Having team members who are skilled in marketing data management and analytics for agencies are table stakes in the modern agency. It’s also true that every agency has equal access to the performance metrics they require. If every agency has the same access to the same data, why then are the client experiences in regards to agency analytics so drastically different?
Does the immaculate and perfect use of marketing data and agency analytics seem like an unrealizable fairy tale? Does better data management improve results? How can we write a new ending and have our Cinderella moment with data management and analytics?
The Story About Data and Agency Analytics
If you’ve worked with data or databases for any amount of time, you’ve probably heard the saying, “garbage in, garbage out.” This is a common phrase that explains one of the most common pitfalls in agency analytics marketing metrics: bad data.
The ways data can show up erroneously are multiplied by all of the thousands of platforms data lives on. Not to mention the myriad toolstacks marketers have to set up, monitor, collect and report on data can cause duplication and degradation issues. Over time, these platforms and processes compound the complexity and potential for errors.
Any agency looking to be truly data-driven in their decision making process will have to decide at some point, to outsource the marketing data management process entirely, hire a full time team of developers and data engineers to create an in-house solution, or pursue a hybridized version of the two. Getting into marketing data management and building a custom data warehousing solution are not without their own difficulties.
Common Challenges in Marketing Data Management
Among the many challenges agencies face in uncovering insights from their data and analytics, there are a few that stand out more than others.
One of the most obvious challenges with agency analytics is that most marketers lack a basic understanding of how to use or read data. Everyone can interpret a pie chart, but when it comes to ascertaining the strategic meaning of marketing data, or the implications of data on an agency’s business objectives, it can take more than a keen eye. For a nice primer, check out our Intro to Marketing Data Visualization.
With so much data available, it can be hard to counter the perception of “more is better” rather than curating the principle of “relevant is best.” The irony of having too much data and not enough information is not lost on marketers that slog through agency analytics to build client reports on a weekly or monthly basis.
Maintained by a combination of rules, standards, and processes, data integrity refers to the accuracy, consistency, and completeness of collected information, covering a customer's journey, end-to-end. Without being able to verify data integrity or manage the entire corpus of performance data associated with campaigns, agencies are left making well-meaning assumptions on potentially meaningless metrics.
The overabundance of available data also paradoxically creates an inability in marketers to do anything with it all. According to a recent marketing data and analytics survey from Gartner, 81% of marketers expected a majority of their decisions would be data-driven in the following year, while 66% of organizations ranked themselves at below or intermediate on Garnter’s Data-Driven Marketing Maturity Model.
How Better Data Management Improves Agency Analytics
Teams dedicated to dealing with agency analytics know that integrating and formatting data is what’s eating up most of their time. Getting a handle on data management has a range of positive effects on your agency, well past just the improved analytics.
- Better marketing data management means improved data integrity, which provides opportunities for clearer insights and a stronger foundation for plans and strategies.
- Managed and manicured data means dashboards, analytics, and reports are precise and as accurate as possible.
- Data integrity can help build a better budget, identifying effectiveness trends more early and often, helping pinpoint where marketing dollars will have impact.
Most advanced agency analytics teams understand the importance of having an ownable marketing data warehouse to store and analyze cross-channel data. A data warehouse can provide a much clearer picture of full-funnel performance metrics, giving marketers the ability to consolidate data from multiple platforms.
Structured data is easier to query and analyze than unstructured data, which is why data warehouses are engaged via tables and employ SQL as the query language. Data warehousing is a relatively inexpensive and accessible alternative to platform-centric data storage options, which have specific data retention policies and challenges.
The majority of computing and processing within a marketing data warehouse is cloud-based, as opposed to on-premise solutions. With a data warehouse, agencies can provision more hardware to crunch data with a few clicks, rather than hire a team of developers to scale up their abilities.
Can Improved Agency Analytics Mean Higher Clients Fees?
Making the choice to optimize and enhance your agency’s analytics and marketing data management processes and protocols is a big decision. The wrong move means wasted time and increased complexity. But selecting the right solution to improve agency analytics could reduce time wrangling data, increase speed of insight, and streamline workflows.
Scattered data will slow your team down, which is why any amount of time spent on organization and formalization applied to your agency's marketing data management process is time well spent.
The benefit of having a fully managed marketing data pipeline, from platforms to warehouses, from clean rooms to point-in-time dashboards, is your agency improves observability and gets closer to a single source of truth.
Improved data management also enables your agency to gather performance insights at a holistic level. This helps your team get a handle on strategic, performance-related datasets your clients might be willing to pay more for, such as customer acquisition costs and return on ad spend.
If improving analytics is an aim, if reducing the chaos and upgrading the integrity of data is a hope, then improving your agency's approach to marketing data management is a step in the right direction.