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SaaS Revenue Modeling:Details of the 7 Revenue Streams
Legacy Software
Customers Developers
Channels
Three basic elementshttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved
Customers Developers
Channels
Software-as-a-Service (SaaS)
Same elementshttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved
Producers Consumers
Ecosystem
Software-as-a-Service (SaaS)
Different approachhttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved
Producers Consumers
Ecosystem
NetworkEffect
Software-as-a-Service (SaaS)
Very different approachhttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved
Producers Consumers
Ecosystem
NetworkEffect
Keydifferentiators
Software-as-a-Service (SaaS)
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ConsumersProducers Scalable Revenue Streams
The goals for a SaaS vendor should be different than a Legacy Software vendor
Understanding why* allowsfor proper Revenue Modeling*business scalability, increased CLV, leveraging multi-tenancy, etc.
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Legacy Software Business Structure
Marketing Intellectual Property
Revenue Model
Technology
Loosely-coupled, at besthttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved
NetworkCentricity
Integrated Business Architecture
Marketing Intellectual Property
Revenue ModelTechnology
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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Revenue Model
NetworkCentricity
Marketing Intellectual Property
RevenueModel
Technology
Revenue Model consists of Revenue Streams
Products
AdvertisingServices
Recurring Ecosystem
Ancillary
NetworkEffect
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MonthlySubscriptionsSaaS
SaaS is not a Revenue Model or Pricing Strategy!
If you only leverage “subscriptions” youare leaving money on the table
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Pricing Strategy
Revenue Model
Understand where each piece fits into the overall SaaS Business Architecture
Architecture Marketing
separate
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Pricing Strategy must be separated from Revenue Streams
Pricing Strategy is applied to customer-facing portions of the Revenue Model
Pricing Strategy
Revenue Model separate
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How can you apply Pricing Strategy withoutknowing what Revenue Streams you’ll leverage?
Use Pricing Strategy to drive users toScalable Revenue Streams
Pricing Strategy
Revenue Model separate
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Pricing Strategy
Revenue Model
Architecture Marketing
separate
Revenue Model + Vertical Specific Pricing = Agility
Agile Revenue Generation is key...
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Products
AdvertisingServices
Recurring Ecosystem
Ancillary
NetworkEffect
7 SaaS Revenue Streams
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Recurring Ecosystem
Ancillary
NetworkEffect
Less Scalable Revenue Streams
Products
AdvertisingServices
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Products
AdvertisingServices
Recurring Ecosystem
Ancillary
NetworkEffect
Scalable Revenue Streams
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Traditional Marketing Mix
Price is a function of Marketing, which is applied to in-built Revenue Models
NetworkCentricity
Marketing
Intellectual Property
RevenueModel
Technology
Marketing Mix
Product
PromotionPlace
Price
Revenue Model
NetworkCentricity
Marketing Intellectual Property
RevenueModel
Technology
Revenue Model consists of Primary & Secondary Revenue Streams
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Primary Revenue Stream
Secondary Revenue Streams
Primary Revenue Stream can be any of the available seven and depends upon a multitude of factors including market
alignment & level of funding
Revenue Metrics
Each revenue stream contains metrics
Products
AdvertisingServices
Ecosystem
Ancillary
NetworkEffect
RecurringMetrics
Modules Users Storage
CPU Units Reports
Transactions Files etc.
In SaaS, metrics are built into the application;This is a key differentiator from Legacy or ASP Models
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Revenue Metrics
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
Metrics
Pricing Bundle #1
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Pricing Bundle #2
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Pricing Bundle #3
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
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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
Pricing Bundle #1
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Pricing Bundle #2
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Pricing Bundle #3
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Revenue Metrics
Different bundles for different market segments
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Metrics
But what are these metrics? How are the pricing bundles determined? These are tied to your company
and your market!
Revenue Metrics
Pricing Bundle #1
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Pricing Bundle #2
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Pricing Bundle #3
Modules Users Storage
CPU Units Reports
Transactions Ads etc.
Different bundles for different market segments
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Metrics
Move any repeatable processes common to all clients into the SaaS
application
SaaS is about Rules, not Exceptions
Key Concepts in SaaS Revenue Modeling
Critical to focus as much on revenue
streams beyond the application as within
the core product
Be aware of all revenue streams when
architecting system even if they will only be used in the future
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Symbol Definition
Scalable Revenue Stream
Less-scalable Revenue Stream
Not Scalable in most cases
Revenue Stream Scalability Index
Scalability refers to margins per revenue stream; the more a revenue stream can benefit from economies of scale & improve margins with growth, the more “scalable” 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 reflect that.
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Recurring
-Examples -SubscriptionsPer User, Per
MonthPer Transaction
Usage-basedCapacity-basedPre-paid Credits
Pros Cons
1-Infinity Scaling Revenue Recognition
Captive Audience for upsell High initial CAC
Predictable revenue stream Churn / Customer Retention
Flexibility in pricing for different markets No large up-front payments
Downside guarantee on CLTV
Cannot be idle; must focus on CLTV/ARPU growth
Products
AdvertisingServices
Ecosystem
Ancillary
NetworkEffect
Recurring
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EcosystemProducts
AdvertisingServices
Recurring
Ancillary
NetworkEffect
Ecosystem
-Examples - Affiliate Sales
ChannelsAPIs
White LabelLicensing
Pros Cons
1-Infinity ScalingUnwanted
interdependencies can grow if unchecked
Improved value for ecosystem partners
Lack of visibility into value chain for clients
Exposure to ancillary & adjacent markets
Need to market to end-users to create demand in front of channel partners
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AncillaryProducts
AdvertisingServices
Recurring Ecosystem
NetworkEffect
Ancillary
-Examples -Processing Fees
Setup FeesOther FeesDiscounts
Float
Pros Cons
Super marginsSome options are complex
and not applicable early
Often not tied to any underlying cost
Overuse of add-on “fees” can hurt other revenue
streams
Discounts / Float are tied directly to the proxy
nature of the SaaS vendor in a Multi-tent
environment and have no direct exposure to the
clients
You can really turn away clients by nickel & diming them with fees that have
no underlying value associated with them
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Products
AdvertisingServices
Recurring Ecosystem
Ancillary
NetworkEffect
-Examples -Anonymized/
Aggregate DataReports
BenchmarksAPIs
Pros Cons
Fully leverages data collected in multi-tenant environment
Privacy concerns require disclosure of intentions by vendor
An asset that increases exponentially in value as usage of
the system grows linearly
Requires planning up front an execution early on data collection
otherwise value is lost until capture begins
Leverage ecosystem partners to develop reports or add value to
data through APIs
Vendor must be diligent in adhering to regulations,
governance, and privacy laws
Does not require a “critical mass” of users as many think for
network effect data to be valuable
Careful planning to determine when network effect data
becomes valuable & to whom required
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Network Effect
Products
AdvertisingServices
Recurring Ecosystem
Ancillary
NetworkEffect
Products
-Examples -Equipment
DevicesAppliancesHardware
Pros Cons
Can be high margin Requires capital to produce
Can produce vendor lock-in 1-1 or 1-few on each transaction
Can develop ancillary revenue streams
Support costs are high
Will improve value of Network Effect Data through automation
Logistics, supply chain management, returns, support, etc. add to overhead in dealing
with hardware
Inbuilt support for channel relationships can allow the
hardware partner to integrate (OEM) the product w/SaaS
Installation & support are difficult
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ServicesProducts
Advertising
Recurring Ecosystem
Ancillary
NetworkEffect
Services
-Examples -ProgrammingInstallationContent CreationTraining
Pros Cons
Core-competency for professional services companies moving to
SaaS1-1 or 1-few
High price Exception, not rule-based
Often high-marginHuman-centric and humans don’t
scale efficiently
When more repeatable processes are inbuilt to SaaS application,
services in less demand, but can be more expensive since they are
more specialized
Takes away resources from more working on more scalable revenue
streams
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AdvertisingProducts
Services
Recurring Ecosystem
Ancillary
NetworkEffect
Advertising
Ads only work when they are the main revenue stream and not an
afterthought. When ads work, the main customers of the company are the
advertisers and the revenue generated is part of the recurring revenue stream
Pros(mostly tongue-in-cheek)
Cons(all serious)
You don’t have to convince people that your product has value
Ads for SaaS products are part of a hope-based strategy
You don’t have to manage cash flow
De-values core product
Clients don’t have to pay you to use the product you built
Difficult to plan and forecast sales (impressions? clicks?)
There are close to 3B sets of eyeballs, if you only get 1% of
those to click...
Too much inventory (each screen) and not enough demand
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Wait... what about Free? If you have to ask...
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Download the Reality of Freemium in SaaS paper (PDF) today!
Appendix A:Case Studies in SaaS Network Effect &
Ecosystem Revenue Modeling
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Quick Start Sessions
SaaS Product Description of the SaaS offering
End-Customer Description of the SaaS vendor’s end-customer
End-Customer’s Trusted Advisors
Who did the end-customer buy from, listen to, etc. that the SaaS vendor could leverage, and help, in an effort to secure the
end-customer relationship
Network EffectWhat benefits the clients derived from the network centricity
of the SaaS solution, including aggregate data
EcosystemHow the Vendor derived value from, and added value to, its
ecosystem, including VARs, SIs, Distributors, etc.
Revenue Streams How the Vendor makes money
SaaS Case Studies
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SaaS Product Retail Supply Chain / EDI
End-Customer Small to Medium Consumer Packaged Goods manufacturer
End-Customer’s Trusted Advisors
•Big Box Retailers•Freight Brokers•Third-party Logistics Providers•Manufacturers reps
Network EffectBenchmarks on retail category performance available to all of
the end-customers’ Trusted Advisors
EcosystemPre-built EDI maps, access to discounted & expedited shipping,
visibility for intermediaries and interested parties
Revenue StreamsRecurring (monthly & per-transaction), Ecosystem, Network
Effect Data, Services
SaaS Case Study #1 - SCM/EDI Vendor
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SaaS ProductVendor Managed Inventory Control System (internal product
re-architected & exposed as SaaS)
End-Customer Fragmented network of small independent pharmacies
End-Customer’s Trusted Advisors
•Pharma Distributor that created the SaaS product•Industry Association•Product Suppliers (whom the Distributor buys from; value-pull)
Network EffectSophisticated inventory system allows distributor to aggregate
order history and current inventory for all pharmacies
EcosystemUse aggregate data to predict restocks, share that w/ vendor
to get better terms for the pharmacy client
Revenue StreamsAncillary (float interest), Ecosystem (distributor commissions),
improved margins), Network Effect Data (suppliers pay), Services, Products (hardware device)
SaaS Case Study #2 - Pharmaceutical Distributor
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SaaS Product Revenue Cycle Management
End-Customer Fragmented network of small independent hospitals
End-Customer’s Trusted Advisors
•Hospital Industry Associations•Independent Consulting Firms•Complementary Software Vendors•Insurance companies and Government Payors
Network EffectRevenue & Collection Benchmarks against similar-sized
Hospitals (per-bed)
EcosystemMedicare, Medicaid, and Commercial Payer clearinghouse,
Channel partners(visibility into their customers’ usage of system)
Revenue StreamsRecurring (per-transaction, % collected), Ecosystem, Network
Effect Data, Services, Products
SaaS Case Study #3 - Healthcare Revenue Cycle Mgmt
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SaaS Product Managed Care Menu Management (ancillary market)
End-Customer Small Assisted Living Facilities
End-Customer’s Trusted Advisors
•Food Distributors•Industry Association•Assisted Living Management Companies
Network EffectAggregate menu item usage data to help negotiate better deals
for end-clients (through channel partners where applicable)
EcosystemDirectly monetized relationship with Food Distributor
(channel) to salvage unprofitable existing relationship w/o getting in front of partner or negatively affecting end-client
Revenue StreamsRecurring (Annual per-location), Ecosystem (Distributor
visibility), Network Effect Data, Services, Products
SaaS Case Study #4 - Restaurant Menu Management
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SaaS Product Mail Center Management & Package Tracking
End-Customer Large Corporate & Fortune 500 mailrooms
End-Customer’s Trusted Advisors
•Mailing Industry Associations•Shipping Carrier Auditors•Industry Consultants•Complementary Software and Hardware Vendors
Network Effect
Most Mail Center managers are in a position to justify their existence so benchmarks against other Mail Centers helped prove operational efficiency, Complementary vendors and
industry associations found data useful, too
Ecosystemshipment tracking, spend management & procurement, carrier
audits
Revenue StreamsRecurring (per-transaction), Ancillary (carrier audits),
Ecosystem, Network Effect
SaaS Case Study #5 - Mail Center Management
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SaaS Product Treasury & Cash Management
End-Customer Large Corporate & Fortune 500 mailrooms
End-Customer’s Trusted Advisors
•Industry Associations•Anti-Money Laundering Groups•Banks•Consultants
Network EffectAggregation of transactional details across industries, locales, etc. Benchmarks on interest, float, sweeps, etc. against similar
industries
Ecosystem
Anonymous Aggregated (A/A) data used by Anti-Money Laundering groups to “teach” their software patterns, Banks and Consultants leverage A/A of their clients & others in the system to judge performance and offer guidance, upsell, etc.
Revenue StreamsRecurring (per user, per-transaction), Ancillary (float,
brokerage/forex commissions), Ecosystem, Network Effect Data
SaaS Case Study #6 - Treasury Management
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SaaS Product Bank Spend Management
End-Customer Local and Regional Banks & Credit Unions
End-Customer’s Trusted Advisors
•Industry associations•Local & Regional Printing Companies•Complementary Software Vendors•Office Supply vendors
Network Effect
Aggregate orders across bank branches allows vendors to aggregate order history and current inventory for customers, customers get group purchasing power through aggregation
under one SaaS vendor in addition to core product value
Ecosystem
Office Supply vendors gain visibility into the buying behavior of specific target market, complementary software vendors gain visiblity into transaction history of customers for inclusion in
their product
Revenue StreamsRecurring (per branch, vendor visibility), Ancillary, Ecosystem
(vendor commissions, API), Network Effect
SaaS Case Study #7 - Bank Spend Management
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Appendix B:Seven SaaS Revenue Streams Worksheet
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Seven RevenueStreams Worksheet
Recurring
Ecosystem
Network Effect
Ancillary
Products
Services
Advertising
OriginalProducers
Stand-AloneConsumers
Consumers OtherProducers
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