Separation of Lanthanides/ Lanthanides and Actinides
Iddi final 2013 stanford e245
1. E245
BETTER DATA
BETTER INSIGHTS
BE
BETTER WORLD
MARYANNA | ZINEB | THERESA | KYLAN
INTERVIEWS | NEW/TOTAL | 10/119
Draft – WIP - Confidential
iddi
2. Team Members : What we Thought
• Zineb Laraki • Maryanna Quigless
• MS EarthSys, SymSys • GSB
• Nice Smile • Lost and Alone :/
• Kylan Lundeen
• Theresa Johnson
• GSB
• PhD, Aero-Astro
• Great Hat!
• Skeptical Engineer :-/
3. Team Members : What we Found
• Zineb Laraki • Maryanna Quigless
• MS EarthSys, SymSys • GSB
• Awesome Cust. • Team Builder :-D
Interviews
• Kylan Lundeen
• Theresa Johnson
• GSB
• PhD, Aero-Astro
• Deep domain exp.
• Skeptical Engineer :-/
• Awesome designer
4. Our Path
Profound Belief: Un-intrusive, Rewarding Feedback
2. Viral Consumer
3. Mobile In-App
1. In-Store for SMB Product Re-sell
Survey Delivery
data
Will ppl give real-time feedback? Is there a better
Will SMB’s buy? way?
Feedback tied to
3 Question POS Survey
location
Will SMBs pay for misc. data?
Will ppl respond? Real time feedback for
Prompt + Pic + SMS
discounts/discovery
Can we go viral?
Real Time Yelp for
Events
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7. MVP: “Where’s the product?”
We built it… ... we sold it… ..then iterated.. …and launched
“Lets experiment: will a “Let’s integrate paying “Let’s figure out analytics,
customer buy a customer feedback and kick marketing and launch!”
subscription?” it up a notch”
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8. What we found
• SMB willing to pay $20-$50/mo.
• Survey Takers 1% response rate
• POS/Table-top is crowded
9. Our Path
Profound Belief: Un-intrusive, Rewarding Feedback
1. In-Store for SMB
Will SMB’s buy?
3 Question POS
Survey
Will (more) ppl Prompt + Pic +
respond? SMS
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10. Test what drives responses
– Test incentives
• Discount at POS
• Chance to win
• Better intrinsic call to action
– Test “reinventing the survey”
• Snap a picture & email
• Text rating to number
+
Test timing
• Before shopping transaction
• After/home based
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11. Experiments
4 Pictures +
• Hand-to-hand commentary
combat works
“Z axis”
– Immediate
Incentives work Intrinsic Motivation
– Ease of texting Marketing matters
– Value of incentive
• 2 Pictures +
Timing matters- after commentary
experience/during
exit asks suck – Social/Viral works
400%
443 Handouts 1
response – Poor placement hurts
– Don’t Delay
Gratification
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12. What we found
• 20% Response rate using pre-shopping
handout + Discount
• 20% Response rate using pre-shopping
handout and pictures
• Low response rate post-shopping
13. Trough of despair…more Qs than
Answers
Cost of scaling SMB? Differentiation? Respondent
acquisition???
units
time
15. Our Path
Profound Belief: Un-intrusive, Rewarding Feedback
2. Viral Consumer
Product Re-sell
data
Will ppl give real-time feedback?
Feedback tied to
location
Real time feedback for
discounts/discovery
Real Time Yelp for
Events
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16. What we thought..
• Let’s focus on acquiring feedback givers…
• Hypotheses:
– Event knowledge solves a pain for users
– Event knowledge keeps id|di ubiquitous
– Event feedback solves a pain for promoters
– “everyone will just….use it…”
17. Business Model v5 -- What we did
• Built a mock up of “id|di rooster”, real time yelp for events
• Got out of the building: Tested it via interviews and “the BBL
test”
18. What we found
• Hyper local events Kind of… events are hard to
discover….people use email and
discovery solves a digests as a hack
pain
Most people plan ahead
(not JIT-ers)
• Community would Kind of… very temporal, after 20
minutes utility “expires”
keep app ubiquitous
Need to be hyper viral
No…campus promoters won’t
pay
• Promoter pain point
solved Need data to show value
19. What we thought…
• If the information is
there…they will come
• Seed the system by
scraping other networks
for information.
• Leverage partners to add
value to promoters and
users
20. Business Model v6 – What we did
Testing outside of the building….
Can we reach target Can we add value Can we create a What is user cost?
viral coefficient? via scrape? conversation?
1.1 Not really… Not really… Yes… $20 (too much)…
21. What we found
• The numbers didn’t add up…we need to bring
distribution channel cost down
22. What we thought
Hypothesis:
• We need to lower cost of acquiring respondents Web banner ad
modules
• We need to create a way for more direct access to Interstitials
respondents +
• We need to automate user sign up/ launch Self service product
Market Researchers
iddi inMobi Targeted
Publishers
Survey Creation, Respondents
Data & Insight Tools
23. Business Model v7 – What we did
Interviewed potential Interviewed potential
channel partners customers and product
partners
24. What we found
• Large ad networks won’t partner with us until
they see scale
• Need to build an API with existing infrastructure
– “banner ad space as a container”
• Potential developing market opportunity
• Product selection bias awareness (don’t behave
like survey on the spot)
• Can the busy customer launch and review quickly
(“the on the toilet test”)?
25. Interstitial surveys via mobile content
Market Researchers
iddi inMobi Targeted
Publishers
Survey Creation, Respondents
Data & Insight Tools
Latte or Cappuccino?
28. Where we add value
Smart Phone
Apps
Tablet
Mobile Ads
Feature Phone Web
29. Revenue Model: Smart-phone, US
Market Researchers
iddi inMobi Targeted
Publishers
Survey Creation, Respondents
Data & Insight Tools $0.30/res. $0.70/res.
$1.50/res.
30. Revenue Model: Feature Phone, Africa
Market Researchers
iddi inMobi Targeted
Publishers
Survey Creation, Respondents
Data & Insight Tools $0.20/res. $0.10/res.
$1.00/res.
31. RoadMap
April –Dec. 2013 Jan. 2014 June 2015
Beta Product Testing
US Smart-phone launch
6 mos. – 1yr
$500K angel Africa, Feature Phone Launch
Raise Series-A based on
3 co-founders working product and 100-
300 paying customers Raise Series B based on
2 additional 2500+ paying customers
developers/designers
Beta test with entrepreneurs Hire 3 mid market sales,
& CPGs $40K + commission Partner with publishers in
Ghana, Kenya and CapeTown
Recurring CPG Revenue
New Sales to NGOs and
Manufacturing & local SMB
32. Viability?
• Secured Space in GSB Venture Studio
• StartX Motwani Labs
• Theresa Johnson • Maryanna Quigless
• PhD Engineering • GSB
• Data algorithms • Consulting
• Start-up (beta-SeriesA, • Start-up Iroko
Apture) • Africa
33. Lessons Learned Summary
• Stick to your guns!! (Thanks Steve)
• Being hypothesis/data driven
– Getting customers to give feedback is hard
– It needs to be easy and convenient
– Needs a clear incentive
• Intrinsic: Help Business – Improve your experience
• Extrinsic: Reward before you walk out the door
• Filtering through lots of contradictory
feedback and unclear signals
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