Does personal, individual customer care no longer count?
In this article, Sabine , Marketing Manager , describes from her perspective why AI is needed in CRM.
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Until now, I have always pushed aside the idea of artificial intelligence (AI for short) in CRM. It sounded more like a dream of the future than a proven process. Bots had something a little disreputable about them.
But then I wanted to create a presentation on the topic of future-oriented software. I first had to google what all falls under artificial intelligence. Here is my list:
Modern CRM software already makes use of some of its functions. But the scope for AI in CRM is still wide. There are already many research results and the first tests with comprehensive AI in CRM are underway. Self-learning bots support website visitors. But there are still functions with great computing power to come that will make AI in CRM a ground-breaking tool in customer acquisition and retention.
This list also immediately made a movie run in my mind's eye of what we could improve in our daily work with AI in CRM.
Companies need predictions to stay competitive
Today's customers are more complex than ever before, as they have many more and very different channels at their disposal for communicating and acting. However, more opportunities for comparison and more touchpoints between companies and customers also present companies with new challenges when it comes to managing the customer experience.
If you fail to meet customer expectations at one or more touchpoints along the customer journey , the customer will reject you. Today, it is very easy for customers to switch to the competition. They can find many comparison portals and product reviews on the Internet. This means that practically every contact has to generate enthusiasm in the customer in order for them to stay - keyword: customer experience. And, of course, customer centricity.
Customers are increasingly using digital touchpoints (websites, social media, online stores, apps, etc.). Companies need to respond to this. Which touchpoints does the customer expect? What does the underlying process look like? Every click on a website, every post on social media, every order in the store generates a large amount of new data. Without AI in CRM, do we even have a chance of meeting the requirements?
IDC study predicts data volume of 175 zetabytes by 2025
A new study by IDC shows that the amount of data worldwide will grow to 175 zetabytes (that's 175 with 21 zeros) by 2025. The volume of data in companies in particular is increasing rapidly: By 2025, the bytes stored there will account for around 80 percent of the total volume.
Without analyses and forecasts, companies will not get any further. They help to identify sales potential and create the perfect customer experience, which ultimately leads to customer loyalty.
How to manage all touchpoints and large volumes of data in the future?
With the support of AI in CRM and in your CRM system. According to the McKinsey Global Institute, 40% of all traditional sales tasks could theoretically be taken over by artificial intelligence. Some "prophets" even claim that artificial intelligence in the CRM system - through data, pattern matching and individual testing - could recognize needs and make recommendations for action even before companies and customers do.
Modern CRM software is thus developing into a holistic platform for interacting with customers. Necessary data from the ERP and other external services are integrated. The data recorded in CRM provides companies with a basis that can be analyzed for specific patterns. For example: Is your company losing customers? If the CRM system recognizes a pattern, you can take the next step - in this case, take appropriate measures to prevent customers from leaving.
What is or will be possible thanks to AI in CRM
A few simple examples of AI in CRM
- Text and image recognition: Helps to understand customer messages, analyze emails and websites as well as social media channels
- Data mining and text mining: Identifies new cross-connections and trends as well as meaning structures by systematically applying statistical methods and algorithm-based analysis processes to large data sets
- Analyses and forecasts: Recognize patterns. Gain insights into customer touchpoints from the growing mountains of data by
a. Analyzing deals from the past
b. Analyzing the customer journey
How and via which channel should the customer be approached? At which points is the churn rate highest? Identify problem areas and find suitable countermeasures, e.g. with personalized offers instead of annoying customers with unwanted offers - Expert systems: IBM works with Watson, an AI platform that develops chat bots and virtual agents that answer customers' questions quickly and efficiently and respond to their needs. This is already being used in medicine, for example. It is only a matter of time before this AI can also be used successfully in customer management
- Chat bots: They provide relief by conducting automatic dialogs via chats. In practice, there is a high level of acceptance of the chat function. It is available anytime and anywhere
- Machine translation of texts: It provides support in international business (e.g. by connecting the external service DeepL) - whether in marketing, sales or service
