Machine learning is used to optimize the use of CRM solutions. Because even if you think you already have the best software in place that meets top data quality, Machine Learning can be a game changer for you. We’ll explain how it works in this post.

Essentially, connecting Machine Learning and your CRM is about predicting outcomes and close times, gaining insights about sales opportunities, automating certain service tasks, and possibly suggesting next steps in the sales process. The list could go on, as these are just a few areas where Machine Learning can be used to generate additional sales opportunities and prevent service failures. Using Machine Learning, you can solve a wide variety of business problems, increase efficiency, drive sales through predictive analytics, and streamline time-consuming documentation. In addition, such solutions can be used in making forecasts for your sales or marketing campaigns. 

Machine Learning holds many advantages

Here are just a few examples of the areas in which you can benefit from Machine Learning:

  • Speed up response to requests
  • Identify new business options
  • Solve simple to moderate problems automatically
  • Engage customers more
  • Handle repeat orders autonomously
  • Set up sales forecasts and predictions
  • Derive future buying decisions from previous purchases
  • Avoid losses of potential deals

Among the most popular features in any CRM that uses Machine Learning is predictive analytics. This is because in the traditional sense, CRMs only focus on past or current data and offer insights into existing consumer data patterns. However, Machine Learning is continuously evolving and provides real-time feedback. It takes past exchanges with the customer and provides recommendations on how to improve sales and retention to achieve the best results.

Machine Learning improves itself and your business step by step

Machine Learning already has impressive capabilities and will only get better over time. That’s because it continuously learns new sales patterns and gains more advanced insights, as long as the dataset keeps growing and enriching. Example: If the basic attitude or specific sentiments need to be extracted from customer feedback, Machine Learning can understand and filter exactly this data. To further add value, all unstructured data can also be searched and tagged in free text fields. That in itself is remarkable. However, the amazement becomes even greater when you realize that Machine Learning can sift through hundreds of thousands or millions of records to deliver these results in the shortest amount of time – faster than you can drink a cup of coffee.

The first steps have been taken, more will follow

Machine learning has undoubtedly made many great strides in recent years. However, it will take several more years before it is used in everyday life and in every industry. No question about it, Machine Learning and Artificial Intelligence are slowly but surely changing customer service, for example. Moreover, the technology underlying Machine Learning is constantly improving. It is designed to help companies take their customer relationships to a new level and increase as well as maintain their market share. One example of this is the use of chatbots or CRM agents in customer service. But that’s another topic for another blog post.

One of our Machine Learning experts would be happy to explain how to best dovetail this technology with your CRM. Contact us today!

Tags:
#CRM #ITStrategy #UseCases

About the author

Mathias Herrmann

CEO at ALLEHERZEN

Mathias Herrmann is an internet entrepreneur going back to the Internet’s early days with a deep interest in digital and future technologies. For over 20 years, he has been helping companies make the most of their data by forging innovative solutions – without forgetting the people behind the data.

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