Selecting the right business model for your business is crucial. In this post I intend to build on some of the work of Fred Wilson and others in the exploration of web and mobile revenue models. I propose there are two major classes to revenue models: trade methods and trade objects. A trade method would be for example, “licensing”, whereas, a trade object would be the “data”. Here is a fairly exhaustive list, extended from the original collaboration on hackpad. It is fairly interesting to be aware of all the possible combinations of trade methods and objects as it can help predict new startups or guide your own business model choice.

Advertising

• Normal ads
• Display Ads - e.g. Yahoo!
• Search Ads - e.g. Google
• Text Ads - e.g. Google
• Video Ads - e.g. Hulu
• Audio Ads - e.g. Pandora
• Paid content links - e.g. Outbrain
• Email Ads - as done by Yahoo, MSN
• Classifieds - e.g. Craiglist
• Featured listings - e.g.  Yelp, Super Pages;
• Recruitment Ads - e.g. LinkedIn
• Promoted Content - e.g. Twitter, Tumblr
• Lead Generation - e.g. MoneySuperMarket, ZocDoc
• Affiliate Fees - e.g. Amazon Affiliate Program
• Ad Retargeting - e.g. Criteo/perfectaudience
• Real-time Intent Ad Delivery
• Location-based offers - ex/ Foursquare
• Sponsorships / Site Takeovers -  e.g. Pandora

Commerce

• Retailing - e.g. Zappos
• Marketplace - e.g. Etsy
• Crowdsourced Marketplace - e.g. Threadless
• Excess Capacity Markets - Uber, AirBnB
• Vertically Integrated Commerce - e.g. Warby Parker
• Aggregator - e.g. Lastminute.com
• Flash Sales:  Gilt Groupe, Vente Privee
• Group buying - e.g. Groupon
• Digital goods / downloads - e.g. iTunes
• Virtual goods - e.g. Zynga
• Training - e.g. Cloudera (??), -> Coursera
• Pay what you want - e.g. Radiohead
• Commission - e.g. SharesPost
• Commission per order - e.g. Seamless, GrubHub
• Auction - e.g. eBay
• Reverse Auction - ex Priceline
• Barter for services e.g. SwapRight

Subscription

• Software as a Service (SAAS) - e.g. Salesforce
• Service as a Service - e.g. Shopify
• Content as a Service - ex: Spotify, Netflix
• Infrastructure/Platform As A Service - e.g. AWS
• Freemium SAAS - e.g. Dropbox
• Donations - e.g. Wikipedia
• Sampling - ex Birchbox
• Membership Services - ex Amazon Prime
• Support and Maintenance - ex 10gen, Red Hat
• Paywall - e.g. NYTimes
• Voice and video-conferencing - e.g. Uberconference

Peer to Peer

• Peer-to-Peer Lending - e.g. Lending Club,
• Peer-to-Peer Gambling - e.g. BetFair
• Peer-to-peer buying - ex Etsy
• Peer-to-peer insurance/home/car - ex (??)
• Peer-to-peer computing (CrasPlan storage, or SETI@home)
• Peer-to-peer service - e.g. Mechanical Turk, TaskRabbit
• Peer-to-peer Mobile WiFi/Tethering - ex (??)

Transaction processing

• Merchant Acquiring - e.g. PayPal (Online / Offline), Stripe (Online), Square (Offline)
• Intermediary - e.g. IP Commerce (POS 2.0), CardSpring
• Acquiring Processing - e.g. Paymentech
• Bank Transfer - e.g. Dwolla
• Bank Depository Offering - e.g. Simple, Movenbank (spread on average deposits)
• Bank Card Issuance - e.g. Simple (interchange fee per transaction)
• Fulfillment - e.g. Amazon
• Messaging - e.g. Peer-to-Peer SMS, IM, Group Messaging
• Telephony - e.g. termination/origination in public telephony networks (skype out/in)
• Telephony - e.g. termination/origination within private telephony cloud (e.g.  native skype)
• Payment Gateways: Mobile -e.g. Braintree
• Platform Monetization (“Tax”) - Facebook Credits; iO6 30% cut.

Licensing

• Per Seat License - e.g. Sencha
• Per Device/Server License - e.g. QlikView
• Per Application instance - e.g. Adobe Photoshop
• Per Site License - e.g. Private cloud on internal infrastructure
• Patent Licensing - e.g. Qualcomm
• Brand Licensing - e.g. Sesame Street
• Indirect Licensing - e.g. Apple Volume Purchasing

Mobile

• Paid App Downloads - e.g. WhatsApp
• In-app purchases - e.g. Zynga Poker
• In-app subscriptions - e.g. NY Times app
• Advertising - e.g. Flurry, AdMob, Heyzap
• Digital-to-physical - e.g. Red Stamp, Postagram
• Transactions - ex Hailo

Gaming

• Freemium - Free to play w/ virtual currency - e.g. Zynga
• Subscription-  e.g. World of Warcraft
• Premium - e.g. xBox games
• DLC - (Downloadable Content)  - e.g. Call of Duty
• Ad Supported - ex - addictinggames.com

Trade Objects:

Advertising

• Impression (CPM)
• Click (CPC)
• Install or open application (CPI)
• Action inside the app e.g. complete first level of a game or make your first follow (CPA)

Content

• Apps
• Virtual goods
• Videos
• Games
• Books
• Magazines
• Images
• Gifts

Utility

• Apps - e.g. whatsapp messenger
• Virtual goods

Data

• User data - e.g. BlueKai
• Business data - e.g. Duedil
• User intelligence - e.g. Yougov
• Search Data - e.g. Chango
• Real-time Consumer Intent Data - e.g. Yieldbot
• Benchmarking services - e.g. Comscore
• Market research - e.g. GLG

Peer to Peer

• Money - e.g. Lending Club,
• Risk upside (gambling) - e.g. BetFair
• Risk downside (insurance)
• Production - ex Etsy
• Computation (storage, processing and security) (CrasPlan storage, or SETI@home, bitcoin)
• Service - e.g. Mechanical Turk, Exec
• Communication - e.g.    shared wifi networks

Limitations

Some of the business models cited are combinations of trade methods and trade objects e.g. in app purchases suggests both freemium (trade method) and virtual goods (trade object).