(Image source: freepik)
by Alex Ho
相關筆記
參考資料
- 參考資料
- Intro
- 1-sided Networks vs 2-sided Networks
- 1-sided Networks
- 2-sided Networks
- Liquidity
- Density
- Category Supply Density
- Commoditized Supply (e.g. Uber)
- Supply Side 競爭激烈
- Multi-Tenanting (demand 和 supply side 同時使用多個平台)
- Differentiated Supply (e.g. AirBnB)
- Geography Supply Density - Hyperlocal Network vs Cross-Border Network
- Latent Demand 潛在需求
- Hyperlocal Network (e.g. Uber)
- Example: Uber
- Cross-Border Network (e.g. AirBnb, Convoy)
- Example: AirBnb
- Example: Convoy
- Regional Network Effects
- Example: Numbers
- 其他範例 (e.g. Preply)
- 用 Liquidity 區分不同特性的 Platform
- Tier 1:
- Tier 2A: Commoditized supply & Cross-border network effects
- Tier 2B: Differentiated Supply & Hyperlocal Network Effects
- Tier 3:
- 增加 Liquidity 的方式 (e.g. Side-Switching)
- <1> “Come for the tool, stay for the network” approach
- <2> Marketplace “Side Switching”
- 2022 largest consumer-facing marketplace startups and private companies (selected by A16z)
Disclaimer
- 此文件只是我的個人筆記,不保證正確性
歡迎找我討論 Web 3、data products、product strategy
Intro
- Network Effect (網絡效應) 常見於 通訊 及 互聯網等行業
- 產品及服務價值會隨着客戶增加而提升,當客戶人數到達臨界點後,網絡規模將以幾何級數上升,形成對手難以踰越的競爭優勢
1-sided Networks vs 2-sided Networks
1-sided Networks
- Same users play 2 different roles in the same network
- E.g. Facebook
- A user can be either demand (content consumption) or supply (content creation)
- So it is easier for 1-sided Networks to hit “critical mass”
2-sided Networks
- Users can only either be on the demand or supply side (but not both) in the same network
- 相較於 1-sided network,2-sided network 比較難達成,因為
- If there is too much demand (supply 不夠)
- Unfilled requests and customer churn
- If there is too much supply (demand 不夠)
- Underutilized capacity and supplier churn
Liquidity
- Liquidity refers to how effectively a network or marketplace matches demand and supply
Density
- Supply Density (within a region or a category) = (Match-able supply) / (demand),
- Network Density = (# of actual connections between users) / (# of users)
Category Supply Density
Commoditized Supply (e.g. Uber)
- Uber/Grab 用戶不會太過在乎司機的車子是什麼品牌的 (users are not sensitive to the vehicle brands or the driver’s identity) ,因為只要能即時找到司機就好了,他們最在乎 “the amount of time it takes them to get a ride”
- 這叫做 commoditized supply (compared to “differentiated supply”)
- a.k.a interchangeable supply
- 整個 Uber/Grab 的 “car-hailing service category” 只有少數幾種而已
- 缺點:this makes them more vulnerable to multi-tenanting and competition
- 優點:較容易取得大量 supply (across just a handful of categories)
Supply Side 競爭激烈
- 在 Uber 上線初期,只要能快速增加司機 (supply),用戶 (demand) 的等車時間就能大幅度降低
- 但當等待時間低到一定程度 (e.g. 5分鐘) 之後,增加更多司機數量 無法大幅度降低用戶等車時間 和 乘車體驗
- 此時 Uber 的競爭者 (e.g. Grab) 不需要力求找到相同數量的司機,只要想辦法讓等待時間和 Uber 差不多即可。
- 他們可能給予 “Uber 司機” 大量補貼,吸引他們改為自己的平台 (e.g. Grab) 接單
Multi-Tenanting (demand 和 supply side 同時使用多個平台)
- 正因為 commoditized supply,競爭者能輕易提供相似的服務,用戶跳槽的成本很低 (low transition cost)
- 若另一家公司的價格差不多、或是有提供優惠,且很快就有車過來我的上車位置,用戶就跳槽改用別的平台了
- Uber 司機也很可能同時開通不同叫車公司帳號(Uber/Grab)
參考資料
Differentiated Supply (e.g. AirBnB)
- AirBnb 用戶在找房時,會在意房子是小套房 or 四人房 or 獨棟別墅 or 日本風格 or 海邊度假別墅 or 有附廚房 or 有停車位 ...etc
- 這叫做 differentiated supply (compared to “commoditized supply”)
- 這導致
- AirBnb 較難 gain critical mass (相較於 Uber)
- 但也讓 AirBnb become more defensible,新來的競爭者很難在短時間內在多種 niche categories 都取得夠多的房源
參考資料:
Geography Supply Density - Hyperlocal Network vs Cross-Border Network
參考資料:
Latent Demand 潛在需求
Supply Density by geography
- Hyperlocal Network Effects
- Cross-Border Network Effects
Hyperlocal Network (e.g. Uber)
Example: Uber
- Demand vs Supply
- Demand: 想要叫車的用戶
- Supply: 有車的司機,開車載人
- 超級本地化
- 在某個地區 (within a small geographic radius) 需要有 司機driver (supply) ,滿足 rider 需求 ( demand)
- 某個小區域之中的司機數量不夠的話,Rider 等待時間變長的話,就會對此平台不滿意
- Uber needs to maintain a specific supply to demand ratio, within the radius of a few miles, in order to hit that targeted wait time.
- Uber/Grab/Foodpanda 進軍到新城市時,都需要重做一次 driver acquisition
- 如果在這城市司機數量不夠,就不能吸引消費者使用 Uber App 轎車
- “cold start” problem
- they had to re-invest in driver acquisition without the benefit of any latent demand. They had no drivers and so did not have riders to attract them organically
- 較晚進入某市場的公司,很難打敗早進市場者
- These dynamics pressure unit economics and increase the amount of capital required to address a given market. This frequently results in investors overestimating the addressable market that be targeted sustainably (see: SoftBank Vision Fund).
- Since unit economics are less scalable, the valuation-to-funding multiple for hyperlocal marketplaces tends to be low. And consequently, this is why many local marketplaces tend to be fragmented by geography (from C2C commerce marketplaces like Shpock or Letgo to food delivery services like DoorDash or Deliveroo).
Cross-Border Network (e.g. AirBnb, Convoy)
Both Airbnb and Convoy are examples of network effects without any boundaries
Example: AirBnb
- Demand vs Supply
- Demand / 用戶:想要到外地城市訂房短住的人
- Supply:在某城市擁有房地產的人,把房子放到 AirBnb 讓人短租
- The Addition of a unit of supply (a host) makes the product more valuable for the demand side (guests) across geographic boundaries.
- E.g. 在紐約的 AirBnb 房源不只能滿足住在紐約的用戶,還能滿足到紐約出差/旅遊的外地人
- Guests judge Airbnb’s product experience by their ability to find a high-quality property at a destination of their choice. However, the exact location of that property is rarely an overarching constraint. Airbnb still needs to maintain a specific supply to demand ratio within a destination to achieve liquidity, but that can be spread across a larger geographic area
- 當 AirBnB 拓展到新的城市,
- AirBnb 比較沒有 “cold start” 的困難 (相較於 Uber)
- Existing AirBnb users 早就會在全世界各地訂房,不需要被教育,他們多了一個城市作為旅遊選項,AirBnb 為這些用戶擴大了 Latent Demand (潛在需求)。
- 這會幫助吸引該城市的房地產屋主提高意願把房子放到 AirBnb 去租賃
- So once Airbnb began to scale their demand and supply sides, they faced very little competition from other, regional startups who had limited supply in other regions.
- This made Airbnb’s unit economics immensely scalable, lowered capital requirements and resulted in a high valuation-to-funding multiple.
(as of 2020)
- As a result, Airbnb is heading towards an IPO with largely healthy unit economics while Uber is still at least a year away from profitability (and sustainability remains an open question).
Example: Convoy
- Demand vs Supply
- Demand: 寄送包裹到跨國城市的 shipper
- Supply: 在美國開卡車把包裹從機場送到 收件地址 的司機 (trucker)
- Adding a unit of supply (a trucker) in New York makes the product more valuable for any shipper across the globe who wants to ship to the Northeastern part of the United States
- And when Convoy expands to other countries, it can leverage untapped, latent demand from shippers to attract new truckers.
- Existing Convoy customers like Unilever can book truckers in the new market, which will organically attract local truckers.
Regional Network Effects
Both Airbnb and Convoy are examples of network effects without any boundaries, but not all cross-border network effects need to be truly global. Some markets could be naturally constrained by factors like regulations, cultural preferences, etc. and exhibit “regional network effects”.
Example: Numbers
- Demand vs Supply
- Demand: 終端消費者
- Supply: 金融服務 供應商
- As Numbrs expands to other countries (e.g. the UK), it will need to attract new suppliers because of regulatory and licensing requirements for financial services firms without the benefit of latent demand in the new market.
- However, adding a new unit of supply here (a financial product) will help attract users anywhere in the UK (the entire market bound by the new regulatory framework), and not just a small portion of it.
- Scaling these marketplaces is far more efficient as compared to those with hyperlocal network effects, but less efficient when compared with truly global marketplaces.
- So as Numbrs expands to other geographies, we should expect its valuation-to-funding multiple to decline but still be well ahead of hyperlocal marketplaces.
其他範例 (e.g. Preply)
Preply are purely online and don’t have any geographic constraints whatsoever.
用 Liquidity 區分不同特性的 Platform
Notes
- It is evident that marketplace liquidity is deeply dependent on the unique characteristics of each marketplace. What makes marketplaces defensible and scalable also has a direct impact on how easy or difficult it is to reach critical mass.
- The traits that make marketplaces scalable and defensible also affect the ease of reaching critical mass
考慮以下維度
- Differentiated Supply vs Commoditized Supply
- Geography impact: Hyperlocal vs Cross-Border
- Liquidity Resistant vs Liquidity Inclined
Tier 1:
- 優點:
- 較容易國際擴張
- 較難被競爭者取代
- 通常有最高的 valuation-to-funding multiple
- AnrBnb: 9-10x
- Numbers: 13x
- Poshmark: 8x
Tier 2A: Commoditized supply & Cross-border network effects
- 優點:最容易建立 liquidity
- 缺點:新的競爭者也容易 scale up
Tier 2B: Differentiated Supply & Hyperlocal Network Effects
- 缺點:最難建立 liquidity
- it is nearly impossible to reach critical mass without relying on other advantages.
Tier-2B marketplaces have two options to achieve liquidity.
- Come for the tool, Stay for the network
- Side-Switching
Tier 2A、Tier 2B 的 “valuation-to-funding multiple” 通常比 Tier 1 更低
- Convoy, Flexport, and OfferUp all have a valuation-to-funding multiple between 3–5x.
Tier 3:
- This category mostly includes hyperlocal, service-oriented (and delivery oriented) marketplaces like Uber, Deliveroo and Wag.
- These startups tend to create the least amount of value for every dollar invested
- Their capital intensive nature combined with low defensibility means that they are only viable in a handful of product segments with very high frequency of use, e.g. ridesharing and food delivery. Of course, some of them are likely to be more viable without high-risk venture funding.
增加 Liquidity 的方式 (e.g. Side-Switching)
<1> “Come for the tool, stay for the network” approach
- In this case, marketplaces can leverage “single-player” software to bootstrap the supply side of the marketplace.
- Creating a SaaS product first allows prospective marketplaces to control and grow their geographic supply density until critical mass is reached before opening the marketplace to the demand side.
- E.g. OpenTable
- They first launched a reservation system for restaurants to manage their own bookings.
- Once they gained sufficient regional density of restaurants, they opened up their restaurant reservation marketplace for consumers. As a result, they already had liquidity when it was made available for consumers.
<2> Marketplace “Side Switching”
- Side switching occurs when marketplace participants do not have fixed roles,
- E.g. a Shopee buyer can become a seller
- E.g. Facebook user can create and consume content
- the number of participants required to attain critical mass reduces significantly. This reduces the complexity of reaching critical mass across both geographies and categories.
- E.g. Shopee
- Shopee 從 C2C 開始做,用戶可以是買家也可以是小賣家
- 然後 Shopee 發展 Shopee Mall,引入 大品牌 (只會是賣家,不會是買家) (leverage the existing base of users to bring in more valuable network participants with fixed roles)
- 原本只賣實體商品,後來增加賣虛擬商品:手機話費充值、繳帳單、買餐廳餐券....etc
- Side switching is not exclusive to Tier-2B marketplaces and can occur in any tier as well.
- For example, even Airbnb (Tier-1) and Uber (Tier-3) exhibit side switching — riders can become drivers and guests can become hosts.
- This does help liquidity, but only marginally because the rate of side-switching is low, i.e. a very small percentage of the demand side become suppliers.
- In order to maximize the liquidity advantage from side switching, marketplaces need users to switch back and forth from the demand to the supply side frequently, almost on par with social networks.
- To really take advantage of this, it is not enough to merely present side-switching as an option for your users. Rather, marketplace startups need to embed side-switching as a core part of their value proposition. Poshmark is a great example of a Tier-1 marketplace built on side switching.
2022 largest consumer-facing marketplace startups and private companies (selected by A16z)
About me
- Software Product Manager in tech.
- 10 years of experience as software product manager in these areas: #ecommerce #SaaS #SoutheastAsia #delivery #MarTech #SuperApp
- Work experiences in Taipei, Singapore, and Shanghai.
- Currently based in Taipei City, Taiwan.
- My Linkedin profile: Alex Ho
Notes & Articles
產品經理、思維策略
經濟、投資
產業筆記
其他
電影筆記
旅行
旅行遊記
旅行建議、推薦景點
台灣
日本
東南亞
歐洲
中國
攝影