2. 4
Startup Analytics
Teil 1
Startup Analytics
Teil 2
Till Kubelke und Daniel Hanelt
im Gespräch
Absolventen der FH Wedel und
seit der Uni über 15 Jahre
überzeugte Unternehmer
3. Validiertes Lernen
ist ein Prozess, der empirisch nachweist,
dass ein Team wichtige Wahrheiten über die
gegenwärtigen und zukünftigen
Geschäftsaussichten entdeckt hat.
Quelle: Ries, Eric (2011): The Lean Startup. New York 2011
5. ?
Was sind Metriken
bei einem Startup?
Visits
Logins
Satisfaction
Clicks
Usage
Returns
Shares
Access
Sign-ups
Downloads
Tell friends
Payments
Gross Profit
ROI
(Return on Invest)
Life Time Value
Churn Rate
Conversionrates
Month-on-month Growth
Customer Acquisition Costs
Cost per Action
Active Users
Revenue
Recurring Revenue
6. Accessible
Auditable
Actionable
3 A‘s of metrics
ties specific,
repeatable actions
to observed
results
can be
understood by
entire team
go behind the
numbers
Quelle: Ries, Eric (2011): The Lean Startup. New York 2011
7. Einfache Charts
Quelle: Maurya, Ash (2012): Running Lean: Iterate from Plan A to a Plan That Works. Sebastopol/CA 2012
http://de.slideshare.net/LeanStartupConf/ash-maurya-slides-2013
11. Quelle: Maurya, Ash (2012): Running Lean: Iterate from Plan A to a Plan That Works. Sebastopol/CA 2012
Problem
Interview
Skript
12. 1. Persönliches Feedback z.B. via
Blogs, Kunden-Interviews
2. Offene Fragen/zuhören, was Leute
sagen z.B. via Communities
3. Kundenfeedback und Bedarfe
ermitteln z.B. via Umfragen mit und
ohne monetären Anreiz
4. Substanzielles Feedback durch
Vorbestellungen z.B. via
Crowdfunding Plattformen,
Bestellungen
5. Kundenversprechen
testen/Kundensegmente ermitteln
z.B. via Test Ads
Quelle: Teten, David (2015): 10 Experiments to Test Your Startup Hypothesis, http://www.entrepreneur.com/article/243528
Weitere
Experimente
Phase 1:
Problem-
Solution-Fit
13. 6. Nutzungs- und
Verwendungsexperimente z.B.
via A/B-Testings, Prototypen-
Designs
7. Feedback über die
Verwendung z.B. Gespräche
mit echten Kunden über die
Benutzung des Prototypen
Quelle: Teten, David (2015): 10 Experiments to Test Your Startup Hypothesis, http://www.entrepreneur.com/article/243528
Experimente
Phase 2:
Product-
Market-Fit
14. 8. Kundensegmentierung z.B.
Verkaufsversprechen für welche
Zielgruppen, Google Adwords-
Analyse mit Kohorten- und
Conversiontracking
9. Channel-Analyse (welcher Kanal
erzielt die höchste Markttraktion)
z.B. Cross-Promotion, Channel-
Tests Influencer-Analyse
10. Weiterempfehlungen (mit und
ohne monetären Anreiz)
Quelle: Teten, David (2015): 10 Experiments to Test Your Startup Hypothesis, http://www.entrepreneur.com/article/243528
Experimente
Phase 2:
Product-
Market-Fit
16. A minimum viable product (MVP) is
the "version of a new product which
allows a team to collect the
maximum amount of validated
learning about customers with the
least effort“.
Eric Ries
18. Time
Test Software Test Business Model
Software Product
Concierge Product
Hardware Product
Physical Product
Test Hardware Test Business ModelTest Software
Launch
MVP
€€
Launch
MVP
In Anlehnung an: Chen, Elaine (2013): Lean Startup, Hardware Edition, http://de.slideshare.net/chenelaine/lean-startup-hardware-edition-20563840, S. 52
19. Video Trailer
Concierge MVP
Mechanical Turk
Boomerang
Analog/physical
Dry-Wallet
High Hurdle
Lean Experiment Techniques
Kramer, the Movie Expert
Quelle: Cooper, Brant (2014): Lean Experiment Techniques, http://www.movestheneedle.com/enterprise-lean-startup-experiment-examples/
20. Experiment Report | Ash Maurya
Background
What are you trying to learn or achieve?
Results
Enter your qualitative/quantitative data.
Validated Learning
Summarize your learning from the experiment.
[VALIDATED or INVALIDATED]
Next Action
What is the next experiment?
Falsifiable Hypotheses
Declare your expected outcome.
Use this format:
[Specific Repeatable Action] will
[Expected Measurable Outcome]
Details
How will you setup this experiment?
Title: [TITLE] Author: [NAME] Created: [DATE]
Quelle: Maurya, Ash (2012): Running Lean: Iterate from Plan A to a Plan That Works. Sebastopol/CA 2012
24. Activation
1st visit
happy experience
Homepage/
Landing Page
Product
Features
Was machen die Nutzer bei
Ihrem ersten Besuch?
Schlüssel-Metriken
− Pages per visit
− Time on site
− Conversions
Quelle: McClure, Dave (2007) Startup Metrics for Pirates.
25. Retention
come back
multiple usage
Warum kommen Nutzer
zurück und wie oft?
Schlüssel-Metriken
− Quelle der Wiederkehrer
− Wiederkehrrate
− Conversions
− Nutzerloyalität
− Session-Länge
E-Mails, Alerts
System-Events, Time-
based features
Blogs, RSS,
News Feeds
Quelle: McClure, Dave (2007) Startup Metrics for Pirates.
26. Acquisition
come from various
channels
Wo kommen die Nutzer her?
Schlüssel-Metriken je Quelle
− Anzahl Nutzer
− Kosten
− Conversion
SEO
SEM
Social
Networks
PR
Blogs
Campaigns,
Contents
Biz DevDirect,
Tel,TV
Domains
Apps,
Widgets
E-Mail
Affiliates
Quelle: McClure, Dave (2007) Startup Metrics for Pirates.
27. Referral
like product enough
refer to others
Wie empfehlen Nutzer das
Produkt weiter?
Schlüssel-Metriken
− % Einladungen X
− # Einladungen Y
− % akzeptierte
Einladungen Z
Viral Growth Factor = X*Y*Z
Viral
Loops
E-Mail
Widgets
Affiliates
Contests
Quelle: McClure, Dave (2007) Startup Metrics for Pirates.
28. Revenue
monetization
behavior
Wie verdiene ich Geld?
Schlüssel-Metriken
− Minimum Umsatz
− Break-even Umsatz
− Profitabilität
Ads, Lead
Generation,
Subscriptions,
Ecommerce
Biz Dev
Quelle: McClure, Dave (2007) Startup Metrics for Pirates.
29. Beispiel
Stage Conversion Status Conv. % Est. Value
Acquisition Visitors on Site/Widget/Landing Page
(2+ pages, 10+ sec, 1+ clicks = don‘t abandon)
60% $ 0.05
Activation „Happy“ 1st visit; Usage/Signup
(clicks/time/pages, email/profile reg, feature usage)
15% $ 0.25
Retention Users come back; Multiple visits
(1-3x visits/mo; email/feed, open rate/CTR)
5% $ 1
Referral
Users refer others
(cust sat >= 8, viral g factor > 1
1% $ 5
Revenue User pay; Generate $$$
(first rev, break-even, target profitability)
1% $ 50
Quelle: McClure, Dave (2007) Startup Metrics for Pirates.
30. EXPERIMENT QUEUE
Lean Dashboard | Ash Maurya
Quelle: Maurya, Ash (2012): Running Lean: Iterate from Plan A to a Plan That Works. Sebastopol/CA 2012
SUCCESS METRICS CURRENT METRICS
EXPERIMENTS
PROBLEM/SOLUTION FIT PRODUCT/MARKET FIT SCALE
KEY OBJECTIVE ACTIVE EXPERIMENTS COMPLETED EXPERIMENTS
BUILD MEASURE LEARN
AARRRKEY METRICS
REVENUE STREAMS
EXPERIMENT
REPORT
31. EXPERIMENT QUEUE
Lean Dashboard | Ash Maurya
Quelle: Maurya, Ash (2012): Running Lean: Iterate from Plan A to a Plan That Works. Sebastopol/CA 2012
SUCCESS METRICS CURRENT METRICS
EXPERIMENTS
PROBLEM/SOLUTION FIT PRODUCT/MARKET FIT SCALE
KEY OBJECTIVE ACTIVE EXPERIMENTS COMPLETED EXPERIMENTS
BUILD MEASURE LEARN
20
Customers
200
Customers
2,000
Customers
8 weeks from
now
1.5 years from
now
3 years from
now
Acquisition Activation
Revenue Retention
Referral
1,000
100%
800
80%
400
50%
200
50%
200
25%
$ 20,000
MRR
Oct 1
1-Page SaaS
Metrics will
resonate
strongly
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Title
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32. Till Kubelke und Daniel
Hanelt im Gespräch
Absolventen der Hochschule und
Entrepreneure seit der Uni
35. Lean Stack
Quelle: Maurya, Ash (2012): Running Lean: Iterate from Plan A to a Plan That Works. Sebastopol/CA 2012
1 Lean Canvas
2 Lean Dashboard
3 Experiment Report
Why
How
What