Date post: | 20-Aug-2015 |
Category: |
Education |
Upload: | steve-blank |
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Customers: Lessons Learned
Potential for alternate sales model: sell to the individual engineer then up-sell to enterprise
Diversity of cloud service offerings Need to consider not just IaaS but also
PaaS Decision chain / sales model learnings Low search volume for terms related to
cloud comparison: missionary market
Highly Competitive Keywords
Lesson Learned:AdWords (paid SEM) is not going to be an efficient channel with these keywords
Costs for Informational Service Website
Development•Source Control (Github)•Agile Management (PivotalTracker)
Cost: ~$900/yr
Hosting•Application Hosting (Heroku)•Domain Reg, SSL (Godaddy)•Privacy Policy (TrustE)•CDN (MaxCDN)
Cost: ~$3700/yr
Marketing•~2000 marketing emails/day (SES)•Search Marketing (AdWords)•PR
Cost: TBD
Billing / Payment•Billing (Chargify)•Authorize.NET(Payment Gateway)
Cost: ~$1800/yr
Support•Support Forum (GetSatisfaction)
~$1200/yr
Job Processing•Cloud (AWS EC2)
Cost: TBD
Total: > $7500 / yr
Sales process: major learnings
Potential to target engineers, meet
their needs and get built into workflow. Then up-sell across
enterprise
If you meet the needs of engineer,
may be able to short-circuit this
process
A First Product: Logging/Prediction
Job Started
Job Ended
Spin Up New Server?
Spin down?
Server Logging Control Panel
Customers: Lessons LearnedHypothesis Findings
Sell-side • Public clouds •Seller: IT/ Business unit •Interest in monetizing unused capacity
Sell-side • Private clouds • One photo/video sharing site with excess capacity might be interested – scheduling interview
Buy-side • Startups • User: IT admin• Approver / Buyer: CEO • Most are satisfied with AWS• Alternative to AWS: hosted solution/ own servers
Buy-side • Enterprises • User: IT admin• Approver: IT director, VP IT, CIO• Economic buyer: CFO, CEO• Influencer: Industry analysts, cloud consultants, peers•May be additional route in, through meeting need of engineer and getting embedded in workflow
Buy-side • Rogue developers
• TBD
Value Proposition: Lessons Learned
Hypothesis Findings
Sell-side Service providers
• Additional marginal revenue at negligible cost (mostly additional customer service cost)
Sell-side Enterprises
• Lower IT cost – spot market
•May be wrong side of the house – IT departments are not responsible for rev gen*
Buy-side • Reduced infrastructure cost• Best-matched service provider
• Cost savings may be significant enough for enterprises with large modeling tasks (life sciences, energy, FS, radio technology) to consider*
* needs additional validation
Value Proposition: New Hypotheses
Hypothesis Findings
Sell-side • Demand prediction to optimize capacity planning
• Azure penalized for not meeting SLAs•Difficult for public cloud providers to determine optimal capacity planning
Buy-side • Infrastructure demand prediction to optimize cloud spend
• Example: life sciences, energy*
* needs additional validation