More Related Content More from Lincoln Murphy (12) Updated 7 SaaS Revenue Streams with Details1. Draft
03/10.9
SaaS Revenue Modeling:
Details of the 7 Revenue Streams
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2. Legacy Software
Customers Developers
Channels
Three basic elements
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3. Software-as-a-Service (SaaS)
Customers Developers
Channels
Same elements
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4. Software-as-a-Service (SaaS)
Producers Consumers
Ecosystem
Different approach
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5. Software-as-a-Service (SaaS)
Producers Consumers
Network
Effect
Ecosystem
Very different approach
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6. Software-as-a-Service (SaaS)
Producers Consumers
Network
Effect
Key
differentiators
Ecosystem
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7. The goals for a SaaS vendor should be different than a
Legacy Software vendor
Producers Scalable Revenue Streams Consumers
Understanding why* allows
for proper Revenue Modeling
*business scalability, increased CLV, leveraging multi-tenancy, etc.
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8. Legacy Software Business Structure
Intellectual
Marketing
Property
Technology Revenue
Model
Loosely-coupled, at best
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9. Integrated Business Architecture
Intellectual
Marketing
Property
Network
Centricity
Revenue
Technology
Model
One core piece of technology must be able to support
multiple revenue streams with different pricing and
distribution methods for multiple market segments.
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10. Revenue Model
Products
Marketing Intellectual
Property Recurring Ecosystem
Network Network
Centricity Effect
Services Advertising
Technology Revenue
Model Ancillary
Revenue Model consists of Revenue Streams
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11. SaaS is not a Revenue Model or Pricing Strategy!
SaaS
â Monthly
Subscriptions
If you only leverage âsubscriptionsâ you
are leaving money on the table
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12. Architecture Marketing
Revenue Pricing
separate
Model Strategy
Understand where each piece ïŹts into
the overall SaaS Business Architecture
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13. Pricing Strategy must be
separated from Revenue Streams
Revenue Pricing
separate
Model Strategy
Pricing Strategy is applied to customer-facing portions of
the Revenue Model
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14. How can you apply Pricing Strategy without
knowing what Revenue Streams youâll leverage?
Revenue Pricing
separate
Model Strategy
Use Pricing Strategy to drive users to
Scalable Revenue Streams
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15. Agile Revenue Generation is key...
Architecture Marketing
Revenue Pricing
separate
Model Strategy
Revenue Model + Vertical SpeciïŹc Pricing = Agility
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16. 7 SaaS Revenue Streams
Products
Recurring Ecosystem
Network
Effect
Services Advertising
Ancillary
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17. Less Scalable Revenue Streams
Products
Recurring Ecosystem
Network
Effect
Services Advertising
Ancillary
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18. Scalable Revenue Streams
Products
Recurring Ecosystem
Network
Effect
Services Advertising
Ancillary
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19. Traditional Marketing Mix
Revenue Intellectual
Model Property Product Price
Network
Centricity Marketing Mix
Technology Marketing Place Promotion
Price is a function of Marketing, which is
applied to in-built Revenue Models
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20. Revenue Model
Primary Revenue Stream can be any of the
available seven and depends upon a
multitude of factors including market
alignment & level of funding
Marketing Intellectual
Property Primary Revenue
Network
Stream
Centricity
Technology Revenue Secondary
Model Revenue Streams
Revenue Model consists of
Primary & Secondary Revenue Streams
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21. Revenue Metrics
Modules Users Storage
CPU Units Reports
Products
Transactions Files etc. Metrics
Recurring Ecosystem
Network
Effect
Services Advertising
In SaaS, metrics are built into the application;
This is a key differentiator from Legacy or ASP Models Ancillary
Each revenue stream contains metrics
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22. Revenue Metrics
Metrics
Pricing Bundle #1 Pricing Bundle #2 Pricing Bundle #3
Modules Users Storage Modules Users Storage Modules Users Storage
CPU Units Reports CPU Units Reports CPU Units Reports
Transactions Ads etc. Transactions Ads etc. Transactions Ads etc.
Metrics from any or all revenue streams that are
represented in the application are bundled, along with
timeframes (monthly, annual, etc.), during Pricing
Strategy based on marketing goals
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23. Revenue Metrics
Metrics
Different bundles for different market segments
Pricing Bundle #1 Pricing Bundle #2 Pricing Bundle #3
Modules Users Storage Modules Users Storage Modules Users Storage
CPU Units Reports CPU Units Reports CPU Units Reports
Transactions Ads etc. Transactions Ads etc. Transactions Ads etc.
Separating Revenue Model & Pricing Strategy improves agility
and allows pricing to be aligned with market requirements;
critical when tightly focusing on a target market segment or
when entering adjacent markets
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24. Revenue Metrics
Metrics
Different bundles for different market segments
Pricing Bundle #1 Pricing Bundle #2 Pricing Bundle #3
Modules Users Storage Modules Users Storage Modules Users Storage
CPU Units Reports CPU Units Reports CPU Units Reports
Transactions Ads etc. Transactions Ads etc. Transactions Ads etc.
But what are these metrics? How are the pricing
bundles determined? These are tied to your company
and your market!
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25. Key Concepts in SaaS Revenue Modeling
Move any repeatable
SaaS is about Rules, processes common to
not Exceptions all clients into the SaaS
application
Critical to focus as Be aware of all revenue
much on revenue streams when
streams beyond the architecting system
application as within even if they will only
the core product be used in the future
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26. Revenue Stream Scalability Index
Symbol DeïŹnition
Scalable Revenue Stream
Less-scalable Revenue Stream
Not Scalable in most cases
Scalability refers to margins per revenue stream; the more a revenue
stream can beneïŹt from economies of scale & improve margins with
growth, the more âscalableâ the revenue stream. Its not possible to
eliminate all of the non-scalable streams (nor should you), but their
value should be improved and the price charged should reïŹect that.
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27. Products Recurring
Recurring Ecosystem
Network
Pros Cons
Effect
Services Advertising
Ancillary
1-InïŹnity Scaling Revenue Recognition
-Examples - Captive Audience for upsell High initial CAC
Subscriptions
Per User, Per Churn / Customer
Predictable revenue stream
Month Retention
Per Transaction
Flexibility in pricing for
Usage-based different markets
No large up-front payments
Capacity-based
Pre-paid Credits Downside guarantee on Cannot be idle; must focus
CLTV on CLTV/ARPU growth
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28. Products Ecosystem
Recurring Ecosystem
Network
Effect
Services Advertising
Ancillary
Pros Cons
Unwanted
1-InïŹnity Scaling interdependencies can
-Examples - grow if unchecked
AfïŹliate Sales Improved value for Lack of visibility into value
Channels ecosystem partners chain for clients
APIs
White Label Exposure to ancillary &
Need to market to end-
Licensing users to create demand in
adjacent markets
front of channel partners
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29. Products Ancillary
Recurring Ecosystem
Network
Effect
Services Advertising Pros Cons
Ancillary
Some options are complex
Super margins
and not applicable early
Overuse of add-on âfeesâ
-Examples - Often not tied to any
can hurt other revenue
underlying cost
Processing Fees streams
Setup Fees Discounts / Float are tied
Other Fees directly to the proxy You can really turn away
Discounts nature of the SaaS vendor clients by nickel & diming
in a Multi-tent them with fees that have
Float environment and have no no underlying value
direct exposure to the associated with them
clients
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30. Products Network Effect
Recurring Ecosystem
Network
Effect
Pros Cons
Services Advertising
Ancillary
Fully leverages data collected in Privacy concerns require
multi-tenant environment disclosure of intentions by vendor
-Examples - An asset that increases
Requires planning up front an
execution early on data collection
Anonymized/ exponentially in value as usage of
otherwise value is lost until
the system grows linearly
Aggregate Data capture begins
Reports Leverage ecosystem partners to
develop reports or add value to
Vendor must be diligent in
adhering to regulations,
Benchmarks data through APIs governance, and privacy laws
APIs Does not require a âcritical massâ
Careful planning to determine
when network effect data
of users as many think for
becomes valuable & to whom
network effect data to be valuable
required
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31. Products Products
Recurring Ecosystem
Network
Pros Cons
Effect
Services Advertising
Ancillary
Can be high margin Requires capital to produce
Can produce vendor lock-in 1-1 or 1-few on each transaction
-Examples - Can develop ancillary revenue
Support costs are high
Equipment streams
Logistics, supply chain
Devices Will improve value of Network management, returns, support,
Appliances Effect Data through automation etc. add to overhead in dealing
with hardware
Hardware
Inbuilt support for channel
relationships can allow the
Installation & support are difïŹcult
hardware partner to integrate
(OEM) the product w/SaaS
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32. Products Services
Recurring Ecosystem
Network
Effect
Pros Cons
Services Advertising
Ancillary
Core-competency for professional
services companies moving to 1-1 or 1-few
SaaS
-Examples - High price Exception, not rule-based
Programming
Installation Often high-margin
Human-centric and humans donât
scale efïŹciently
Content
Creation When more repeatable processes
are inbuilt to SaaS application, Takes away resources from more
Training services in less demand, but can working on more scalable revenue
be more expensive since they are streams
more specialized
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33. Products Advertising
Recurring Ecosystem
Network
Effect Pros Cons
Services Advertising (mostly tongue-in-cheek) (all serious)
Ancillary
You donât have to convince people Ads for SaaS products are part of
that your product has value a hope-based strategy
Ads only work when they You donât have to manage cash
are the main revenue De-values core product
ïŹow
stream and not an
afterthought. When ads
work, the main customers Clients donât have to pay you to DifïŹcult to plan and forecast sales
of the company are the use the product you built (impressions? clicks?)
advertisers and the revenue
generated is part of the There are close to 3B sets of
Too much inventory (each screen)
recurring revenue stream eyeballs, if you only get 1% of
and not enough demand
those to click...
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34. Wait... what about Free? If you have to ask...
Download the Reality of Freemium in SaaS paper (PDF) today!
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35. Appendix A:
Case Studies in SaaS Network Effect &
Ecosystem Revenue Modeling
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37. SaaS Case Studies
SaaS Product Description of the SaaS offering
End-Customer Description of the SaaS vendorâs end-customer
Who did the end-customer buy from, listen to, etc. that the
End-Customerâs
SaaS vendor could leverage, and help, in an effort to secure the
Trusted Advisors
end-customer relationship
What beneïŹts the clients derived from the network centricity
Network Effect
of the SaaS solution, including aggregate data
How the Vendor derived value from, and added value to, its
Ecosystem
ecosystem, including VARs, SIs, Distributors, etc.
Revenue Streams How the Vendor makes money
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38. SaaS Case Study #1 - SCM/EDI Vendor
SaaS Product Retail Supply Chain / EDI
End-Customer Small to Medium Consumer Packaged Goods manufacturer
âąBig Box Retailers
End-Customerâs âąFreight Brokers
Trusted Advisors âąThird-party Logistics Providers
âąManufacturers reps
Benchmarks on retail category performance available to all of
Network Effect
the end-customersâ Trusted Advisors
Pre-built EDI maps, access to discounted & expedited shipping,
Ecosystem
visibility for intermediaries and interested parties
Recurring (monthly & per-transaction), Ecosystem, Network
Revenue Streams
Effect Data, Services
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39. SaaS Case Study #2 - Pharmaceutical Distributor
Vendor Managed Inventory Control System (internal product
SaaS Product
re-architected & exposed as SaaS)
End-Customer Fragmented network of small independent pharmacies
âąPharma Distributor that created the SaaS product
End-Customerâs âąIndustry Association
Trusted Advisors âąProduct Suppliers (whom the Distributor buys from; value-
pull)
Sophisticated inventory system allows distributor to aggregate
Network Effect
order history and current inventory for all pharmacies
Use aggregate data to predict restocks, share that w/ vendor
Ecosystem
to get better terms for the pharmacy client
Ancillary (ïŹoat interest), Ecosystem (distributor commissions),
Revenue Streams improved margins), Network Effect Data (suppliers pay),
Services, Products (hardware device)
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40. SaaS Case Study #3 - Healthcare Revenue Cycle Mgmt
SaaS Product Revenue Cycle Management
End-Customer Fragmented network of small independent hospitals
âąHospital Industry Associations
End-Customerâs âąIndependent Consulting Firms
Trusted Advisors âąComplementary Software Vendors
âąInsurance companies and Government Payors
Revenue & Collection Benchmarks against similar-sized
Network Effect
Hospitals (per-bed)
Medicare, Medicaid, and Commercial Payer clearinghouse,
Ecosystem Channel partners
(visibility into their customersâ usage of system)
Recurring (per-transaction, % collected), Ecosystem, Network
Revenue Streams
Effect Data, Services, Products
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41. SaaS Case Study #4 - Restaurant Menu Management
SaaS Product Managed Care Menu Management (ancillary market)
End-Customer Small Assisted Living Facilities
End-Customerâs âąFood Distributors
Trusted Advisors âąIndustry Association
âąAssisted Living Management Companies
Aggregate menu item usage data to help negotiate better deals
Network Effect
for end-clients (through channel partners where applicable)
Directly monetized relationship with Food Distributor
Ecosystem (channel) to salvage unproïŹtable existing relationship w/o
getting in front of partner or negatively affecting end-client
Recurring (Annual per-location), Ecosystem (Distributor
Revenue Streams
visibility), Network Effect Data, Services, Products
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42. SaaS Case Study #5 - Mail Center Management
SaaS Product Mail Center Management & Package Tracking
End-Customer Large Corporate & Fortune 500 mailrooms
âąMailing Industry Associations
End-Customerâs âąShipping Carrier Auditors
Trusted Advisors âąIndustry Consultants
âąComplementary Software and Hardware Vendors
Most Mail Center managers are in a position to justify their
existence so benchmarks against other Mail Centers helped
Network Effect
prove operational efïŹciency, Complementary vendors and
industry associations found data useful, too
shipment tracking, spend management & procurement, carrier
Ecosystem
audits
Recurring (per-transaction), Ancillary (carrier audits),
Revenue Streams
Ecosystem, Network Effect
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43. SaaS Case Study #6 - Treasury Management
SaaS Product Treasury & Cash Management
End-Customer Large Corporate & Fortune 500 mailrooms
âąIndustry Associations
End-Customerâs âąAnti-Money Laundering Groups
Trusted Advisors âąBanks
âąConsultants
Aggregation of transactional details across industries, locales,
Network Effect etc. Benchmarks on interest, ïŹoat, sweeps, etc. against similar
industries
Anonymous Aggregated (A/A) data used by Anti-Money
Laundering groups to âteachâ their software patterns, Banks
Ecosystem
and Consultants leverage A/A of their clients & others in the
system to judge performance and offer guidance, upsell, etc.
Recurring (per user, per-transaction), Ancillary (ïŹoat,
Revenue Streams brokerage/forex commissions), Ecosystem, Network Effect
Data
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44. SaaS Case Study #7 - Bank Spend Management
SaaS Product Bank Spend Management
End-Customer Local and Regional Banks & Credit Unions
âąIndustry associations
End-Customerâs âąLocal & Regional Printing Companies
Trusted Advisors âąComplementary Software Vendors
âąOfïŹce Supply vendors
Aggregate orders across bank branches allows vendors to
aggregate order history and current inventory for customers,
Network Effect
customers get group purchasing power through aggregation
under one SaaS vendor in addition to core product value
OfïŹce Supply vendors gain visibility into the buying behavior of
speciïŹc target market, complementary software vendors gain
Ecosystem
visiblity into transaction history of customers for inclusion in
their product
Recurring (per branch, vendor visibility), Ancillary, Ecosystem
Revenue Streams
(vendor commissions, API), Network Effect
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45. Appendix B:
Seven SaaS Revenue Streams Worksheet
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46. http://sixteenventures.com
Seven Revenue
Streams Worksheet
Consumers Original Other Stand-Alone
Producers Producers Consumers
Recurring
Ecosystem
Network Effect
Ancillary
Products
Services
Advertising
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