How to Reap Insights from This Fall’s Data Harvest

As the leaves fall off the trees and the ground starts to harden, you likely have pulled everything you wanted from your gardens and left the rest to freeze.

Fall also brings the final quarter of the business year.

In all likelihood, you have been collecting marketing data all year. You have a database filled with contacts, social media and email marketing data, and more.

But what are you getting out of this data? You’ve done the work, you’ve grown your crops. Now it’s harvest season and you need to consider what you can do and learn from the data you’ve compiled this year.

But where do you start? How do you get insights from all this data?

Figure out what you’ve collected

To get started, you need to determine what data you have. If you’re like many smaller companies, you may have data scattered across several different channels and silos.

You need to dig into every source of data, so you can use it to help find insights. Where can you find data?

Try:

  • Google Analytics — go to Google Analytics and you will find everything about your website’s traffic. It will tell you what channels your web traffic came from and when and where your audience goes after they reach your website.
  • Social media accounts — list out each social media channel you post on. If you haven’t been tracking data on these channels (you should) you can download a year’s worth of data off of each of the networks you use.
  • Email analytics – your email/marketing automation collects analytics for you, pull about a year’s worth of data from here.

Parse and Hygiene Your Data   

From there, you need to make sure your data is consistent and accurate. Otherwise, you’re trying to pull insights from data that might contain false information, data which is improperly entered, or data that doesn’t match the formatting of the rest of your data.

You will likely have to do this step for every channel you pull data from.

Sometimes, if you’ve pulled data from a third party like Pinterest or Twitter, you may have to reformat data to meet your needs. Ideally, most or all your data from similar channels (like all social networking channels) will be the same so you can analyze the data against each other.

This is the equivalent of washing and cleaning your final fall harvest. You don’t want bugs sneaking their way into your kale salad or dirt adding an extra crunch to your eggplant. Don’t skip this step. It’s much easier to make accurate insights

Hypothesize and Look for Oddities

It’s hard to find insights in a bunch of raw numbers.

First, before you start sorting through your data, think about what you expect to see in the data.

This includes:

  • Trends you expect to see
  • Spikes in engagement or traffic related to content or campaigns
  • Relationships between important data points

These expectations are basically hypotheses about what you expect to find in the data. You can use them as markers to see what’s true and what isn’t.

From here, you must dive into your data. Focus on a channel. Keep your focus narrow to start. Now make bar graphs, scatter plots, rearrange data to see trends.

Now ask, is this what I expected to see?

The answer will likely be no, and if it isn’t you either know everything about your business or you haven’t searched hard enough.

Look for what doesn’t make sense. You’re looking for “that’s odd” or “that doesn’t make sense.” Those are insights, not just strange flukes in the data.

At first, it may seem hard to find these relationships. You might struggle to find insights. You’ll get better at it the more you do. Another great tactic is to seek out a mentor in your industry, lean on them for the business knowledge you don’t quite have yet.

From there, just keep digging, look for what doesn’t make sense and don’t just stop at, “Huh, weird.”

Dig deeper and you will find the insights that will help both your marketing and your business grow.

Let us know what you think:

  • What questions do you have after searching through your data?
  • What are your favorite uses for your data and the insights you pull from them?
  • What have you learned about your business from drawing insights from your  data?

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