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Goal:
AirBnB mission - help people feel at home anywhere in the world
Fully furnished home can make huge difference to get home feel for a person
Strengths and weaknesses
| Strengths | Weaknesses |
AirBnB |
|
|
Competitors like:
|
| - Only rented by Organization/ Mass scale |
Use Cases:
Marketplace for furniture:
- Renting of furniture for longer or shorter duration
- Can rent electronic items along with the stay - example:- Laptops/Ipads/Kindle/ Speakers
- Can rent musical instruments along with the stay like guitars
- Can rent camping gears like tent, outdoor chairs, etc.
- With work for home becoming norm, longer stay is becoming common and people might want to rent out furniture to make the stay/work comfortable
- Kid friendly furniture or toys can be rent out to family to cater to needs of friendly
- Pet-friendly equipment /furniture can also be let out
Risks:
- Damage or stealing of furniture or equipment
- Local or longer term might not be success as people are currently used to looking for new or far-off places
- People renting it out directly to the airbnb stay travelers instead of reaching via AirBnB sites
- Delivery/pick up hassles need to be managed by suppliers
Success:
- Higher chance of renting for short duration
Recommendation:
- Renting for equipments/furnitures for shoter duration relevant to make stay as comfortable and homely to the users
- Reviews can be used to let out equipment
- if people rent out on sites, they can cater to more users
Clarification - airbnb is designing furniture, ability for people to rent furniture through Airbnb, ability of people to buy furniture through airbnb - answer - ability to rent furniture through Airbnb
Goal - Airbnb supports people in having a space of their dreams so having furniture for that space makes sense, user acquisition is the initial goal is my assumption
User segments (basis opurpose of app usage)- normal app bookers (who book listing), listers (people who list their space in Airbnb), renting companies/retail partners - answer - looking at the ecosystem it makes sense to initially focus on listers as if they can have better furniture in their homes this will lead to better booker experince and also achieve Airbnb mission.
Pain points (use case and how I am prioritizing, points bolded):
1) Which existing furniture to replace - will not priortize as that initially can be a human decision
2) Furniture item recommendation - which furniture item they should rent eg - bed, couch etc - I will prioritize this as users have multiple items list and recommending this will enhance user exp.
3) Within that item type, what to buy - what kind of bed? - I will again prioritize this as it is an extention of above point and also airbnb can help in making that user decision.
4) from where to rent - marketplace, retailers, third party firms, manufactures - will not priortize as this is not an immidiate pain point, they care more about getting different options.
5) Quality and trust - will prioritize this as affects user exp
6) return and exchange - will not prioritize as this is a good to have
Solutions- will be integrating this feature within Airbnb initially
Recommendation of items:
1) use initial survey as customers come to the app, 2) ask users to upload image and use neural netowork to recommend items, 3) use past reviews to see any complaints on furniture, 4) review past image upload to evaluate quality of furniture
Choosing items/enhancing decision to rent -
5) use listing info such as size, layout etc to decide the size of furniture etc, 6) map this listing to other third party data and see what kinds of items will go with this lister and make top 3 recos, add 7) save feature to review items later, 8) allow lister to create collection to increase decision conversion
Quality
9) threhsold on image quality, 10) 360 video, 11) badge program to show trusted renters, 12) past customer testimonials.
Solution Priority - basis impact and effort and user goal - choose 1, 3, 6, 7, 10, 12
Tradeoff - users might not fill survey that may affect engagement and hence churn, using third party data might be tricky
Metrics - # of rentals/user/week, %of items searched outside the ones recommended, % of users that made atleast one rental.
Northstar - # of active user per week
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