which preferences and preferences each customer has.
The result is personalized content or product recommendations that interest the customer and precisely meet the customer’s needs. A perfect example is a personalised coffee cup, which may play a pivotal role in pulling more clients to your side. 90% of leading marketers state that personalization is a significant factor in the profitability of their companies.
Personalization – the Most Important Things at a Glance
- Personalization
means adapting to the interests and needs of the customer individually as a company and to act specifically - In this case, utilizing machine learning to determine which preferences and preferences of each customer has
- Concerning personalization, the following three aspects are essential: the right product or content, the right time, the right communication channel
- Personalization within marketing holds great potential for both companies and customers
- Long-term customer loyalty, increased activity, or strengthening against the competition are advantages for the use of personalization in marketing
Why Is Personalization Important in Marketing?
Personalization increases sales and binds customers to your company in the long term. Studies show that people who feel understood through personalization are more likely to and prefer to use the company’s offering. This, in turn, leads to a better customer experience.
Large companies show how important the topic is and invest a lot of money in the development of personalized communication. In particular, the automation of marketing processes is possible through personalization in marketing. Algorithms are primarily responsible for selecting the right products for each marketing campaign. In companies, this often leads to resources being freed up.
What Are the Technical Basics for Personalization in Marketing?
A good
personalization strategy requires the collection of various data sources on purchasing behavior, website interactions, product information, or shop visits. This collected data serves as the basis for a recommendation service, a method from machine learning that determines personalized product recommendations. Which algorithm is used depends heavily on the business model or the number of products available.
In addition to the collection and analysis of data, the correct automation and integration into the communication channels (e-mail, web shop, app, etc.) is extremely important. The technical fundamentals and algorithms of recommendation services are complex and often put off marketers. For this reason, it makes sense to start with a simple use case to quickly and easily gain initial successes. Then you can go a step further and scale personalized communication for your company.…