Let’s say that your technology stack consists of SalesForce to store customer data, Marketo to nurture leads, Hootsuite to manage your social media marketing and Google Analytics to track website visitors. Siloed data is defined as all your platforms having different ways of storing and organizing data.
You will waste a lot of time bouncing back and forth between reports, and will likely miss critical pieces of the puzzle.
Siloed data can also lead to inconsistencies and discrepancies in performance reports. They make it difficult to get a complete picture of customer insights, leading to blind spots and incorrect assumptions.
What’s more, siloed data can lead to missed opportunities. Businesses that don’t have a unified view of their customer data are unable to identify patterns and trends. This makes it difficult to spot new business opportunities or take advantage of emerging markets.
Related: Why Un-Silo-ing Your Data Will Boost Your Company’s Efficiency and Productivity
Why is siloed data problematic?
Siloed data has become the scourge of today’s business owners. It’s estimated that the average company has more than 2,000 silos of information, each housing data that is inaccessible to other parts of the business. The result is that businesses lack a single view of their customers, their campaigns and even their own performance.
Treasure Data’s State of the Customer Journey report shows that 47% of marketers say that silos are their biggest problem when it comes to gaining insights from data.
The modern-day business landscape is a complex one. Intuitive tools and products have given rise to dynamic cross-functional teams that work across numerous projects. The sheer number of business platforms and tools can be dizzying. It’s no wonder that so many businesses have trouble getting a handle on their data, let alone making use of it to inform their business decisions.
The impact of siloed data can be far-reaching and devastating. Businesses that don’t have a clear picture of their customers are at a distinct disadvantage. They are unable to personalize the customer experience or target their marketing efforts effectively. As a result, they end up wasting time and money on marketing campaigns that don’t produce the desired results.
Related: Preventing Communication Gaps Makes Productivity Better, Too. Here’s How.
Limit the view of data
Big data has the potential to transform businesses and provide previously unattainable insights. However, this can only be achieved if data is unified and accessible.
According to IBM’s Big Data and Analytics Hub, “we’ve learned that many of the most common challenges associated with big data aren’t analytics problems. In many cases, these problems are fundamental, even traditional IT challenges that have been exacerbated by the volume, velocity and variety of big data.”
When data is spread out across different departments and systems, it becomes difficult to get a cohesive view of customer data. This can lead to inconsistencies in the data, as teams are working with different subsets of the customer journey. For example, the sales team may use data from the last 30 days, while the marketing team may use data from the last 90 days. As a result, teams are likely to have different views of the customer, which can lead to misunderstandings and conflict.
Threaten data integrity
The ownership of data often becomes an issue when data is spread across different departments. Multiple teams may claim ownership of the same data, leading to confusion and conflict.
This can also lead to data being siloed among individual team members. For example, a salesperson may keep customer data in their own spreadsheet, rather than sharing it with the rest of the team.
Since there is no central repository for data, it can be difficult to track changes and ensure data integrity. This can lead to critical errors and inaccuracies in reports.
Related: To Break Down Silos, Build in Cross-Communication
Make it difficult to comply with regulations
The General Data Protection Regulation (GDPR) is a set of regulations that govern how businesses collect, process and store personal data. The GDPR applies to any business that processes the data of EU citizens, regardless of where the business is located. The GDPR requires businesses to take steps to protect the personal data of their customers.
In addition, the GDPR requires businesses to provide customers with the ability to access their personal data. Data silos can make it difficult to retrieve the data that customers are requesting.
Siloed data can lead to duplicate efforts, as different teams may be working on the same project without knowing it.
For example, let’s say you have a customer list that is stored in three different systems. The sales team is working on importing the list into their CRM, while the marketing team is working on segmenting the list for a campaign.
Both teams are wasting time and resources on the same project. In addition, duplicate efforts can lead to errors and inaccuracies in the data.
Related: How to Break Down Silos in Your Company by Building Lanes
Limit cross-team collaboration
The omnichannel customer data is complex and it requires cross-team collaboration to understand. When data is siloed, it becomes difficult for teams to share information and solve problems. In addition, siloed data can lead to a lack of trust between teams. If team members feel like they are not getting the full picture, they may be less likely to trust the data they see.
Data silos can have serious implications for businesses. If your business is struggling with data silos, it’s important to take steps to address the problem.
Best practices for managing data
1. Invest in data quality
Organizations should invest in data quality management software to help ensure that their data is accurate and complete. Data quality management software can help to identify and correct errors in data.
2. Establish data governance
A centralized data governance team can help to ensure that data is managed correctly and is accessible. This team should be responsible for setting standards, maintaining data quality and ensuring compliance.
3. Use data visualization tools
Data visualization tools can help teams to understand their data better. This understanding can help teams to make more informed decisions.
4. Leverage artificial intelligence
AI can help automate the data collection and analysis process, making it easier to get a cohesive view of the customer journey. It can also help to identify and connect data silos.
5. Use single marketing technology stacks
Organizations should consider using a single marketing technology stack. This will help to ensure that data is properly integrated and accessible. Finally, you need to ensure that data is being used effectively by all teams.
When data is no longer siloed, businesses can unlock the true power of their data. They can make better decisions, improve customer experiences and drive growth.