As vaccines roll out and consumer confidence grows, we expect to see a significant return to in-person class fitness. To that end, we wanted to study which data is predictive of existing fitness studios like SoulCycle and Crossfit. To do so, we collected Census data within a 10-minute drive from thousands of points in NYC and regressed it against the number of studio fitness locations. Of the 50+ variables studied on population, occupation, education, and income, we found that the number of $200k+ income households had the strongest correlation to number of fitness studio classes, with an r^2 of 0.66.

Many organizations struggle with gathering and reporting data. Writing information down on paper and sending excel sheets back and forth can lead to issues with data quality and privacy while making reporting almost impossible. Webster Pacific has developed efficient systems to get data into the cloud and then use it for reporting. Use cases have included 1) factory employees recording daily production, 2) vendors recording product specifications, 3) teachers recording test results, 4) executives recording business performance indicators. See example forms and reports below.

Custom Form and Reports

Webster Pacific continues to expand analytical capabilities for real estate investors of all asset classes. We gather data for our clients on demographics, income, competitive supply and alternative data like proximity to quality restaurants and transit. See below example of demographic data that a multi-family (apartments) investor may want to consider when investing in Philadelphia. You can also watch a video of Steve presenting the data here.

Because many of our clients are e-commerce companies, we were curious to know what level of stockouts are experienced by other e-commerce companies. We were quite surprised to find that 9 out of 10 companies we studied had 40% or more of their products stocked out. This would be like a grocery store having 4 out of 10 shelf spaces empty. We think this situation represents a significant revenue opportunity for e-commerce companies, and we have developed and implemented a solution.

Specialty food and beverage companies (e.g. craft beer) have lost substantial revenue from COVID-related closings of restaurants. Fortunately, most stores are still open. To help find revenue opportunities, Webster Pacific built a tool to find stores (and other venues) where your competitors are carried and you aren’t. The redacted example below shows venues in Chicago where “XYZ Brand” of beer is stocked and other venues where competitors are stocked. This tool can be used as a hunting list for salespeople and a market strategy tool for leadership. You can interact with the map here.

In the current environment, retail store sales are basically nonexistent, which means that brands are being forced to rely on Ecomm. To that end, we have been helping our clients use geospatial data to find MSAs and Zip Codes where their Ecomm is weaker than it should be. We do this by comparing our client’s Ecomm sales (where they are successful) to the presence of their competitor’s physical locations (where they should be successful). The scatter below shows a client under-performing in Midwestern markets.

Webster Pacific believes that the foundation of any analysis is strategy. In our location analytics work, we go beyond what software tools and real estate brokers provide, by thinking deeply about our clients’ business and how they are strategically positioned. This means understanding the competitive landscape. We created the below 2×2 matrix to better understand the fitness landscape.

• Gyms have expanded outside of the US more than studio classes. This is a function of 1) gyms are easier to franchise and 2) the concept of studio fitness is newer than gyms.
• Equinox is not being challenged in the luxury gym space. Most competitors are in-market high-end clubs (like Bay Club, which is only on the west coast).
• There is a much smaller price-spread for studio classes than for gyms.

We are developing a new database tool for any high-end, single-brand retailer. Most of these retailers are focused on selling their brand in department stores like Neimans, Saks, and Nordstroms. Another less-traveled channel is local, high-end boutiques, which sell multiple brands, but are much smaller in size and located in only one premium neighborhood. With thousands of these boutiques in the country, finding the “right” one can be a challenge. 

Through our work in retail location strategy, we have begun to develop a database of these boutiques. This database includes fields for things like brands carried, surrounding stores, years in business, and wealth-level of surrounding neighborhood. This database can be used by retail sales teams for driving growth.

Part of serving our retail clients involves understanding their competitors’ target customer and market entry strategy. We analyzed Sephora, one of the largest companies in the personal care and beauty space, and found that their locations regress most closely with total households and not a particular income range. This is evidence that Sephora is a mass-market brand whose target customer comes from a wide range of income levels.

You can interact with these Tableau Vizzes here.