Data, Data, Data
So, how do you know that all of your branding efforts are successful?
Let’s analyze the data!
I sat down with MP&F’s Digital Advertising Specialist, Emily, to discuss how she uses analytics to track the success of branding efforts.
Here are my top takeaways:
- Pixels are important
- Utilize Facebook analytics
- Be strategic with what content you “boost”
To put it very simply, pixels are pieces of code that can be connected to online links that allow you to track and measure reach, engagement, and other vital pieces of data. Pixels are the key to seeing how your content is doing online. A large part of what Emily does is track and analyze data from pixels in order to survey and adjust advertising strategies.
In addition to pixels, Emily told me that Facebook itself offers its own set of analytics. If you login to an organization’s Facebook page, you have access to the analytics tab. This tab allows you to view a plethora of data that can actually help you understand who is engaging with the brand and how often.
Most people have probably seen the “boost” button on Facebook posts. I have always wondered, what content should be boosted? Emily said that the content that is worth the investment to boost is the content you are confident people will want to see. You should not be boosting seemingly trivial posts that are hit-or-miss on whether the audience will be interested. Boosted posts are the ones that you want to reach the largest amount of viewers, so it should be reserved for some of your best content.
While it can be difficult to measure if a brand is totally successful based off of numbers alone, one can measure success by seeing how many people are engaging with a website, how long they spend perusing the website, and if people are taking actions. These actions are referred to as conversions, which are defined in a Skillcrush.com article as “instances where a website user, ad viewer, or email recipient takes a specific action they’re led toward by the site, ad, or email content” (Morris, 2018).
For example, Emily explained that she was analyzing an online advertisement that was a call to action for people to sign up for an email list. A large number of people were clicking on the advertisement, which is a good sign. However, an incredibly small percentage of people were actually signing up for the email list. While it seems good that the ad had a large reach, the ad was not accomplishing what it was intended to do. To Emily, this was a call for her to turn to the ad itself and strategically make changes for the better. Maybe the ad wasn’t properly portraying the voice and look of the brand and instead looked like a generic advertisement. Maybe the ad wasn’t reaching the brand’s target audience. These are some conclusions she was able to make based off of key data, which highlights the value in understanding analytics.