3/1/2011

Team Members Alan Chiu

Product management, enterprise software, storage, distributed systems

Danielle BuckleyProduct management, business development,

management consulting Evan Rosenfeld

Machine learning, mobile / web app architecture Gabriel Yu

Enterprise software development, web systems

Hypotheses needed for cloud compute marketplace Cloud IaaS has become a fungible

commodity Large supply of excess capacity Willingness to purchase from various

providers It’s possible to create a cloud

marketplace

Cloud compute marketplace

Build a cloud Build a cloud marketplacemarketplace

Direct sales Direct sales to both to both

buyers and buyers and sellerssellers

Many Many different different customer customer segments segments on buy-on buy-side and side and sell-sidesell-sideHuge Huge

dependency dependency on technical on technical

platformplatform

We got out of the building…

Interviewed potential buyersZynga, Xambala, Greplin, Pulse,

KISSMetrics, SumoLogic, Zencoder, Desktone, All Covered…

Interviewed potential sellersSavvis, AWS, Azure, Yahoo, Addepar…

Interviewed industry expertsVMware, Zuora, NetApp, SolarWinds, telco

consultant…

… And found a challenging missionary market Diverse IaaS products Non-trivial switching costs Amazon default for many Long-term vendor relationships

dominate Enterprise IAAS

Cloud Services Match Maker

Pivot Pivot away from away from technical technical platformplatform

Help buyers Help buyers find the best find the best

providerprovider Removed Removed financial, financial, consumer consumer segmentssegmentsAct as Act as

channel for channel for sellerssellers

We ran AdWords campagns and talked to customers… Ran Google AdWords campaign to test

landing pages and copy Talked to more customers

… And struggled to identify a “hair on fire” problem Low search volume for IaaS comparison Interest from public sellers in new channel Private seller IT not revenue-driven Variable workloads impact opex

Low search traffic implies “missionary” sales effort

Automated Cloud Capacity Planning

Pivot 1:Pivot 1:Capacity Capacity PlanningPlanning Pivot 2:Pivot 2:

Focus on Focus on enterprises enterprises

with with variable variable workloadworkload

We focused on demand creation and sales… Researched demand prediction models Explored sales models with experts Talked to more customers

… And came up with a 2-tiered model Found traction for capacity planning

business Identified sales strategy

Field sales model to large enterpriseInside sales model for lower end offering

Inside sales model for entry level customer

$1,000 / mo 5% attrition rate month-

to-month 20 month average

lifetime $20,000 LTV

Annual Sales Cost (inside sales): $1.3M Leads cost: $8.3K MarComm: $240k Advertising: $37k 5 Inside sales reps:

$1M 2 Tradeshows: $200K

Annual New Revenues: $4.8M

Sales Model Estimated Customer LTV

Field sales model for enterprise level customer

$20,000 / mo 2% attrition rate month-

to-month 50 month average

lifetime $1M LTV

•Annual Sales Cost (Field Sales):

•3 Field Sales Reps: $1.5M Cost

•Annual New Revenues: $3M

Sales Model Estimated LTV

Enterprise sales process

Capacity Planning· High variability in usage Service Matching• Companies new to cloudSLA Monitoring• Companies with high SLA requirements

· IaaS Integrators / consultants

• Inside and field sales· Development Costs· Infrastructure costs – AWS· Support costs

• Subscription charge to buyers• Pricing table scales based on # of servers and # of seats, with tiers

· For enterprise, higher touch model with field sales

Customers· Reduced cloud infrastructure cost· Increased visibility on service level

Integrators:· Increased revenue

• Develop capacity planning algorithm•Develop IaaS vendor relationships•Marketing and sales

· Technology partners – cloud vendors, management tools· System integrators / Consultants

· IP– prediction · Developers· Inside sales force· Field sales force · Biz dev (channel and technology partners)

Agora – FINAL

Cloud Lifecycle Management

Partner with Partner with IntegratorsIntegrators

Leverage Leverage both inside both inside and field and field

salessales

Position Position product for product for

lifecycle lifecycle managementmanagement

We got out of the building, and built a business model… Decided to use two-tier sales model Attended AWS meet-up Interviewed IT consultants Analyzed competitor and comparable

models Selected strategic direction

…and validated a 2-tier sales model with integrator support Ecosystem of cloud IT consultants /

integrators willing to engage Our product makes integrators money Concerns about 2-tier sales model,

though some examples of success Income statement passed test of reason

Agora Evolution

Addressing $5.4B market

Stage 1:Demand Prediction

Stage 2:Service Matching

Stage 3:Usage Monitoring/Control

Stage 4:Lifecycle Management

Relevant Category

IT Capacity Planning, Job Scheduling

Lead-gen on cloud spend

Server Management

BSM/ALM

Sizing Estimate

Capacity Planning: $258M (2008) -> $392M (2011)

Job Scheduling:$1.2B (2008) ->$1.6B (2011)

Forrester

10% affiliate fee on $13.1B cloud spend = $1.3B

IDC 2010

$430M (2008) -> $500M (2011)

Forrester

$637M (2008) -> $1.6B (2011), accelerating 36% YoY growth rate

Forrester

Total $2B $1.3B $500M $1.6B

We came a long way Key Lessons

Early days for compute market Opportunity for tools to support move to PaaS/ SaaS

adoption Customer engagement crucial

Our product now: a tool set for managing cloud compute usage Service matching Capacity planning Usage monitoring & control Targeting ~30% savings for customer

Potential for a viable business

Thanks!

Appendix: Canvases

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Capacity Planning· High variability in usage Service Matching• Companies unfamiliar with using cloud infrastructureSLA Monitoring• Companies with high SLA requirements with their customers

· Integrators / consultants specialized in cloud infrastructure

• Inside sales and field sales· Development Costs· Infrastructure costs – AWS· Support costs

• Subscription charge to buyers• Pricing table scales based on # of servers and # of seats, with tiers

· For enterprise segment, higher touch model with field sales force

· Reduced cloud infrastructure cost· Better compute needs matching· Increased visibility on service level

Integrators:· Increased budget for consulting services

• Design and refine capacity planning and match making algorithms•Develop and maintain cloud infrastructure vendors relationships•Develop brand as go-to place for cloud lifecycle management

· Technology partners – cloud vendors, management tools· System integrators / Consultants

· Intellectual property – prediction algorithm· Developers· Inside sales force· Field sales force · Biz dev (channel partners and technology partners)

Agora – V8

Week 8