A Great idea does not mean that you are going to make it. 90% of all startups fail. But don’t feel hopeless, there is a systematic approach to startups that will increase your chances of success and we are going to introduce it to you. Through the use of Lean startup methodology, building MVP, customer discovery methods, Hypothesis-Driven development, advanced metrics and learn-build-measure cycle you will learn what approach is most successful for startup projects.

1. Lean Startup
How to turn your great idea into a live product
by Faris Zacina and Adi Behlulovic

2. Why are we relevant to talk about this?

3. Ministry of programming - Startup Factory
- From inception in 2015 we are exclusively in the startup game
- Our ~60 team members built over 30 startups across different categories. Many
of them failed over the years.
- We recently had an IPO with one of our startups that went from MVP to IPO in
less than 3 years and has a current market cap of 210 mil. EUR in Germany

4. Goal of this presentation
Understand the critical elements and concepts of the Lean Startup approach

5. Definition of a Startup
“Startups are money burning machines with low chances of success. Better give
money to Your girlfriend instead.” - A smart guy

6. The actual definition
“A Startup is a temporary organization used to search for a repeatable and scalable
business model.” - Steve Blank, 4 Steps to Epiphany

7. Why do I need to search?
I know my Startup will succeed. It’s a
billion dollar idea!!!
I just need a dev team and 6 months to develop it and BOOM! Millions!

8. Billion $ idea - Webvan - Online grocery store

9. Webvan - Raised 800mil $, IPO-ed and failed
- Founded in 1996
- Sure of success → Get Big fast and use the First Mover Advantage
- Hired seasoned CEO and VP’s from big corporations
- Raised 800 mil $ of venture capital and invested in complex infrastructure and
team growth (especially marketing & sales)
- Built a Web App and supporting infrastructure
- At some point they had a market cap of 1.2 billion $
- Went bankrupt in 2001 - 24 months after IPO

10. The retention death pyramid

11. Why it failed?

12. They focused on execution instead of search,
discovery and learning
- Market and Product risk was not questioned
properly at very early stage
- They focused on scaling before actually
validating the value hypothesis and “finding” the
business model to scale
- This is A.k.A. Strategy Waterfall

13. What’s the solution?

14. One possible solution - Lean Startup

15. Business Model Canvas

16. What is a business model canvas?

17. Business Model Canvas
- You start with a vision and break it down into a set of hypothesis to question
different ASSumptions
- One of the first elements of your startup
- Since product-market fit is unknown the idea is to validate every hypothesis with
real data
- The goal is to test the hypothesis as soon as possible
- Business model canvas is a living artifact. It changes all the time with customer
understanding.

18. Death vs Success
- Webvan was sure of success. They didn’t need a hypothesis. They had a clear
business plan to execute and they started investing into marketing/sales quickly
to grow fast which caused premature death.
- Success is writing your hypothesis and validating it with real data. Question
everything, including Your vision.

19. MVP / Customer Discovery

20. Minimum Viable Product (experiment)
Minimum set of features, most important for your customers to validate the key value
hypothesis. This is Your first experiment.

21. Types of MVP
An MVP can be a clickable prototype, paper design, video, etc. Whatever is needed
to discover the customer needs and product-market fit as soon as possible.

22. Story behind Zappos
- Nick Swinmurn founded Zappos in 1999
- They built an efficient MVP to test a hypothesis: “Will people buy shoes online?”
- Acquired by Amazon in 2009 by 1.2 billion $

23. Death vs Success
- Webvan built a real MVP in three years and spent 800 mil $ in total without real
understanding of customer needs
- The MVP should be built in days and weeks, not in months and years. Get out of
the building as soon as possible
- The first MVP should research the problem space rather than the solution space,
to understand the customer needs and behaviors and to make informed
decisions in subsequent versions of Your product

24. Initial Customer Validation

25. Initial Customer Validation
- It is important to test commitment and validate that customers want to actually
use and buy your product
- There are 3 types of commitment: Money, Time/Usage and Reputation
- The strongest validation for an early stage startup is purchasing behavior (money
commitment)

26. Death vs Success
- Webvan got signals of the wrong kind, and they didn’t get real customer
validation before deciding to scale
- Real Validations are strong signals that indicate that people will actually behave
the way you do (e.g. purchasing)

27. Speed. How fast can you learn?

28. Be faster than your competitors
Speed is a competitive advantage, especially in a state of high competition (which is
often the case, since startups tend to launch in existing markets)

29. Use speed to learn, pivot as needed
A startup needs speed of iteration to learn as fast as possible about market and
product risks to achieve product-market fit

30. Death vs Success
- Webvan had a slow learning cycle. They spent 3-4 years before they started
understanding who are their customers and what they want
- Strive to shorten the feedback loop and learning cycle. Get out of the building as
soon as possible. Move fast to learn.
- Know what you need to learn -> have a written hypothesis
- When you understand the customer, use speed of delivery as a competitive
advantage to deliver value faster

31. Hypothesis driven development

32. Support your hypothesis with data
- Hypothesis driven development is a data driven approach to product
development
- Support your user stories, features with Success criteria to be able to measure
your assumptions validity
- Explain why you are creating something to increase buy in by team members and
also to connect features to data

33. Hypothesis user story - example

34. Death vs Success
- Webvan developed “Out of my Ass” software features that they assumed would
bring value to customers without measuring actual outcomes
- Build a hypothesis and Measure every feature impact
- Write down all your assumptions and use data to make informed decisions

35. Pivot or persevere

36. Ego comes in play
- Pivot or persevere is the most important
question when there is enough data about a
wrong hypothesis
- In order to respond objectively founders needs
to lower their ego and start using data instead

37. The Point - Master of pivot
- Andrew Mason started the Point to enable people to set collective goals
- They had One million in funding, but no growth
- By observing the data, they determined the Most successful goals are the ones
involved with buying
- They Pivoted and changed to Groupon
- Now they are Highly successful company with current market cap of ~2.7 billion
$

38. Analytics/Metrics

39. Peter Drucker - Smart guy

40. Measurement/analytics are a key part

41. Death vs Success
- Webvan was tracking wrong, vanity metrics. Mostly revenue, orders, etc. and
setting KPIs like it’s a well established corporation which understands the market.
- You should track different things in different phases of Your startup (AAARR)
- Having an insight into your customer behaviors is very powerful to inform decision
making
- Epic Tip: Document all your qualitative data (e.g. customer interviews) and share
with the team openly

42. Behavior Analytics & Insights
Ideas & Opinions any day

43. - “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”
- Jim Barksdale, former CEO of Netscape