UX Designer/Researcher Crafting Unique Experiences

MACM1

 Mac and M1 Processor Insights

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Out of about 32,000 comments for the MacBook Air, Pro and Mini with the new M1 chipset, these are the insights and trends that emerged.
 

Overall Sentiment

The graph below shows a majority of positive comments in regards to the Macbook. Positive sentiment accounts to a 70% of non-neutral comments. This indicates that the MacBook is well received although not as well as the Iphone, Watch and iPad in the data collected from Youtube.

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Term Frequency

Top 30 words mentioned in 23,462 positive comments relating to new Mac M1 line including Macbook pro, Macbook Air and Mac Mini.

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The most interesting words that most frequently come up in the positive comments for Mac and M1 are video, chip (M1 for the win!), perform, and battery. The M1 chipset is making a splash with its amazing and efficient performance while maintaining great battery life.

 

The Top 30 words mentioned in 9,265 negative comments relating to new Mac M1 line including Macbook pro, Macbook Air and Mac Mini.

Within the negative dataset for Mac and M1, we can see there is a lot of reference toward Intel, Windows, Ram, and chipsets. The IDF will allow us to get some better insights into this category.


 
 

Inverse Documentation Frequency

This gets us insights into the the Keywords that come across both documents. Once I ran this algorithm I sorted them into 2 lists for most frequently occurring in Positive or Negative.

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The positive list has some really great insights. We can see that people are using the product for editing and are really focused on the looks and how ‘pretty’ it is.

The negative list provides some really key insights on what people don’t like. Linus the YouTuber comes up as one of the most negative terms within this list which indicates that he does not endorse Mac products. We can also see intel, the ports, touch(bar), screen and AMD come up. Apple’s M1 chipset is doing so well it’s challenging Intel chipsets and people are noticing.

These are key insights that should be focused on and improved within the next iteration of this device.