7 SaaS Revenue Streams With Details

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Draft03/10

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SaaS Revenue Modeling:Details of the 7 Revenue Streams
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Legacy Software

Three basic elementshttp://sixteenventures.com Copyright 2010 Sixteen Ventures. All Rights Reserved
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Software-as-a-Service (SaaS)

Same elementshttp://sixteenventures.com Copyright 2010 Sixteen Ventures. All Rights Reserved


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


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Keydifferentiators




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Scalable Revenue Streams

The goals for a SaaS vendor should be different than aLegacy Software vendor

Understanding why* allowsfor proper Revenue Modeling*business scalability, increased CLV, leveraging multi-tenancy, etc.

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Legacy Software BusinessStructure

Loosely-coupled, at besthttp://sixteenventures.com Copyright 2010 Sixteen Ventures. All Rights Reserved


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SaaS Business Architecture

All aspects are tightly coupled



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Revenue Model

Revenue Model consists of Revenue Streams



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SaaS is not a Revenue Model or Pricing Strategy!

If you only leverage subscriptions youare leaving money on the table



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Understand where each piece fits intothe overall SaaS Business Architecture

Architecture Marketing

separate



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Pricing Strategy must beseparated from Revenue Streams

Pricing Strategy is applied to customer-facing portions ofthe Revenue Model

separate



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How can you apply Pricing Strategy withoutknowing what Revenue Streams youll leverage?

Use Pricing Strategy to drive users toScalable Revenue Streams

separate



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Architecture Marketing

separate

Revenue Model + Vertical Specific Pricing = Agility

Agile Revenue Generation is key...



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7 SaaS RevenueStreams



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Less Scalable RevenueStreams



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Scalable RevenueStreams



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Traditional Marketing Mix

Price is a function of Marketing, which isapplied to in-built Revenue Models


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Revenue Metrics

Each revenue stream contains metrics

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 arerepresented in the application are bundled, along with

timeframes (monthly, annual, etc.), during PricingStrategy based on marketing goals

Pricing Bundle #1


CPU Units Reports


Pricing Bundle #2


CPU Units Reports


Pricing Bundle #3


CPU Units Reports


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But what are these metrics? How are the pricingbundles determined? These are tied toyour 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 markets

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Key Concepts in SaaS Revenue Modeling



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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 revenuestream can benefit from economies of scale & improve margins withgrowth, the more scalable the revenue stream. Its not possible toeliminate all of the non-scalable streams (nor should you), but theirvalue should be improved and the price charged should reflect that.



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Recurring

Pros Cons

1-Infinity Scaling Revenue Recognition

Captive Audience for upsell High initial CAC

Predictable revenue streamChurn / Customer

Retention

Flexibility in pricing for

different markets No large up-front payments

Downside guarantee onCLTV

Cannot be idle; must focuson CLTV/ARPU growth



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Ecosystem

Pros Cons

1-Infinity ScalingUnwanted

interdependencies can

grow if unchecked

Improved value forecosystem partners

Lack of visibility into valuechain for clients

Exposure to ancillary &adjacent markets

Need to market to end-users to create demand infront of channel partners



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Ancillary

Pros Cons

Super marginsSome options are complex

and not applicable early

Often not tied to anyunderlying cost

Overuse of add-on feescan hurt other revenuestreams

Discounts / Float are tieddirectly to the proxy

nature of the SaaS vendorin a Multi-tent

environment and have nodirect exposure to the

clients

You can really turn away

clients by nickel & dimingthem with fees that have

no underlying valueassociated with them



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Pros Cons

Fully leverages data collected inmulti-tenant environment

Privacy concerns requiredisclosure of intentions by vendor

An asset that increasesexponentially in value as usage of

the system grows linearly

Requires planning up front anexecution early on data collection

otherwise value is lost untilcapture begins

Leverage ecosystem partners todevelop reports or add value to

data through APIs

Vendor must be diligent inadhering to regulations,

governance, and privacy laws

Does not require a critical massof users as many think for

network effect data to be valuable

Careful planning to determinewhen network effect data

becomes valuable & to whomrequired


Network Effect
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Products

Pros ConsCan be high margin Requires capital to produce

Can produce vendor lock-in 1-1 or 1-few on each transaction

Can develop ancillary revenuestreams

Support costs are high

Will improve value of NetworkEffect Data through automation

Logistics, supply chainmanagement, returns, support,etc. add to overhead in dealing

with hardware

Inbuilt support for channelrelationships can allow the

hardware partner to integrate(OEM) the product w/SaaS

Installation & support are difficult

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Services

Pros Cons

Core-competency for professionalservices companies moving to

SaaS1-1 or 1-few

High price Exception, not rule-based

Often high-marginHuman-centric and humans dont

scale efficiently

When more repeatable processesare inbuilt to SaaS application,

services in less demand, but canbe more expensive since they are

more specialized

Takes away resources from moreworking on more scalable revenue

streams



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Advertising

Pros

(mostly tongue-in-cheek)

Cons

(all serious)

You dont have to convince peoplethat your product has value

Ads for SaaS products are part ofa hope-based strategy

You dont have to manage cashflow

De-values core product

Clients dont have to pay you touse the product you built

Difficult to plan and forecast sales(impressions? clicks?)

There are close to 3B sets ofeyeballs, 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!
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Appendix A:Case Studies in SaaS Network Effect &

Ecosystem Revenue Modeling



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SaaS Product Description of the SaaS offering

End-Customer Description of the SaaS vendors end-customer

End-CustomersTrusted Advisors

Who did the end-customer buy from, listen to, etc. that theSaaS 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


Big Box RetailersFreight BrokersThird-party Logistics ProvidersManufacturers reps

Network EffectBenchmarks on retail category performance available to all of

the end-customers Trusted Advisors

Ecosystem Pre-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 Product

Vendor Managed Inventory Control System (internal product

re-architected & exposed as SaaS)

End-Customer Fragmented network of small independent pharmacies

End-Customers

Trusted Advisors

Pharma Distributor that created the SaaS productIndustry 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

Ecosystem Use aggregate data to predict restocks, share that w/ vendorto 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


Hospital Industry AssociationsIndependent Consulting FirmsComplementary Software VendorsInsurance companies and Government Payors

Network EffectRevenue & Collection Benchmarks against similar-sized

Hospitals (per-bed)

Ecosystem

Medicare, 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


Food DistributorsIndustry AssociationAssisted Living Management Companies

Network EffectAggregate menu item usage data to help negotiate better deals

for end-clients (through channel partners where applicable)

Ecosystem

Directly monetized relationship with Food Distributor

(channel) to salvage unprofitable existing relationship w/ogetting 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


Mailing Industry AssociationsShipping Carrier Auditors

Industry Consultants

Complementary Software and Hardware Vendors

Network Effect

Most Mail Center managers are in a position to justify theirexistence so benchmarks against other Mail Centers helpedprove 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


Industry AssociationsAnti-Money Laundering GroupsBanks

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-MoneyLaundering groups to teach their software patterns, Banks

and Consultants leverage A/A of their clients & others in thesystem to judge performance and offer guidance, upsell, etc.

Revenue StreamsRecurring (per user, per-transaction), Ancillary (float,

brokerage/forex commissions), Ecosystem, Network EffectData

SaaS Case Study #6 - Treasury Management

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SaaS Product Bank Spend Management

End-Customer Local and Regional Banks & Credit Unions


Industry associationsLocal & Regional Printing CompaniesComplementary Software VendorsOffice Supply vendors

Network Effect

Aggregate orders across bank branches allows vendors toaggregate 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 gainvisiblity 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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7 SaaS Revenue Streams With Details