Is Swoopo a Legit Auction site?

Why hasn't any bidding-fee reverse auction / penny auction site been able to scale up like other e-commerce sites? (such as Dubli / Swoopo / Quibids / Madbid)

• There are no $100-$200mn topline players in this space, even though companies are present in multiple markets (eg. Dubli operates in 70 countries).

• Answer:

  The Core what you are looking for can be found: Critical Success Factors There are many factors that relate to the competitors in this space realizing the variables factored into the above projections.  One of the most notable factors will be if the US government decides to regulate this industry as gambling.  However, considering the self policing track record of the competitors in this space, this is less of a concern in terms of the long term execution strategy.  Competitive Advantage - All of the competitors in this industry sell basically the same items and there is little to lock in customers.  If a user can win more for less bids, then obviously, they are going to switch.  Historically for one market participant, 22% of the bidders comprised nearly 77% of ALL the bids placed.  Since they are bidding for physicial goods - how many Apple iPads do you need? Product Mix - The monthly comparative metrics for performance show huge deviation in the trends for Revenue per Auction, Profit per Auction, Bids per Auction, and Unique Bidders per Auction.  Market particiapnts are searching for their right compositions of available items, but they need to figure out how to evolve beyond the Apple iPad. Cohort-Leverage - There is an incredible market opportunity for leveraging the social-graphs of the users.  The ability for Matt to bid against his friend, Tom, for an Apple iPhone creates a fun competition.  Let’s say that Matt won the auction for an Apple iPhone.  This means that everytime Matt calls Tom from the phone or they are hanging out, Matt has a physical trophy that he beat Tom and is implicitly better than him.  The competition will compel Tom to hit another auction and spend more moneyIntroduction & Overview As the internet becomes a more pervasive aspect of lives for consumer, inherently the amount of money consumers allocate to online purchases will increase.  In 2009, online retail sales were up 11 percent, compared to 2.5 percent for all retail sales according to Forrester Research.  The increase in e-commerce spending reflects three main trends: More people spending more time online = Increased experience & trust with the electronic commerce medium:  The assimilation of the internet by US consumers as an established tool for accessing information and entertainment will continue to fuel the “trust” factor for purchasing online.  As consumers spend more time online and increase their experience with it as a commerce medium, they will inherently purchase more goods and services online. The Great Recession forced consumers to get smarter:  The internet provides a flat communication vehicle for delivering information to consumers about the best available price.  The Great Recession did not systemically change the consumer-discretionary addiction that can characterize the consumption patterns for the past 30 years.  The Great Recession forced the consumer to cut-back purchases and get “smarter” about how they employ their available dollars.  Getting smarter means that the consumer needs to get more information and the distributed nature of the internet means it is “THE” means to gain perfect information on the best available price Economic Recovery = Cash & Increased Consumer Credit:  As the economy regains jobs and returns to growth, lending institutions will, albeit at a snails pace, relax the vice-grip on consumer credit that has been in place for the last 2 years.  This means that consumers will increasingly have the means to execute online transactions via the established medium of credit/debit cards. Forrester Research recently released their 5-year forecast for US Online Retail Spending that illustrates a 9.9% CAGR.  Figure 1 illustrates Forrester’s estimate for online retail spending for 2011 through 2014: What is the Pay-Bid Auction Market Business Model Over the past 10 years, the online auction market has been dominated by essentially one player, Ebay, employing a classic auction model.  This classic model is where a good is placed up for auction in a marketplace and bidders have the ability to place bids that progressively increment the value of the good up to the level that represents the each bidder’s maximum economic value for the good.  The bidder in the marketplace that has the highest maximum economic value for the good wins the auction.  For facilitating this exchange, the marketplace, Ebay, takes a percentage of the final price.  This model is great and has worked well for Ebay.  However, there are two trends that serve as the foundation for the genesis of the Pay-Bid Market: All of the Action Takes Place Right at the End:  If you have ever participated in an online auction, you have most likely experienced a flurry of activity on the auction in which you were participating during the last several minutes prior to the auction expiring.  This is an exciting period that can compel the bidder to react emotionally and increase their maximum economic value for the good in order to secure it.  The Pay-Bid Market replicates this excitement at it’s very core. A Large Market of Un-sourced Revenue:  The potential to purchase a good below the prevailing market rate represents a clear value proposition for the bidders.  In the classical model, the revenue model for the marketplace provider benefited by virtue of millions of participants in the marketplace (more people = more bidders = greater variety of subjective value = more revenue).  However, the participants did not have to compensate the marketplace for this value proposition.  In a similar manner to Costco, where Costco members pay a fee for access to the bulk-buying discounts at Costco stores, the Pay-Bid market enacts a transaction fee for bidders to have access to these deals and charges them for placing the bidding. The Pay-Bid Auction Market is a business model generates it’s revenue from the bidders compensating the company for the value proposition of purchasing a good at a huge discount.  Here is an example of the business model: Company A is a Pay-Bid Auction marketplace that places an Apple iPad up for auction for $0.00 with a bid increment of $0.01 and a time limit of 1hr Participants in the marketplace (the bidders), purchase Bid Tokens from Company A for a set fee per token (most of the time this is about $0.75). Bidder A uses one of the previously purchased bid tokens to increase the auction’s price by $0.01. Every time a bid is placed, the auction’s time limit extends by a fixed number of seconds to provide other bidders with the ability to respond and react to new pricing information in the marketplace. Should the time limit expire, Bidder A secures the auction for the accrued value of bids - meaning if 1 bid was placed the value of the auction has incremented 1 time and costs the bidder $0.01. In many of the auctions this process of bidding occurs thousands of times generating HUGE revenues for Company A in the process.The Revenue Model The Pay-Bid market generates revenue from 3 sources: 1.  Bid Packs:  Bidders in the marketplace pay the bid-fee upfront to the Company A.  Meaning that a bidder must first purchase packs (generally in quantities of 30, 50, 100, 200, 300, 500).  This creates a negative working capital situation for the marketplace by virtue of Company realizing the revenue of 30 bids when the bid-pack is purchased prior to the bidder exercising the value of the purchase - Getting the $$ upfront 2.  Final Cost:  Each time a bid is employed to increment and extend the auction, when the auction expires the winner pays for the good.  Meaning if the auction price for that iPad increased to $20.00, the final winner will pay Company A $20.00. 3.  Shipping Costs:  about 75% of the auctions that occur are for physical goods that require transportation to the customer.  This cost is illustrated prior to the start of the auction for a fixed amount.  For a Pay-Bid company in San Francisco, CA it costs a lot less to ship the iPad to Los Angeles (probably $5.00) than to a customer in New York (probably $16.00).  However, Company A earns the revenue for the shipping costs regardless of the geographic location of the winner. Industry-Segment Analysis - Pay-bid Market The pay-bid market is highly undeveloped as the majority of the firms have been operating in the United States for less than a year.  There has been an explosion of new players in the market, all of whom are desperately searching for their niche and securing their customer base.  As this is a fledgling industry with almost ZERO information regarding the dollar value of this industry, as such, we are limited in clearly illustrating the magnitude of this market segment.  However, the traffic of visitors serves as a means to illustrate the growth of the industry.  By sourcing the visitors compiled by Compete, an industry-leading third party website traffic aggregator, there is a constant information resource to generate an idea of the traffic flowing to websites that comprise this industry.  Figure 2 illustrates the monthly visitors for the Pay-Bid Auction Market. For purposes of compiling the aggregate industry, the marketplace is compiled of the following participants monthly visitors provided by Compete: Assumption:  The total traffic of the 16 companies that we collected traffic information on was projected to comprise 85% of the marketplace.  There has been an explosion of new competitors in the marketplace with a very high churn rate.  In effort to hold the marketplace variable constant over time, the composition of all of these players was assummed to be 85% of the total traffic to Pay-Bid Auction sites. Historical Analysis & Metrics In effort to gain deep market understanding about the driving factors for growth moving forward, we first must acutely understand the historical evolution of this budding industry.  There are three academic pieces of work that provided the majority of the information for the historical build.  The key facts of the analysis are summarized below: Every month was reviewed by hand to discover the qualitative factors that is often left out of the analysis.  Each company was broken out by Company and Month whereby the statistics for each auction were summed into groups based on the unique item.  In order to estimate revenue, the following statistics were calculated for the total of each unique item. In the historical analysis section, the data collection methodology was discussed to provide context for gathering 43 monthly data points of company-specific auction & bid information.  Initially, the methodology for calculating the market value was as follows: 1.  Estimate the # of Bids per month # of Auctions - Each unique item (i.e. 32 auctions for a 13” Macbook Pro laptop held by Swoopo from January 1, 2010 - January 31, 2010) was totaled into a unique row. Average # of Bids per Auction - the weighted average of each auction for the given period for the unique item category. Bid Increment - This was the critical piece as as the value by which each auction increments when a bid is placed drastically can change the # of bids that are projected into the aggregate.  For example, if an iPad sells for $34.00 and the average increment was $0.01, then the following would occur: $34.00 / $0.01 = 3400 X $0.75 yields bid revenue of $2,550.00 However, if this was estimated to be a $0.05, we have completely underestimated the projection.  This informs the reason that each auction was reviewed manually for a “Does this make sense” analysis.  One of the best tools for forecasting is a simple analysis of is this logical, which involves spending the time to play around with the numbers.  In addition, this process has powerful implications for employing the Delphi adjustments. 2.  Revenue Build Bid Revenue - The number of bids for each month multiplied by the cost for each bid (weighted out where discounts were applied). Product Revenue - The total of the bids multiplied by the # the bid increment value.  For example, if there were 1,000 bids in a given month and each bid incremented the auction by $0.05, then the Product Revenue would be $50.00 = 1,000 bids multiplied by $0.05. Shipping Revenue - Whenever a pay-bid auction contains a physicial item, such as an Apple iPad, the item must be shipped to the customer.  These companies charge the auction-winner for this shipping.  The shipping costs were fairly consistent across product categories were computed as a weighted average of the type of the auctions as they compromise the aggregate for each month. 3.  Market Composition - All sites were compared to the Visitor level traffic statistics as aggregated by Compete Inc.  This information formed the baseline to serve as a formative means of comparing unlike auction providers. Visitors - The Unique Visitors metric only counts a person once no matter how many times they visit a site in a given month. Unique Visitors are typically used to determine how popular a site is.  The weakness of this methodology is that many of these people may leave the site immediately. However, this is the only data that was available to serve as a representative comparative measure. Market Share  - The total number of visitors as logged by Compete divided by the total of the sample extrapolated into the whole. 4.  Revenue per Visitor & Extrapolation - computing the market value by unitizng the value of each visitor and then computing that into the whole. Swoopo (Mar ‘09 - May ‘09) Swoopo was one of the first companies to employ the pay-bid auction model in the United States.  As such, they were the market leader until major competition began emerging in the marketplace in late-’09.  Swoopo began operating in the United States in October ‘08 and the initial period for analysis was Mar ‘09 through May ‘09.  This period was chosen as it represents the time period where the service began gaining traction and offered the company 4 months to tweak the service offering - meaning that it was the strongest opportunity to analyze the foundations of the market’s behavior. Figure 3 illustrates the number of visitors and market share for http://Swoopo.com Swoopo (Mar ‘10 - May ‘10) The Mar ’09 to Mar ’10 timeline for Swoopo is incredible.  Swoopo went from championing a new industry in the United States to losing nearly 75% of their monthly traffic volume.  Basically the world looks very different for Swoopo. http://BigDeal.com Comparables Analysis & Metrics The Pay-Bid market is a new industry that is very immature and the limited timeline of available data points did not offer a substantive base for forecasting this into the future.  Flash Sales immediately jumped out as a perfect comparable industry due to the young, highly monetizable, and recent popularity of the companies in the industry.  Flash sales is a phenomemum of social commerce (group buying) that has charged into the world stage through the market leaders such as Groupon & Gilt Groupe. Most notably, the first and most prominent aspect that jumped out, when comparing Pay-Bid to Flash Sales, was that the visitor & revenue model just “looked right”.  Simply put, when you looked at the traffic patterns for the Flash Sales companies such as Groupon & Gilt Groupe, the industry visually looked as though they were related.  The important factor that Flash Sales appeared to be about 12-months ahead of Pay-Bid - Perfect. This is a logical qualitative analysis as their business appeals to a much wider demographic and requires absolutely no learning curve.  In addition, there were several qualitative factors that quickly pushed Flash Sales as the most directly related industry for the following reasons: Transformative business models:  The Flash Sales market and the Pay-Bid auction market are heralded for monetizing new revenue sources in new manners. The Time Crunch Deal:  Time is of the essence that compels people to make emotional purchasing decisions and leads to more $/customer.  The countdown of the deal. Inherently Social for Commerce Purposes:  The nature of the marketplace revolves around bragging and in turn marketing the service.  For example, if I picked up a killer deal on http://Gilt.com a member of the Flash Sales market, I could easily post the item and the discount that I received on my social network.  Thereby marketing the service to my social network and communicating my influence to the social network.  In the same manner the incredible deals compel people to post to their networks that they purchased an Apple iPad from the following site for a 99% discount.  Highly Correlated Growth Curves:  The qualitative factors are manifested in how the growth rates correlate or the data points between two sources is related to the trends that are occurring in either source. Huge influx of New Competition:  Low transaction Costs mean that people can switch freely & they do.  The deal is all that matters and the customer knows that - once you have a lot of big fish winning the auctions, they go play in a smaller/newer pond. Market-Value Forecast The historical information was gathered and there was a dataset to serve as a base for forecasting where the industry was going.  The foundation of the forecast revolves around the growth of the # of visitors that market receives.  The forecasted value is a combination of the visitor traffic patterns that were studied and correlated to the patterns for Flash-Sales. Figure 3 - Growth Rate for the Pay-Bid Auction Market To frame this properly, we need to make some market comparisons for why we believe this is going to grow in the same manner.  Appendix Swoopo Vs. http://BigDeal.com Traffic Analysis Swoopo Demographics http://BigDeal.com Demographics