Symptom: Travellers prefer Uber as mode of transportation while going to airport but prefer other modes of transport while leaving airport.
Objective: Increase number of passengers taking Uber at airport while keeping total revenue constant.
Customer: Airplane travellers can be broadly segregated into two categories:
- Business Travellers: Working professionals or business owners who travel for business purposes. They generally leave early in the morning from home or in evening after office. Their expenses are generally covered by company and are less price sensitive. They prefer comfort and time over cost.
- Leisure Travellers: People travelling to visit homes, meet friends, holiday trips etc. They have flights booked for noon or after office. Since they pay for their Uber, they are price sensitive and can prefer to other modes of transportation. They prefer cost over comfort and time.
Since leisure travellers are less likely to book Uber, I will concentrate on them for this particular problem.
Uber to Airport:
Customer Persona: Medium Income traveller, travelling with partner to visit his friends or family or vacation. Happy mood because of vacation. Lives in big cities. Flight booked after office with return flight on Sunday night.
What:- Books Uber for airport because he doesn't want to miss flight.
Why:- Prefers Comfort and time over cost.
How: Compares Uber time with other modes. Compares Uber price with other modes. Select Uber over others.
Customer perception of Uber is comfortable and quick ride to airport so that he doesn't miss his flight.
Uber from Airport:
Customer Persona: Medium Income traveller, returning with partner from visit his friends or family or vacation. Happy mood because of vacation. Lives in big cities. Reaches airport in evening.
What:- Books other means of transport.
Why:- Prefers Cost over comfort and time.
How: Compares Uber time with other modes. Compares Uber price with other modes. Select others over Uber.
Customer perception of Uber is costly ride.
Symptom Analysis: Same customer perceives Uber differently at different point of time. Customer who preferred comfort and time over cost now prefers cost over value prop of Uber.
- Prices are indeed higher for his journey from Airport to home then from his journey from home to airport. (Most Likely)
- Customer doesn't value Uber's value proposition which is comfort and quick journey. (Maybe)
- Customer has other alternative modes of transportation which weren't available when he booked Uber to airport. (Least Likely)
For the sake of simplicity, I will target first reason which is Uber prices are higher "at airport" then "to airport".
Suppose two flights will arrive and depart at same time. For departure, travellers start reaching airport 3 hrs before flight time. Suppose for a flight of 200 passengers and all reaching airport by Uber, 33 pasengers reach airport every 30 mins. They come from all places. Suppose 33 pasengers ahve arrived in first 30 mins in 20 cabs. Now next flight to arrive is 2.5 hrs away. so either those 20 drivers can wait for three hrs or take other trips. Suppose 10% wait while 90% leave. This phenomenon continues with percentage of waiting drivers increasing every 30 mins.
By the time all 200 passengers have reached airport, 120 cabs were utilized. Out of them 70 stayed till next flight arrival.
|Nos of Cabs Arrived per 30 mins||20||20||20||20||20||20|
|Percent Stayed back at Airport||10%||30%||50%||70%||90%||100%|
|Nos of cabs stayed at airport||2||6||10||14||18||20|
Earlier we had 120 cabs to bring 200 customers to airport, now we have 70 cabs available for 200 customers arriving in next flight. Cabs per customer ratio decreases from 0.6(120/200) to 0.35(70/200). This leads to scarcity of cabs and Uber algorithm will increase prices. If all things remain constant then 116(70/0.6) customers with 70 available cabs will have same ratio of 0.6. Hence, rest of the 84 customers will move to other modes of transport.
Problem Description: There are fewer cabs available at airport, hence leading to surge pricing and reduced number of pickups.
- Increase number of cabs when flight lands while maximising revenue in demand supply curve.
- Determine number of passengers arriving beforehand.
- Determine number of cabs needed to cater those passengers.
- Notify nearest cabs to arrive at airport for probable pickups.
- Notify cabs,which arrived earlier, to stay at airport for future pickups.
- Delay pasengers by offering them better deals so that they can wait until rush hour normalizes.
- Display probable price for next 1 hr.
- Provide coupons for lounge
- Offer alternative mode of transport to cater high pasenger volume.
- Integrate with Bus/train and other ride sharing apps.
- Integrate with local taxis.
- Improve ride sharing to increase fill rate.
Factors to consider while prioritising solutions:
- Value to passenger/driver/company.
- Resource investment
- Time investment
| ||Increase number of cabs||Delay pasengers||Offer alternative mode of transport||Improve ride sharing|
|Value to passenger/driver/company||H||L||M||L|
Prioritized Solution: Increase number of Cabs.
- Determine passengers: Integrate with Google Maps, Airline API.
- Determine passenger: Single/Multiple, Bags, Probable Destination, Previous history.
- Determine Number of cabs needed.
- Notify drivers
- Determine driver willingness
- Determine demand/supply curve.
- Determine flight landing.
- Notify passenger of cab availability
- Business Metrics: Number of Users, Revenue/Trip
- Product Metrics: Fill Rate
- Anciliary Metrics: Number of Cabs, NPS, Customer Exp.