Foot Locker ($FL) kicked off this morning with a bit of great news! The Zack Consensus Estimate of $1.58 per share got beat by five cents. Unfortunately, that was the only real bit of good news, since there's a ton of competition in the sports clothing and athleisure space today.
"While we had leading positions in key on-trend footwear styles, this was not enough to offset softer than expected demand during the compressed holiday season, a very promotional marketplace for apparel, and tougher launch comparisons." - Richard Johnson, CEO of Foot Locker
But with a weak holiday, lots of options for buying shoes, and (just our observation) declining ratings for sports, how can we interpret this morning's earnings call for Foot Locker using alternative data?
The stock (and the sky) are falling for FL. The employee count has gone up by 4% over the last three months, but the stock price has dropped 19% since the start of February. Not ideal for those two lines to be going in different directions.
The job listings data also gave us whiplash, falling 12% in a single month. It's still quite high, and maintains a good average amount of new openings, but the last thing we want is volatile data for a company. Well, the company doesn't, we love it because it makes for a better story. We love drama.
After some good growth in both the Twitter and Facebook followers/likes charts, things have leveled off in the past year. The plateau might be coupled with the weaker holiday shopping season we saw in the earnings report. But the Facebook Talking About count is still pretty good considering, which makes it all the weirder that people were talking about Foot Locker but not actually going to Foot Locker.
Finally, FL's Instagram game FL is the one bright spot within the data. Since September, there's been an 11% bump in Insta followers. Maybe Foot Locker can start leaning on the 'gram to push business with some new products.
About the Data:
Thinknum tracks companies using the 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.