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The Beauty of AI-Driven Social Media Analysis for Business Planning

Beauty may be only skin deep, but truly understanding the beauty products market is no mere cosmetic exercise.  Quite the opposite: business success requires insightful analysis of competitors, products, and consumer attitudes. To that end, mining social media with an assist from AI technology can be invaluable.

For example, the clean beauty movement has been gaining traction around the world as people increasingly care about the ingredients that are in their beauty products and the impact their buying decisions have on the planet.   Let’s take a look at a few tweets in this space to see which brands are reaching their target audience and who’s missing the mark.

We consulted Beauty Insider, an expert on the cosmetics industry that runs big events in Manhattan for a global brand, with some social media questions.  We pitted machine learning-powered Northern Light Social Analytics against Beauty Insider’s extensive professional knowledge of the industry to see how our tool might add value.

Which hashtag has the broader reach, #cleanbeauty or #veganbeauty?

Beauty Insider’s answer: “#cleanbeauty should definitely be used more frequently.  This is the term we’re using with our clientele in stores when we promote a product’s natural ingredient attributes.”

Correct answer:  #veganbeauty has twice the reach of #cleanbeauty.  With a 77% semantic similarity, the hashtags are in the same conversation, so #veganbeauty is the clear winner here.

Bonus answer:  #crueltyfree has reach more than 10x that of #veganbeauty and #cleanbeauty combined!  With an 86% semantic similarity, it’s the best choice for a cosmetics marketing company to use.   @Covergirl got this one right.  They’ve used #crueltyfree 76 times in the past 90 days for a total of nearly 50 million impressions.

Sephora and Covergirl are both in the market of selling beauty products.  How semantically similar are their tweets?  0-25% similar; 26-50% similar, 51-75% similar, or 76-100% similar?

Beauty Insider’s answer:  26-50% similar.  I think they have overlaps around market trends (#redlips, #wokeuplikethis, #naturalbeauty, #cleanbeauty etc.), but then vary widely around specifics like brands, products, retail locations, naming people etc.

Correct answer:   7% semantically similar.    Sephora’s top five Sentiments are “beautiful”, “sorry”, “thank”, “beauty” and “happy”.    Covergirl’s top five Sentiments are “beautiful”, “easy”, “glow”, “fresh”, “sweet”.

Follow up question: which brand has a bigger audience on Twitter?  

Beauty Insider’s answer: “I think Covergirl has more impressions because I think a larger percentage of their customer base is on Twitter compared to Sephora.”

Correct answer:  Sephora.   With nearly 2.4 million followers, each tweet by Sephora has a far broader reach than Covergirl with about 650,000 followers.

Influencers are known for having a big impact on the beauty market.  Which of these influencers has the biggest Twitter following: Huda Kattan, Jeffree Star, or Marlena Stell?

Beauty Insider’s answer:  Jeffree Star.

Correct Answer:   Jeffree Star.   With 7.5 million followers, he is the clear winner over Marlena Sell with 73,600 followers, and Huda Kattan who does not have a Twitter account.

Final score: The human industry expert at Beauty Insider got one out of four answers correct. Northern Light Social Analytics got all four answers correct.

We all think we know our industry inside and out. However, this brief conversation shows that intuition is fallible. When even a beauty industry insider gets only one out of four questions right, it’s clear that experience or gut instinct isn’t enough to bet your marketing budget, and your company’s online reputation, on.  Northern Light Social Analytics gives your team the power of AI-driven analysis for making sound social marketing decisions – and that’s a beautiful thing.

If you’re ready to take your Twitter marketing to the next level, contact us or request a demo today.

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