Canadian clothing retailer Lululemon ($LULU) is shutting down its children's brand Ivivva. One would think, in a vaccuum, that would spell trouble for Lulu. But in reality, this is simply cutting off a dying twig on a money tree, because Lululemon has never been doing better in its history, and we have the alternative data to prove it.

Social media

When we break down Lulu, the first thing we noticed was the social media following numbers.

There was a 8% spike from September 9th to the 10th, which may or may not have been from a cool photo of people doing yoga in front of the Eiffel Tower. The Lulu Instagram game is strong, and fun fact, has actually tripled in follower count over the last three years.

It might have taken almost five years, but Facebook likes and followers doubled to over two million. I'm not sure Facebook is the "cool" place to gather young people to buy your products, so this is more icing on the cake than anything else.

The "Were Here" count, however, is worth noting. More than 100,000 people marked that they were in a Lululemon store this summer, and that's significant because people in stores, you know, tend to buy things there.

The Twitter following is at a plateau, but the rest of the social media metrics more than make up for that. There's no reason to believe these trends won't continue into the near future, as long as people want to see yoga pants and then decide to buy said pants.

Hiring, stores, and stock

The job figures are remarkably bouyant for Lululemon, which sports strong numbers for openings and for employee count.

They aren't slowing down growth and have doubled the size of the company from 2015 to earlier this year.

You can get a better sense of the Ivivva stores globally, and how those will inevitably either close down or be turned into Lululemon proper.

Who knew Lululemon was huge in Austrailia?

About the Data: 

Thinknum tracks companies using information they post online - jobs, social and web traffic, product sales and app ratings - and creates data sets that measure factors like hiring, revenue and foot traffic. Data sets may not be fully comprehensive (they only account for what is available on the web), but they can be used to gauge performance factors like staffing and sales. 

Further Reading: 

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