Starbucks opened its first reserve store in Mumbai a few days back! Let’s deep dive into how Sherlock AI could help Starbucks India in identifying the exact locations where they should their premium cafes. After there is a lot at stake while expanding showrooms! (literally millions of dollars!)
What makes a Starbucks café successful?
Earlier we saw some how Sherlock AI understood how different parameters affected a premium coffee outlet’s performance. Key takeaways from Sherlock AI’s analysis of all premium coffee shop locations in Mumbai and the type of people visiting there. (Read the previous article here)
- Locations of high commercial index (top 20 percentile) suited best for high-performing cafes
- Locations of high-well being index (top 10 percentile) bide well for the outlet’s performance
- Moderate Hospital index between 0.4 to 0.65 (neither too high (high healthcare POI concentration)- nor too low (no healthcare amenities in the locality)) was important for a successful café
Sherlock AI start with layering in 3 different indices in the city of Mumbai
- Places Index™: How well connected the location is to other places (shopping POIs, entertainment POIs, malls, other showrooms, etc.)
- Prices Index™: What is the spending capacity of the person like (mixture of multiple parameters such as how many affluent showrooms & restaurants are present in a locality, what are the average menu prices for restaurants, cafes and other places in the locality, etc.)
- Commercial Index™: Presence of offices, commercial establishments and IT parks in the locality
This is the map of Mumbai with all the above indices interlaid on top of each other- note, that each 100 meter block has a distinct value. You know what they say, nothing gets past Sherlock and Sherlock AI is as granular as it gets! 🙂Bluest regions are the regions ranking the best among all the three parameters, light blue regions rank moderately whereas red colored regions signify the lower percentiles. (Deeper the shade of red, worse the locality’s score is)
Now we add the commercial index filter, which ensures that we only look at micro-localities which are in the top 20 percentile of the commercial index-per Sherlock AI’s previous deductions on what makes a café outperform. This filters down the number of localities to a considerable level as below (filters away Sanjay Gandhi Park region, extreme East of Mumbai, and some of the low income slum locations)
Now, Sherlock AI adds in the prosperity index (wellbeing index) layer on top of this as a filter- the top 10% of micro localities based on WBI™, which brings us to a filtered and a more target set of locations. Please note that, in the below graph, localities in shades of yellow will have a higher preference than the ones in red
Now, the final piece of filtering the locations comes in from the ‘Hospital Index’ signifying that the best performing Starbucks should not be in heavy hospital and healthcare heavy areas, but in the medium concentration of Hospital Index (0.4 to 0.65). Add this final level of filter, we get the top locations for Starbucks to open premium high-performing cafes as:
Now, the final piece of filtering the locations comes in from the ‘Hospital Index’ signifying that the best performing Starbucks should not be in heavy hospital and healthcare heavy areas, but in the medium concentration of Hospital Index (0.4 to 0.65). Add this final level of filter, we get the top locations for Starbucks to open premium high-performing cafes as:
We see that by interlacing the existing set of cafes, there are 4 Starbucks which fit the bill to be a high-performing premium outlet: The one in Horniman circle, the Shivaji Park outlet, BKC One branch and the Turner road.
No wonder Starbucks chose to go with Horniman circle as one of their first reserves. We would not be surprised if Starbucks plans to go all out and start focusing on the other 3 outlets as well!
Do you want to use Sherlock AI to help you analyze and make data-driven decisions on where to expand to next? Sherlock AI is able to not just map demand-supply, understand what makes an outlet perform better, but it also crunches millions of gigabits of consumer data everyday and can even understand where consumers are coming from, what their preferences are, their spending capacity and other places consumers tend to visit (before / after visiting your showroom). Sherlock AI has delivered great impact to global automotive giants and retail giants alike in terms of recommending where to open up their next showrooms. Leverage the colossal power of AI and make data-driven decisions and save millions of dollars! Schedule a consultation with us
