AI in marketing and sales: easier customer-centric communication with artificial intelligence

Whether it's the ChatGPT chatbot, OpenAI, Dall-E or Midjourney - no topic is as hotly debated these days as artificial intelligence (AI for short). But AI can make our work significantly easier. Especially in marketing and sales. In this article, we would like to introduce you to use cases that show how you can use AI to align marketing and sales in your company more closely with your customers.

What does artificial intelligence (AI) have to do with customer centricity?

You need data to make your marketing customer-centric. Data about your customers' purchasing behavior, their customer journey, their preferences and the touchpoints with your brand and your company. AI applications help you to use this data in a structured way (see also data-driven marketing). They provide you with the information you need. As a result, you can improve customer understanding and thus also the experience that your customers have with your brand. For example, you can recommend products that match their wishes (next best offer). Or address them via personalized content with suitable customer journeys. You can also automate marketing and sales processes or develop products and services based on data. Focusing on the customer enables companies to increase sales while reducing costs at the same time.

Artificial Intelligence (AI) along the Customer Journey - Procedure

Use cases where you can generate (AI-supported) knowledge about your customers are located along the entire customer journey. However, before you start with AI applications, there is some homework you should have done first. Because: AI is not a miracle, but stands and falls with the collected data. The first step is therefore: "What is the question for which I want to generate knowledge in order to achieve my set goal?" Based on this question, you derive what data and in what quality you need the data so that you can answer the question. You can develop the corresponding roadmap for generating the data with a data strategy.

How exactly can artificial intelligence (AI) help you and your business communicate in a better customer-centric way?

In the following, we would like to use specific application examples to show you what artificial intelligence can do in marketing and sales. Please note that this is only a small selection. The fields of application are much larger and will continue to grow in the future.

Targeting customers who seem likely to make a purchase (prediction and lookalike audiences)

Let's imagine that we operate an app that is free to use for the first month and is then available via a paid subscription. Our goal is to increase the conversion rate of subscription contracts. We achieve this, for example, by addressing the right customers at the right time via the right channel. The question here could be: Which customer shows enough potential and is suitable for the upselling campaign (sale of the higher-value product)? How and where should we approach this customer? Artificial intelligence (AI) can provide the answers with a model for predicting the probability of closing a sale. To do this, we need data from users who are already using the paid subscription, e.g. biometric data, usage data, etc. We use this data to create a model that can be used to assess the behavior of new users. Marketing can then target people who are similar to existing users (lookalike audiences) and are therefore more likely to take out a subscription.

Predict the success of campaigns (attribution prediction)

What if we wanted to directly address the target group that is most likely to subscribe to the app when promoting the app? So-called attribution models calculate the share of a touchpoint in a conversion. Data on campaigns and channels that have already been carried out provides information on which campaigns and channels have led to subscriptions and where subscribers previously obtained information. You can use the models created on this basis to make predictions about successful campaigns. This allows you to allocate your marketing budget to targeted channels (and their combination!) and campaigns and increase the conversion rate and return on investment (ROI).

Reduce customer churn in a targeted manner (churn prevention)

By optimizing the campaigns and addressing the target group in a targeted manner, we have now been able to take out more subscriptions and use the budget in a targeted manner. However, this is not the end of the customer journey. What can be done to increase customer loyalty and minimize the risk of churn? Recognizing cancellations at an early stage is particularly important for contract and subscription-based business models. Acquiring new customers is usually very expensive and these business models are therefore often only profitable if the customer lifetime value is high. Predicting customer churn is therefore another interesting use case for AI in marketing. Here again, we try to derive a model and predict churn probabilities for active users by analyzing past behavior and the corresponding data. For example, we can address customers with a high probability of canceling with an attractive offer and retain them again.

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Our conclusion

AI in marketing and sales is a useful tool and can help companies uncover new potential and implement actions in a better and more targeted manner.

However, it is important not to forget the prerequisites and doings that are necessary for a good data basis and should be fulfilled (beforehand).

We are happy to support you in the generation of your data and the application of artificial intelligence.

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Sonja Rösler, Projects

I look forward to your questions and exciting conversations.