How Marketing Agencies Can Get Higher Data Quality with Less Work

July 9, 2019

The Challenge: Ensuring Data Quality

When clients expect to see data that proves the success of your marketing strategies, having accurate data is critical to your marketing agency.  

However, collecting and presenting clean, relevant data can get complicated, especially when you’re dealing with mountains of data for multiple clients, and each client has multiple data sources through Marketo, HubSpot, Facebook Ads, Google Analytics, etc. Compiling, creating, and analyzing all your needed reports can quickly become overwhelming.

Time Lost to Manual Reporting

Manual reporting is typically done by an analyst who has to compile information from various data sources into a spreadsheet. Then they have to distribute the spreadsheet via email to the appropriate team members within their agency and to their clients.

Many agency teams use manual reporting techniques to communicate data and findings, but there are a few concerns with this approach.

  1. It takes an inordinate amount of time to keep everything updated. You can easily just spend most of your time updating, checking, and tweaking metrics in order to ensure all the data is correct.
  2. You're only providing the basic numbers. To run comparisons and create visualizations of the data will require even more work.
  3. Workplace surveys of data analysts show that 80% of their work time is spent in the data prep stage. Much of that prep time includes simply collecting and aggregating all of the data in various spreadsheets.

If you can automate the process of collecting numbers from all of your structured and unstructured data sources, you can significantly reduce your time spent on data. It also decreases the likelihood that your data with be plagued with accuracy errors.

Manual Methods Risk Dirty Data

A manual BI or data management approach not only requires that your marketing agency spend more time preparing datasets and reports for each client, but it also increases the risk that mistakes will be made and that you will ultimately share inaccurate findings with your client.

What is Dirty Data?

Dirty data is incorrect data that pollutes your data integrity. Dirty data falls into three categories:

  1. Inaccurate: Not correct due to human or system errors.
  2. Incomplete: Missing fields or missing information.
  3. Inconsistent: Duplicates or reported differently in different locations.

The Dangers of Dirty Data

While it is true that there is an inherent risk dirty data in any type of data collection, those risks are exponentially higher when you are tracking and updating data manually. Poor data quality can hurt your agency and your clients. When team members don’t have access to accurate data misinformed decisions can lead to significant consequences for your clients and your entire agency.

One particularly dangerous aspect of poor data quality is the false sense of security it gives. Extensive or serious data errors blind your clients to problems or missed opportunities and reflect poorly on your agency service as well as make it all the more difficult for your clients to trust you.

Causes of Dirty Data

There are many ways that bad data can enter your system, but they all fall into two major categories: human error and systems challenges.

Human error is extremely common for companies where manual spreadsheet data entry is the norm.  Employees entering typos into the system by mistyping or due to distraction. Another issue could be that multiple employees are entering the same data causing duplicates in the system.

Systems can cause challenges when they don’t integrate properly. This is especially true during data migration from one platform to another. Platform updates can also cause issues when the update is being performed.

All of these possible system errors can be checked but it is a daunting task with the high volume of data involved. Having to look over all the data to ensure that it is still accurate takes time. And then there is data decay which can happen when data decays into inaccuracy. Things can change and your once-good-quality data becomes outdated, poor quality data.

The best way to ensure that your data is accurate and timely is by looking at the dimensions of data quality (which you can learn more about in our blog post).

Improve Data Quality and Reduce Dirty Data with BI

Business intelligence solutions (like Grow, wink wink) help ensure better data quality by automatically checking for accuracy and providing suggestions for cleaning up any questionable data. Instead of spending hours manually checking that your data is updated and accurate, you can let the BI system do the work for you.

BI solutions automate data entry by connecting to your data sources correctly, automatically reporting and updating your data in real-time. Every time your data updates it's automatically included in your dashboard.

You don’t need to worry about team members or clients working with outdated data sent in a report. All you need to do is log in and look at your dashboard to see all the updated data. You'll also receive notification of any data errors. Everyone has access to real-time data.

BI Visualizations Help You Grow

With a robust BI solution, not only do you better protect your marketing agency and your clients from data quality and inefficiency issues, you also have the ability to create and share beautiful data visualizations. By building dashboards that display the data your clients care most about, you can easily share information with the teams managing these accounts and keep both your agency and the client on the same page.

Take Grow’s metric dashboards, for example:

  • Your clients can log in to view-only dashboards at any given moment to see the progress of their campaigns or other projects they are working on with your marketing agency.
  • With a custom branded account, your logo and colors will be used throughout the app, so your clients’ experience will be seamless (and they’ll be seriously impressed).

Better Data Insights for Less Work

Data analysts are some of the most skilled experts in today’s digital marketplace. However, many data analysts end up spending their time and talent on manual data entry, prep and presentation. Time on those tasks is time taken away from what their most valuable work activity should be, analyzing your data looking for opportunities, trends and ways to optimize your marketing and sales funnels.

Utilizing a business intelligence solution to automate much of your data entry and prep process empowers your data analysts to spend more time studying the data your organization is collecting instead of merely cleaning and compiling it.

Request a demo of Grow to see how a simple business intelligence system can simplify and enhance your marketing process. Or, you can check out one of our marketing cheat sheets here.
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