Good Data has become one of the most important factors to making business decisions. Making judgments based on what we think to be true is no longer enough in today’s market; data has become important for B2B businesses to remain competitive and accurate or relevant enough.

Data silos separate data and give limited space for collaboration between different departments or teams of B2B businesses, which compromises the accuracy and efficiency of marketing campaigns held by B2B businesses. Therefore, a B2B business must understand data silos, the core difficulties of data silos, and, most importantly, how to unlock them to continue making their B2B businesses progress. 

What are Data Silos?

Data silos are differentiated data sets exclusively available to specific teams or divisions inside a company. Different departments of the B2B business collect data using varied tools, resulting in important data pieces being saved in devices that only a few individuals can access. 

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Avoiding Data Silos and Too Much Data Fragmentation 

There are multiple methods and tools that B2B marketers can use to avoid data silos and data fragmentation.

• Unification of Data – One of the best ways to avoid data silos and fragmentation is to unify all the customer data collected. Client Data Platforms such as YouGov are a type of software that can help B2B businesses to gather all customer information they have received into a single, centralized, and easily accessible database.

Client Data Platforms are tools that help B2B businesses consolidate and organize customer data acquired from many touchpoints, arrange it into customized and central customer profiles, and then make that data accessible to other software and systems. As a result, Client Data Platforms can prevent data silos by creating complete customer profiles that contain data from several sources.

The Data Axle team collaborated with AEG to develop a unique marketing solution that connected different marketing technology and data across the enterprise. The collaboration helped AEG to avoid data silos and data fragmentation. 

• Collaboration Environment – Collaborative working environment is another way through which Data Silos can be avoided; the collaborative working environment allows teams to exchange data without neglecting data ownership is to create a company-wide roadmap for data management and usage. Teams must continue to interact, innovate, and learn new things about their existing conditions.

Having a designated Data Protection Officer for your B2B business marketing will guarantee that the subsequent data executions are consistent with data protection rules by providing the team’s knowledge and skills to analyze and interpret the data.

• Data Governance – Data governance strategies that increase synergy and optimize data effectively can help B2B organizations avoid data silos. The rules, ownership, and structure for data management within the B2B business should be outlined in a data governance framework. The Wachovia Bank offered a fantastic example of this method. Wachovia Bank was suffering from data silos because of development through mergers of the Bank. With the help of more than 250 people from several departments, the company spent a year establishing and executing an overall data governance program. As a result, it was successfully able to avoid data silos. 

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How Data Silo and Data Fragmentation Impacts B2B Business 

Data Silo and Data Fragmentation can have a significant impact on a B2B Business 

• Collaboration Limitations – One of the most significant issues with data silos is that they make it difficult for teams to interact with each other in B2B business. Due to the numerous bits of information not correlating well enough for one coherent aim or goal, the members of the B2B business become separated from each other. This division of data silos results in disconnected initiatives and an inability for the entire B2B business to collaborate. Managers desire data-driven choices, but they cannot understand how this affects other departments of the B2B business since their team is only focused on what is happening with themselves. 

• Machine Learning Models are Prevented – The most severe issue with data silos and data fragmentation is restricting B2B businesses from gaining actionable insights into their consumers, which is essential for marketing. This is due to a lack of a comprehensive framework of their data and a failure to capitalize on the benefits of complete data analysis. Data silo and fragmented data will prevent a machine learning algorithm used for marketing campaigns from gaining complete knowledge of a customer, resulting in lower-quality insights and the inability to employ predictive analytics to effectively anticipate future consumer behavior. For B2B business marketing campaigns, complete information of their prospective customers is needed to attract them.

To gain a competitive advantage for B2B businesses, having a clear, accessible image of your consumers is critical to pushing your marketing plan. This is why, for every B2B business marketing campaign which aims for expansion, removing data silos and data fragmentation should be a top priority. B2B Marketing campaigns can gain a lot from the removal of data silos and fragmentation.