Social Media – Breakdown #2

Dun Dun Dun, it’s another social media break down but this time, we are looking at a partnership post.

Last time, I broke down Google’s Tweet for National Ice Cream Day. Today, I will similarly break down a post, but this time, it is from Microsoft and involves a partnership with clothing and lifestyle brand HYBEBEAST.

Social Post Rating:


Rating: 3 out of 5.


Rating: 5 out of 5.

Clear Objective/CTA:

Rating: 4 out of 5.

“It’s the intersection of function, style and comfort for me.” 

The copywriting is short, cool, and involves trending terminology for Gen Z and Millenials. HYBEBEAST’s brand is a hub of knowledge of fashion and lifestyle trends, so Microsoft’s post needs to reflect that language to appeal to this particular audience. 

“More on Hardwear from 


The following line includes Microsoft tagging/mentioning HYPEBEAST, highlighting their partnership, and directing viewers to a link. The CTA is clear–encouraging viewers to follow and engage with HYPEBEAST’s twitter and venture to the link for more information on the collab.

But what is interesting is that the link does not drive you to Microsoft’spage but HYPEBEASTs. 

The Link:

I do not see any UTM tracking, so I wonder how Microsoft’s team is tracking the engagement. Anywhoozels, the link brings users to a page titled: Microsoft Partners With Supervsn’s Gavin Mathieu for an Exclusive Capsule Collection, bringing attention to Microsoft’s collaboration with HYPEBEAST’s brands. The page consists of stylish photos from the collab and answers why the tech giant would be interested in this partnership, stating, “Technology inspires fashion with the announcement of corporate giant Microsoft’s recent partnership with Supervsn Studios’ pioneering founder Gavin Mathieu. The two have teamed up to create an exclusive capsule collection inspired by normcore.”

This PR announcement has several actions for users who want to continue their experience – sharing on other social media platforms, a comment section, featured/spotlight articles, and even stock information for HypeIndexB. 

Now let’s consider various types of user experiences from this post: 

  1. Jane, a 25-year-old woman from New Jersey, opens Twitter and sees the Microsoft post. She looks at the post but does not engage.
  2. Jane, a 25-year-old woman from New Jersey, opens Twitter and sees the Google post. Finding the post interesting, Jane “likes” the post but does not engage further.
  3. Jane, a 25-year-old woman from New Jersey, opens Twitter and sees the Google post. Finding the post interesting, Jane “likes” the post and clicks the link, interested to know more. Scrolling through the content, Jane eventually closes out of the site.
  4. Jane, a 25-year-old woman from New Jersey, opens Twitter and sees the Google post. Finding the post interesting,, Jane “likes” the post and clicks the link, interested to know more. Scrolling through the content, Jane finds herself enjoying her time and wants to check out the “Spotlights” section, where there are other articles by Hypebeast to view similar content.

Now, what does each interaction mean? You can learn more about KPIs & Metrics, and their definitions in my previous posts:

  1. Jane looks at the post but does not engage, so her view will be considered an “impression”. Jane might also only be interested in content that comes directly from Microsoft. Jane may not be the target audience of HYPEBEAST or is unaware of the brand. Brand awareness is key when considering partnerships!
  2. Jane looks and “likes” the post, so her view and “like” will be captured as an impression and engagement. Jane thought the post was interesting to engage with the post but did not want to know more.
  3. Jane looks, likes, and visits the website. Jane scrolls through the page but does no other actions. In this scenario, Jane’s actions will be captured and can be reviewed in Google Analytics. Here the (DM) Digital Marketing team will see that a viewer was brought in from the organic post, and they will also see the average engagement time of all of their viewers. Though Jane is only one person, through the data that is collected, the DM can team can learn from this experience and strategize how to target users better. They can consider many things – “If viewers are being taken to our site, they are not lingering? Is it because the website is taking too long to load? Should we reconsider the user journey? Is it easy to navigate? Is the content engaging enough?” So despite Jane not engaging with the page’s content, her data is still captured and the DM team can restructure their strategy to get more Jane #4’s.
  4. Oh, why can’t there be more Jane #4’s in the world? Jane does exactly what Microsoft and HYPEBEAST wanted – she viewed the post, liked it (which allows other people that Jane follows to see that she engaged with; go JANE), clicked the link to the website, viewed and engaged with the content, AND clicked another link, directing her to another website on HYPEBEAST’s page. Microsoft did not use UTM tracking for this campaign but HYPEBEAST’s team will be able to share reports of users’ actions. So, Microsoft’s DM team will be able to review all of Jane’s captured data and try to understand better why she engaged and get others to follow suit. And because Jane is a 25-year-old woman from New Jersey who frequently engages with Twitter, we can start targeting her knowing her behavior. From this interaction, we know that Jane likes a post that has a playful ToV and possibly understands trending vernacular. Jane also is curious; she wants to know more about why Microsoft is collaborating with fashion and lifestyle brand HYPEBEAST and information pertaining to the posts. Jane is likelier to click a post to investigate rather than be content with a simple post with a few sentences. So Jane is patient and curious–she will be a great target to send her information with lengthy copywriting and backlinks to other pages, and maybe, just maybe, she will be a potential lead.

What are other posts you want me to break down?

5 thoughts on “Social Media – Breakdown #2

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