Gift Hero: Using the Wisdom of the Crowd to Gift Smarter

Choosing the right presents can feel like a challenge at times. Christmas and birthdays are the perfect opportunity to spoil your friends and family and show you care. At the same time though, if you are not confident about choosing the right present, it can feel pressured and difficult. Around Christmas, economist will inevitably talk about the deadweight loss of Christmas gift giving, a theory by economist Joel Waldfogel. Deadweight loss occurs because of the mismatch between what a gift giver thinks a receiver wants and what the receiver actually wants. Expanding this concept to the whole economy, Waldfogel found the gift giving deadweight loss is 10 percent. Given that Americans are expected to spend about $600 billion on holiday gifts each year that would put the amount of deadweight loss at $60 billion. What are the proposed solutions for reducing this loss? Cold hard cash in an envelope. But, that solution feels too practical and lacking in holiday spirit. Fear not, it is possible to turn into a present buying extraordinaire; you just need to use Gift Hero.

Gift Hero is the service you can turn to when you need a personalized gift recommendation. Rather than using Amazon, which will recommend the same gifts everyone else is giving, Gift Hero matches gifters with expert gift recommenders. Not sure what kind of earrings to get your girlfriend who is into owls? Not that knowledgeable on earrings or what constitutes a cute vs. ugly owl? Get recommendations from someone with your girlfriend’s tastes so you don’t pick the set that is “too owly.” Gifters post the occasion, their budget, and the interests of the person receiving the gift.

 

Potential recommenders can review a list of these events, find events that match their profile, and suggest a personalized gift idea. The gifter can review the suggestions, rate the quality of the suggestion, and approve or reject the gift.

If their idea is used, recommenders get paid, with the rating system in place to identify and remove bad recommenders. Gift hero takes the stress out of choosing gifts by finding the perfect person to recommend the perfect gift.

To demonstrate the effectiveness of our product, we will run a trial with a group of 200 gifters and recipients.  We will attempt to create a varied and balanced sample of participants, representing a range of ages, budgets, and tastes.  We will then randomly assign participants to either the control group or the “Hero” group.  The control group will be asked to pick a gift for their recipient using whatever methods they would normally choose.  The Hero group, however, will be given the GiftHero product to aid in their gift selection.  We will survey both the recipients and the gifters about their experience.  We will measure 1) the percentage of those in the Hero group who chose to gift a product recommended by the product; 2) the difference between gift satisfaction rating of recipients in the Hero and control group; 3) the difference in amount of time taken to select a gift between the Hero and control group, and 4) the reported willingness to pay for the product among gifters in the Hero group.  We are confident that our product will demonstrate value along all of these dimensions.

Over time, we expect that the recommenders will organically increase and the reviews will self-select the best. We believe that there is a lot of value is created and hence extractable. Successful recommenders can be paid per recommendation with a commission being paid to Gift Hero. Further, similar to Amazon Prime, a subscription can be paid to be part of the Gift Hero members list. Further, we believe another channel of revenue is through affiliate marketing. Clearly, it is a natural extension to the business to direct consumers to e-commerce website and obtain the affiliate fee. Finally, we believe that the data that Gift Hero is extremely valuable. This can be monetized through contextual marketing as well as recommendation analytics. The overall revenue potentially runs into at least a billion dollars within the United States.

 

Team Codebusters