In 2019, the S&P return including dividend reinvestment was 33%. When times are good with easy money monetary policies, full employment, and a government favorable to business boosting domestic production, machines and anyone with the Robinhood app can feel like a hero.
Investors try to meet the challenge
One of the unfortunate consequences of the Coronavirus is the serious spike in market volatility, putting the first quarter deeply in the red. Now, Wall Street has been pressed into service to prove that investment professionals can yet again beat the market, or at the very least manage the downside better than passive management; an allocation of target date funds mixed with ETFs.
There is a new breed of data sets that are required for investors to maintain competitive information ratios. Investors in their collective best Darwinian approaches have been upskilling to meet this challenge by learning how to code, sourcing alternative data, and using heavy computing power to create robust financial models to predict market behavior and produce outsized returns. While I was at Bloomberg I spent several years reviewing these new data vendors for data uniqueness, data quality, and data availability.
Alternative data and modeling
More and more alternative data providers are springing up to address this need. They're scraping millions of web pages, creating partnerships with non-traditional sources, and even deploying drones to monitor trade flows and economic activity at ports.
Investors plugging away at creating prediction models need the right mix of old and new. They need a macro model to consider the expanding government balance sheet, trade flows and tariff negotiations, oil supply demand characteristics, the latest job reports, and further the ongoing battle with the world against the virus.
There are several factors required to predict the shape of a recovery that hinge on the effectiveness of stay at home containment, economic support policies, private sector behavior, and of course consumer confidence. This manifests all the way down to the microeconomic level; Will the consumer buy a few pairs of sweatpants and watch Netflix for six months, or will the consumer buy some richer degree of discretionary goods out of habit in anticipation of a return to normal life? It is hard to ignore the almost full stop of movie theater attendance, mall patronage, and dining-in at restaurants.
A current look at retailers through the lens of alternative data
Perhaps the industry undergoing the most turmoil right now is the retail industry. It has been under pressure to achieve the right mix of experience economy, in-store purchases, and most importantly, ecommerce. Investors will want to assess web and app data in these categories to augment models that were previously only driven by the physical economy; foot traffic, average checkout size, same store sales comps, etc.
I have been curious about all of these considerations from my seat at Ascential, where we have alternative data for the investment community. Our core business serves all of these retailers and CPG companies with price, promotion, market share, and other critical data sets. This information pairs well for investors with mobile app, credit card, and location data. To get a handle on these changing digital trends, we reviewed 20 representative retailer apps using Apptopia data. The following data is worldwide data and combines estimates across Apple and Google platforms.
The 20 apps we reviewed follow a power law which is significant in its scale. The top quartile of Walmart, Nike, Zara, H&M, and Target hold an 89.7% share of sessions in Q1 2020, representing 73 million sessions. By comparison, those in the cohort who are more experience driven with in-store purchasing (DSW, Lululemon, Gap, Bloomingdale's, Neiman Marcus) had a total of 382,000 sessions or 76,400 sessions per day. Those with an in-store experience and less digital customers will likely suffer revenue losses more heavily from the Coronavirus as their customer base is not acclimated to patronage from a digital experience first perspective.
Many iconic apparel focused brands including Kohl’s, Macy’s and Gap have recently announced significant challenges in their core businesses after several weeks of store closures. They ostensibly have joined a growing cohort of retailers that have announced restructurings to core operations. These moves have halted pay for a large percentage of their workforce - preserving only critical employees in operations, front office, and online fulfillment & support. Although the negative catalyst here is Coronavirus related, these general changes in trends and online & offline consumer journeys can’t be ignored. Who doesn’t occasionally succumb to buying a new bathing suit on Instagram while day-dreaming about an island vacation?
Further, struggling retailers like Macy's and Kohl's, that have been upfront about their challenges with various employee furloughs and restructuring plans, are seeing daily sessions and downloads plummet. Macy's daily downloads have been ~10,200 per day in the last quarter and dropped to ~7,200 in the last seven days. Kohl's is in a similar situation, dropping from ~8,800 per day in the last quarter to ~6,100 in the last week.
Keep your ear to the ground for the changing dynamics across consumer and retail supply & demand habits. Price changes and promotions will likely be fluid and we are all hopeful for a recovery and return to a more stable/predictable environment. Irrespective, as an investor or stakeholder, make sure you have the data you need to stay up to date.
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Jeremy Baksht
SVP, Ascential Alternative Data Division
Jeremy Baksht
SVP, Ascential Alternative Data Division
