According to Forrester, some 72% of firms say managing data silos across multiple systems, technologies, and regions is moderately to extremely challenging. But, what are data silos and how can marketers and CMOs avoid them? In this post, we explain what data silos are, how they have a negative effect on marketing, and how you can integrate data silos to ensure you are getting the most value out of your data.
What are Data Silos?
Data silos are isolated data sets that live within a single source or, most commonly, within a particular team, and which are not accessible by other data systems or teams.This ultimately causes issues with holistic visibility, the ability to optimize campaigns, and confidence in data quality. Data silos can happen in agencies that work in teams based on channel or campaign focus. They can also happen between in-house brand marketers who are also split by channel or discipline. Examples of where data silos can exist would be Earned vs Owned teams, or between Social and Multi-channel marketing.
How do data silos happen?
The two most common reasons that data silos occur are a lack of sufficient technology, and/or rapid team growth.When there are insufficient tools to aggregate, harmonize, and share data across teams, data silos can be extremely common. With a centralized data stack, each team may have its own technology in place (or none at all) and a certain tool used by one team may not be accessible to another team.
Conversely, as businesses grow, they often add new tools and data sources at a rapid rate without a game plan for how to integrate them with other teams, tools, or data sources they are using. Often, a department or team will simply end up collecting data for their own use but, mostly, this will only support the individual team’s goals.
Why are data silos a problem in marketing?
In today’s data-driven world of marketing, data silos create a number of key problems for marketers.1. Data silos limit visibility over campaigns
The main issue that data silos create for marketers is limited visibility into performance. Because data is disparate and disconnected, it’s impossible to truly see how one channel or data source influences the bigger picture. Thus, it is difficult to decide how campaigns should be adjusted to achieve campaign objectives.To give an example, imagine you are a CMO at a brand and you want to see what happens to web sessions when there’s a focused effort in generating more impressions across your paid media platforms. Let’s say you use Google Ads, Bing Ads, Facebook, LinkedIn, and Twitter, and you have Google Analytics as your web analytics tool.
If Google Ads and Bing Ads live with one team, the social media sources live with the social team, and your web analytics team owns GA, and none of the data lives in a single place; how can you compare metrics, ensure objectives are aligned and adjust spend accordingly?
2. Data silos prevent marketing teams from demonstrating their impact on the business
Take this one step further and imagine you also want to understand how your marketing efforts are impacting revenue. However, if your sales data is isolated from your marketing data, it becomes extremely difficult to understand how marketing performance is influencing the company's bottom line. In fact, data silos are one of the reasons why 47% of CMOs struggle to demonstrate the business impact of their marketing efforts.3. Data silos can result in poor customer experience
A good data set-up can bring marketers closer to their customers. But a bad one can result in poor customer experience. In fact, according to a study by Forrester, 38% of decision-makers see data silos as one of the biggest challenges of delivering a good customer experience. The more data silos you have, the longer it takes to get the data you need for reporting. In the agency space, this can impact your client’s experience with you when they’re constantly waiting on data from another team. This delay in getting their questions answered can create frustration.In the world of brand marketers, not having access to a single view over all your data sources means it's much harder to spot risks and opportunities for channels and creatives that are tanking, or performing well, and react in a timely manner.
