We can do so using building a recommendation engine. The easiest we can do is to show content that is popular with other users, which is still a valid strategy if, for example, the contents are news articles. To be more accurate, we can build a content-based filtering or collaborative filtering. If there’s enough user usage data, we can try collaborative filtering and recommend contents other similar users have consumed. If there isn’t, we can recommend similar items based on the vectorization of items (content-based filtering).
Build a master dataset with local demographic information available for each location. -local income levels
-proximity to traffic
-proximity to other businesses -a reference dataset on local, regional, and national macroeconomic conditions (e.g. unemployment, inflation, prime interest rate, etc.) -Any data on the local franchise owner-operators, to the degree the manager -Identify a set of KPIs acceptable to the management that had requested the analysis concerning the most desirable factors surrounding a franchise. Quarterly operating profit, ROI, EVA, pay-down rate, etc. -Run econometric models to understand the relative significance of each variable -Run machine learning algorithms to predict the performance of each location candidate
-Based on the past pickup location of passengers around the same time of the day, day of the week (month, year), construct a travel map -Based on the number of past pickups -Account for periodicity (seasonal, monthly, weekly, daily, hourly) -Special events (concerts, festivals, etc.) from tweets
The following points were discussed:-
a. Find out the place where people have mostly searched for 5 or 7-star hotels
b. Find the place where the average annual income is high, maybe Bangalore, Pune, Delhi, Hyderabad, etc.
c. Look for that place which is known for tourism as it will attract foreign customers
d. Look for that area which has good facilities around like popular restaurants, pubs, malls, etc.
e. Look for that city where there are all the necessary facilities like airport near the city, railway station, etc. f. Look for that city where you can get good service from third party vendors for basic services like laundry, service employees, security service, etc.