SaaS Revenue Modeling: Details of the 7 Revenue Streams

Draft 03/10.9

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SaaS Revenue Modeling:Details of the 7 Revenue Streams

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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


Different approachhttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved



Producers Consumers

Ecosystem

NetworkEffect


Very different approachhttp://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved



Producers Consumers

Ecosystem

NetworkEffect

Keydifferentiators





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.




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


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.




Revenue Model

NetworkCentricity


RevenueModel

Technology

Revenue Model consists of Revenue Streams

Products

AdvertisingServices

Recurring Ecosystem

Ancillary

NetworkEffect




MonthlySubscriptionsSaaS

SaaS is not a Revenue Model or Pricing Strategy!

If you only leverage “subscriptions” youare leaving money on the table

≠http://sixteenventures.com Copyright© 2010 Sixteen Ventures. All Rights Reserved



Pricing Strategy

Revenue Model

Understand where each piece fits into the overall SaaS Business Architecture

Architecture Marketing

separate




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




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




Pricing Strategy

Revenue Model

Architecture Marketing

separate

Revenue Model + Vertical Specific Pricing = Agility

Agile Revenue Generation is key...




Products

AdvertisingServices

Recurring Ecosystem

Ancillary

NetworkEffect

7 SaaS Revenue Streams




Recurring Ecosystem

Ancillary

NetworkEffect

Less Scalable Revenue Streams

Products

AdvertisingServices




Products

AdvertisingServices

Recurring Ecosystem

Ancillary

NetworkEffect

Scalable Revenue Streams





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


RevenueModel

Technology

Revenue Model consists of Primary & Secondary Revenue Streams


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




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


CPU Units Reports

Transactions Ads etc.

Pricing Bundle #2


CPU Units Reports


Pricing Bundle #3


CPU Units Reports





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


CPU Units Reports


Pricing Bundle #2


CPU Units Reports


Pricing Bundle #3


CPU Units Reports


Revenue Metrics

Different bundles for different market segments


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


CPU Units Reports


Pricing Bundle #2


CPU Units Reports


Pricing Bundle #3


CPU Units Reports


Different bundles for different market segments


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




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.




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




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




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




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


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




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




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




Wait... what about Free? If you have to ask...

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Download the Reality of Freemium in SaaS paper (PDF) today!

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Appendix A:Case Studies in SaaS Network Effect &

Ecosystem Revenue Modeling




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




SaaS Product Retail Supply Chain / EDI

End-Customer Small to Medium Consumer Packaged Goods manufacturer


•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




SaaS ProductVendor Managed Inventory Control System (internal product

re-architected & exposed as SaaS)

End-Customer Fragmented network of small independent pharmacies


•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




SaaS Product Revenue Cycle Management

End-Customer Fragmented network of small independent hospitals


•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




SaaS Product Managed Care Menu Management (ancillary market)

End-Customer Small Assisted Living Facilities


•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




SaaS Product Mail Center Management & Package Tracking

End-Customer Large Corporate & Fortune 500 mailrooms


•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




SaaS Product Treasury & Cash Management

End-Customer Large Corporate & Fortune 500 mailrooms


•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




SaaS Product Bank Spend Management

End-Customer Local and Regional Banks & Credit Unions


•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




Appendix B:Seven SaaS Revenue Streams Worksheet




Seven RevenueStreams Worksheet

Recurring

Ecosystem

Network Effect

Ancillary

Products

Services

Advertising

OriginalProducers

Stand-AloneConsumers

Consumers OtherProducers

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SaaS Revenue Modeling: Details of the 7 Revenue Streams

Technology

Transcript of SaaS Revenue Modeling: Details of the 7 Revenue Streams