Implementierung von KI im Vertrieb - Hürden

Implementation of AI: Obstacles and Recommendations


Studies paint a picture of how things are going with the implementation of AI in companies. Obstacles are often a need for more human resources and a lack of support from management.

Artificial intelligence (AI) is becoming increasingly present in our (professional) everyday life. Who would have thought 20 years ago that there would one day be software to help those responsible for sales make statements about events likely to occur?

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b2b wholesale distribution facing insolvency

B2B Wholesale & Distribution: Challenges and Triumphs of Industrial Wholesale Companies Facing Insolvency in Germany

Insolvency? A debtor that cannot pay its debts and liabilities to creditors. No cash, no business.

In Germany, specialist wholesalers and industrial distributors who can no longer meet their payment obligations due to current or foreseeable overindebtedness must, by law, file for insolvency protection. Forget your revenue, your brand, your years in the market. If you will not be able to meet your obligations, insolvency is cast.

The Statistisches Bundesamt counted 34,000 fewer wholesalers in the past ten years. Additionally, we’re seeing an increase in insolvencies in Germany’s industrial wholesale and retail segment, with several high-profile companies filing for bankruptcy. It’s essential to understand the significance of this trend and take necessary actions to address the issue.

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AI in b2b sales

Where AI already Supports Sales Today

Learn seven practical use cases where artificial intelligence is already supporting sales today.

More and more companies are using AI to streamline processes in sales and hand over unpleasant tasks to algorithms. AI is therefore assistance for sales without making employees obsolete.

The use of artificial intelligence (AI) is radically changing the way sales works. This primarily refers to sales processes under the influence of AI tools that make the work of sales employees easier, optimize operations and take away tasks that are perhaps not so readily done.
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Predictive Analytics and Customer Behaviour

Predictive Analytics to Understand Customer Behavior in the B2B Sector

Predictive analytics is an innovative technology in the B2B sector that calculates data-based predictions about customer behavior.

For some B2B companies, predicting customer behavior is like guesswork. Managers sit together and try to make predictions about upcoming sales, future pricing or appropriate customer loyalty measures.

Often these forecasts are based on sales reports, sales representative’s own gut feeling and, Excel analyses created with a lot of frustration. Don't get us wrong, the gut feeling of an experienced sales team can very often be right, especially when it comes to customers they have had a lot of contact with. But what about all the other customers?

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Artificial Intelligence in a Salesman of Construction Machinery

Artificial Intelligence in a Construction Machinery Company

Artificial intelligence technology can be used in a wide variety of areas. In this article, you will learn how AI was used in a mechanical engineering company.

I've already written a few posts on this blog about Artificial Intelligence (AI) in sales. Simply a fascinating topic for an old sales hand like me who has worked with several different CRM systems as well as sold AI systems.

For someone in sales, the area of predictive analytics is particularly interesting - an AI is able to predict sales opportunities. That's why I report on a specific case study below.
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Wie Sie Predictive Analytics in Ihrem CRM für datenbasierte Entscheidungen nutzen können

How to use Predictive Analytics in your CRM for Truly Data-Driven Decisions?

Successfully implementing Predictive Analytics for data-driven decisions in your CRM requires more than just software.

Every successful sales team wants to become data-driven. Companies that successfully execute predictive analytics in their CRM are easy to identify.

They take care of their salespeople and successfully utilise their current data and processes. They employ the standard software and adapt them to their situation. Finally, they introduce Predictive Sales to CRM step by step and learn from their experience.

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