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Collecting data stinks… Do this instead.

Automating data collection can save you a significant amount of time and effort, and it can help to ensure that your data is accurate and up-to-date.
a photograph for charts being displayed on a monitor

As a leader in a marketing team, you are likely very interested in your data. Every tool we use has some level of reporting capability, and most of the time, we find them valuable. We use their charts and graphs to find insights from the data. When we see something that gets our attention, we can do a deep dive to try and understand what the data is trying to tell us. 

So what’s the problem with that? Nothing really. It’s just when we’re looking at data, we look at it for more than one reason. One reason is that we are tracking the performance of our goals. Another is that we try to create meaning from the data we collect. Tracking your progress and metrics is considered data collection. Understanding the “WHY” behind the numbers and providing future recommendations is data analysis. I will argue that we need to minimize the time we spend collecting and organizing the data and maximize the time we spend analyzing the data.

Importance of separating data collection from data analysis

If we subscribe to 5+ marketing tools and want to track our performance, we need to get data from 5+ places. As your marketing stack grows, getting your data from so many fragmented sources is problematic. Many times, marketing teams will create an internal spreadsheet that combines the data from all of their sources. 

It’s important to know that I am not talking about data analysis when referring to reporting. Creating meaning from our data is an important job that should be done independently and not combined with the reporting function. 

Separating reporting from analysis means we will not trick ourselves into thinking that generating reports and collecting data is the primary focus and end goal. Our long-term results will improve if we devalue data collection and prioritize the time we spend analyzing our data. 

The case for automating data collection for reports

Suppose the reports that give you the most information are automated. In that case, you will quickly be able to see interesting data, trends, and outcomes that you would want further analyzed, especially when you can look at the trends over time. Below are five reasons data collection for reports should be automated. 

  1. It’s efficient: Automation eliminates manual, repetitive tasks, reducing the time and effort required to complete them. With the extra time savings, you can focus on higher-value activities (like data analysis).

  2. It’s immediate:  Instead of going through each tool you use and copying your data over manually, automation collects and process data continuously, providing up-to-date insights.
  3. Grows with you: Today, you might have data from five sources. What happens if that grows to 15? More and more time is spent gathering data instead of analyzing it. 
  4. Focus: If you couldn’t tell yet, I really don’t value collecting data. I value analyzing the data. By removing the need to collect data manually, all your time is spent trying to make meaning of your data is so much more important. 
  5. Customization: If you automate your data collection, then you can modify the data with custom code. Sometimes the tool you are using doesn’t provide you with the results you need, and you create a custom spreadsheet to fill the gaps. If you automate the collection of data, you could also automate the processing of the custom logic that you introduced with your spreadsheet. This is super powerful. 

When should you automate your data collection

Automation is important because it enhances efficiency, scalability, timeliness, and productivity. It empowers you to optimize your reporting processes and make data-driven decisions. But, if you do it too soon, you will regret it. If you read my article about creating the best possible marketing scorecard, you know there is a bit of trial and error in developing your reports. 

Here are some tips that I think about before I automate anything. 

  1. Define what is important, or at least what you think is important at the moment.
  2. Track the data for a while manually, and determine if it is as important as you think. 
  3. Adjust your metrics as needed, throw out ones that don’t matter, and add data that does matter. 
  4. Repeat steps 1-3 until your reports are stable and useful. Then AUTOMATE!

What are your automation options?

Many tools collect data from different sources and provide a reporting dashboard. My recommendation is to go through a progression of complexity, start with the simplest first, and go from there. For me, the simplest starting point is always a spreadsheet, and then when things get too complicated, I grow to the next level of complexity. 

  • Google Sheets: The benefit of using Google Sheets is that it integrates with all Google products. It also allows custom scripting so you can easily connect to different data sources and save the data in a format that you find helpful. On the downside, you are locked into Google at that point (I wonder if that is actually bad). 
  • Google Looker Studio: Previously known as Google Data Studio, Google Looker Studio is awesome for marketing teams. It will connect to many types of data connectors and provide a very nice way to present your data. You can always save your data in Google Sheets and present the data with Google Looker Studio. 
  • Tools like Databox: There are many solutions out there that connect to different data sources and allow you to visualize the data. The upside is that this is not a Google Specific solution. On the other hand, you are just as tied to this new solution, so you better like it. Most of these tools allow you to interface with their API, so if you want to customize the data, you could with the right know-how. 
  • Custom Interface: Going the custom route is pretty advanced. It’s great because you can do whatever you want. It’s not great because of the time and cost to set it up, and then you must maintain it. One alternative is using a solution like Databox, Google Looker Studio, or something else to have custom code to perform your desired calculations and customizations using their APIs.  

I can tell you with a decent level of certainty that if you really want automation and efficiency, at some point, you will need to have custom code written to get exactly what you want. I don’t think this is a bad thing. Either teach yourself how to do this level of coding or work with a developer that can help you. If you are working with an agency, they can likely help you automate your internal dashboards. 

It’s most important to spend as much time as possible doing the knowledge work you are an expert at. Deliver this value to you, your team, and your peers rather than wasting time and resources on tasks that don’t push the needle. 

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