The Importance of Knowledge Management in Marketing

Knowledge Management

Regardless of industry and product, businesses must build their own data system gathered from employees and customers to keep growing. This process is also known as knowledge management or KM. However, in the new era of the digital revolution with the rise of artificial intelligence and other automation services, is traditional knowledge management forgotten or will it find a way to prove its value? Do businesses need only one or both two types of knowledge management to flourish? We will find out the answers right away in this article.

What is knowledge management?

Knowledge management (KM) is the process of creating, using and managing the knowledge and information of an organization. It deals with company data related to customers, products, and working. There are two main types of knowledge in terms of knowledge management. Explicit knowledge is knowledge or skills that can be easily understood, and therefore easily transferred to others. Tacit knowledge, by contrast, is the knowledge that is difficult to transfer to others.

Through KM, organizational knowledge is maintained and developed over time so that anyone in the business can utilize it. Knowledge management, therefore, implies a strong tie to organizational goal and strategy.

How can knowledge management create value?

Knowledge management can positively influence specific teams within a company such as IT service team and customer support team. Many businesses have implemented automated services like chatbots into knowledge management programmes. Knowledge management, in this case, is basically used for the benefit of the IT service team. Data from knowledge management can reversely support those AI projects and make them more valuable.

For customer support team, knowledge management helps them to tackle customer problems. They collect information on the issues that customers report. By analyzing this set of data, they can identify both individual problems and problems related to a large group. Thus, they will find new content required to help customers solve their problems themselves.

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Problems with knowledge management

Knowledge management

Information not getting shared well or not adequately managed over time are some issues related to knowledge management. For example, one team within a business comes up with an excellent solution. If it is not shared with others simultaneously, it will be difficult to spread the idea and expand the business. Similarly, if new employees have no idea about that knowledge, it will be hard to keep a high level of service stable over time when the staff leaves the team.

How to share knowledge in an easier way is also a big challenge for teams. They can execute it via new articles, videos, and in-depth content pieces. However, it is important to gather information on the problems that affect customers. It makes the process of finding a solution easier and more efficient. Marketers and customer service teams need to collaborate to get the content that customers want from them. Moreover, they need to know which stage customers are in when approaching a product.

The use of automation and chatbots in combination with knowledge managemet to build content

By making use of knowledge management, companies have content delivered to more customers. This process even brings about more efficiency if it occurs earlier no matter how you apply new automation service and chat bots. It will be better if you use these artificial intelligence tools to build content. For companies aiming at having more human interaction, automation is recommended for content. For those that encounter important problems or issues affecting customers on a large scale, they can make use of chat bots. Agents can make content available for those chat bots based on the problems that they have to face.

The adoption of artificial intelligence (AI) into knowledge management

The use of AI in knowledge management replaces the human consultants that had been analyzing the data and monitoring the KM process. Today, cognitive computing, adaptive technology, and intelligent filtering tools have huge implications for codifying knowledge. However, rather than depending solely on AI to solve the problems, you can combine the best of both AI and knowledge management to improve marketing campaigns and customer experience. Building valuable content relies on the combination of AI with understanding how customers react to their problems. You can use the knowledge that you already have to keep moving forward. This will become more efficient if you apply AI during the process to support each other. Your business will ultimately grow quickly if you can flexibly combine both traditional factors and high-tech factors. However, try not to depend on only one kind of factors thoroughly.

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