Folksbay pascal qa_1806


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Folksbay pascal qa_1806

  1. 1. Folksbay.comYOUR PERSONAL SHOPPING NETS DisRaptor TeamStanford Technology Entrepreneurship Class June, 2012
  2. 2. Session 1 Summary1. Start with a limited set of product categories, preferably those with high frequency of purchase2. Think of how to identify those with an intention to buy3. Limit the number of options recommended along the select product4. Identify what are the sources that can be used to come up with top 3 product recs5. What is the minimum viable product? Consider starting from product curation6. How do you get first customers? Why would they come? Who/what will drive them?7. Affiliate commissions are tiny – how many users do we need to break-even?
  3. 3. Product categories to start with● We think of starting from product categories, which promise healthy growth rates while being less exposed to competition: 1. Apparel & accessories 2. Home furnishings 3. Toys and hobby● We still need more than one category - to capture reasonable range of interests and keep some variety
  4. 4. Identify the intention to buy Hypothesis: the users who come from Google search results are more likely to buy than those who come from social networking sites (the two sources seem are top traffic contributors for many sites) Why: in more than half of cases intentional shopping starts from Google search (check..) Implications: use Google ads as a preferred tool to gains conversions (?)
  5. 5. Sources of recommendations Looks like there are not many Product review site Monthly really popular product review sites visitors 3.4M In addition to those which position as “review” sites, we 3.1M found our that digital media (e.g. and the Amazon itself 2.5M are other very important sources of product reviews 1.9M 940K We will also seek whether recommendation sites provide API, so we can use it automatically (at least ratings)
  6. 6. Any idea what’s wrong with  Product curation site  Not many users and decreasing  Still good downstream referral rate, Amazon being top-2 destination after Google, with 12.4% share (Alexa)
  7. 7. Minimum viable product Value proposition: Minimum viable (discuss): Personalized and curated  Personalized and curated product feeds product feeds. +Limited number of product categories Only best-priced offers available  Only best-priced offers available for delivery to your location for delivery to your location Only the most reputable shops  Only the most reputable shops Sharing your likes and purchases  Sharing your likes and purchases with friends with friends Premium membership to earn  Premium membership to earn personal revenue personal revenue
  8. 8. How do we get first customers We are thinking of the way to make our customers try and get curious what was that service that managed to make them a bit happier. That is, first experience, then attribution. We have discussed several ideas, dropped a couple, and left two for further discussion: Seamless Facebook fan acquisition. Facebook already provides customer filtering possibility through its ad platform. It can be well enough to approach narrow groups of customers with offerings they are likely to "Like". Seamless: we create a feed of selected products on our Facebook page, advertise the page with product image, so if a customer likes a product, s/he becomes our fan (need a feasibility check). Once we have fans, we’ll have some customer base to work with and we can target that particular customer sample directly with our value proposition and drive them to our site "Social network" for goods. What if goods "liked" their buyers (and probably other goods, thus creating relationships used for suggestions). So far, we have no idea how to implement this, but the mere fact of goods liking people might draw enough attention to our startup
  9. 9. Tiny affiliate commissions We are working on the revenue model now. A very rough estimate based on 4% revenue sharing (Amazon pays 4-15%) suggests we need to generate $25mn in online sales to cover a $1mn cash cost with affiliate commissions. Is it feasible? We think it is, given that US e-commerce sales amount to almost $200bn Another thing that gives us some comfort is that the affiliate e- commerce model is not something new (we list some of the peers in this presentation) To address the “break-even point” issue, we also need to understand our costs, which is even harder than evaluate revenue potential. So working on the costs too
  10. 10. Additional slides
  11. 11. How it works Matching engine Referral Product trafficCustomer preference aggregation, processing curationPersonal informationFriends information Demographic, social, CJ, SkimLinks, etc.cultural and economic data
  12. 12. Market sizeTop-down approach Bottom-up approach: US 2011 online ad market: $32bn  US comparison shopping  Display ad: 35% cumulative monthly visitors (top-5  Performance-based: 65% sites): 60mn  Retail: 22%  Assuming: Intersection: $1.6bn (5.1% of  It’s only 1/5 of global referral traffic online ad market)  1 click a month per visitor 2014: $2.6bn (c.60% 3y growth)  5% conversion rate for shopping sites Based on 2011 actual data (PwC) and IAB projections  180mn purchases a year  At $20 avg check, it’s $3.6bn revenue  Indirectly supported by estimates of the “affiliate marketing” spending mentioned in the articles ($3-4bn)  Another check: Amazon min commission of 4% times US e- See also Market size update at our commerce sales of $195bn = venture-lab blog: http://venture- $7.8bn 17&data_type=post
  13. 13. Peers – summary$3bn aff market $?? bn ad market /,,,,, ,,,,,,,,,,
  14. 14. Peers – Folksbay modelMainly startups aiming at commercializing Pinterestmodel [unique monthly visitors - 75k] [3k] (micro-affiliate model, startup)
  15. 15. Peers – Comparison shoppingE-commerce aggregators often referred to as “Smartshopping” (they shouldn’t ) and [c.27m] [16m] [8m] (eBay company) [7m] [3m] [2m]
  16. 16. Peers – Bookmarking & SharingHigh concentration, still low competition (pinned stuff) [20m] (fancy stuff) [108k] (rated stuff) [47k] (clipped stuff) [5k] (all stuff) [1k] Others:,, (pivoting),,,