How do independent coffee shops compete with international sensations like Starbucks and Dunkin? Or are these two types of experiences not in competition at all?
We took a look at SafeGraph Patterns data to try to understand how consumers interact with local, independent coffee shops compared to major national chains.
SafeGraph Patterns measures foot-traffic patterns to 3.7MM commercial points-of-interest and provides a monumental window into American commerce. SafeGraph data users look through this window to ask detailed questions about consumer behavior (e.g., What is a brand’s true customer demographic? How far do people travel to go grocery shopping? What is the impact of opening a national brand coffee shop on all the other coffee shops in a neighborhood?).
We analyzed every point-of-interest in Washington D.C. categorized as NAICS code 722515 - Snack and Nonalcoholic Beverage Bars (over 250 locations). This category is dominated by coffee shops, although it also includes retail bakeries, smoothie bars, doughnut shops, ice cream shops, bagel shops, and other similar establishments. The analysis included all of these locations, but for conciseness we refer to these places as “coffee shops” throughout this article (note: in January 2020 SafeGraph launched a new feature called category_tags that allows us to hone in on coffee shops exclusively for future analyses).
Here were some of the top brands in this Washington D.C. dataset:
We wanted to investigate differences between national chain brands vs local homegrown independent businesses. SafeGraph Brands (safegraph_brand_id) helps distinguish these two types of places. Additionally, we also wanted to investigate possible differences between national brands vs local or regional brands. So, we manually categorized all of these businesses into one of three classes.
The duration of a visit (i.e., dwell time) to a coffee shop has a lot of variance. Some people order to go and are in-and-out in 5 minutes.. Others come to a coffee shop to be social, or to work, or to read, and may stay many hours. We wondered whether these types of behaviors varied between visits to single-location businesses vs visits to chain coffee shops. Analyzing the columns median_dwell and bucketed_dwell_times we discovered a major difference.
Visits to single-location coffee shops (blue) have a median dwell time that is around 80% longer than visits to major chains (orange) (difference p<= 0.01).
Interestingly, Local Chains (businesses like Firehook Bakery or Qualia Coffee that have >1 location, but only locations in the Washington D.C. metro area, green bar) are more similar to Single-Location businesses than Major Chains.
To dive into these dwell time distributions more, we used the bucketed_dwell_times column to reveal a striking difference in the dwell time patterns of consumers at these different classes of coffee shops.
It turns out that the dwell time differences between visitors to Single/Local vs Major chains is entirely driven by differences in the shortest and longest dwell times. Major Chains (orange bars) have dramatically more of their visits in the 5-20 minute range, and dramatically fewer visits lasting longer than 4 hours.
20% of visits to Single-Location and Local Chain coffee shops last greater than 4 hours (compared to only 14% for Major Chains).
4 hours is a long visit, and likely includes visitors who sit in comfy chairs to read, plug in a laptop to work, or spread out notes and textbooks to study. It is striking to see that, for these extended types of visits, consumers in Washington D.C. vastly prefer single-location and local chain coffee shops over major chains. If you want a quick 5 minute coffee to go, Starbucks and Dunkin dominate. But if you want to sit back, settle in, and spend an afternoon at a coffee shop, people seek out local, unique places.
What other differences exist in consumer behavior between local vs chains? Using the column popularity_by_day, we asked what days are people most frequently visiting coffee shops?
Across the week, visits ramp up and then ramp back down. Peak foot-traffic to coffee shops occurs on Tuesdays and Wednesdays, and the fewest visits to coffee shops are during weekends. In general, this pattern is the same for Major Chains, Local Chains and Single Location businesses. However, there is an intriguing trend suggesting that consumers possibly prefer visiting single location coffee shops on the weekends more than they prefer to visit chain coffee stores on the weekends (see blue bars higher than orange bars on F, Sa and Su, but lower than orange bars on M,Tu,W,Th).
Above we saw that consumers prefer single-location and local chains for long visits. And intuition suggests that people are more likely to spend 4 hours at a coffee shop on the weekend compared to a weekday, so this may drive the preference for single-locations on the weekends.
The dwell time data suggest that local, independent coffee shops and major national brand coffee shops may not be competing for the same consumer experience. Almost 50% of visits to Major Chains last fewer than 20 minutes, whereas for single-location coffee shops the number is only 38%, so Major Chains are winning the majority of shorter visits. But when it comes to spending long visits reading, working, or studying (or whatever else you do in a coffee shop for many hours), consumers prefer single-location and local chains much more than major chains. The data also show that consumers treat single-location and local chain coffee shops similarly, and different from major chains.
This opens a number of interesting possible future investigations. If local businesses offer a unique value proposition compared to major chains, are people willing to travel farther to visit local businesses vs national chains? Are consumers visiting both types of coffee shops for different experiences, or are the two patterns of consumer behavior truly distinct demographic populations? If the customers are different populations, what other types of shopping patterns distinguish these two groups? Should major chains like Starbucks and Dunkin compete for long visits? Do similar differences exist for other categories of places, like restaurants or grocery stores? Questions like these can all be explored using SafeGraph Patterns data. To try some for free, use the coupon code LocalVsNationalCoffee for $100 of free data.
Please send us your ideas, feedback, bug discoveries, and suggestions to [email protected]
Use the coupon code LocalVsNationalCoffee for $100 of free data at the SafeGraph Data Bar.
That's it – that's all we do. We want to understand the physical world and power innovation through open access to geospatial data. We believe data should be an open platform, not a trade secret. Information should not be hoarded so that only a few can innovate.