right image r&d
TRANSCRIPT
Right Image R&DAI that maximizes CTR of your marketing visuals
April 2016
1. Problem: slow A/B testingContext: suboptimal marketing content leads to lost sales
+41%
-51%
Our successful manual A/B testing case:6x increase, lasting impactMobile Game. Genre: Strategy.
Start of app store page optimization
Monthly installs by device
+480%Lasting impact achieved: 5-6x average monthly installs lift
2. Solution: instant image ranking
Applications:o Mobile app icon & screenshotso Ad banners etc.
3. Market: mobile app promotion
o Mobile app market: –$40 billion / year–5-year CAGR: 20%–Mobile app promotion market (est.): $4-8B
o Concentrated: –85% of revenue comes from games–2% of app developers claim 54% of all app revenues
Source: App Annie Report: http://files.appannie.com.s3.amazonaws.com/reports/App-Annie-02-2016-Forecast-EN.pdf?aliId=80125619http://www.techrepublic.com/article/mobile-developers-should-spend-less-time-on-development-more-on-marketing/
4. Competitiono Self-serve A/B testing platforms
o A/B testing platforms that provide clickers
o RightImage R&D competitive advantage: –Automation, enabled by AI–Quick results at low cost
5. How it works: learn from SM images
Apply analysis to marketing visuals
Usage-based, to be decided:
● Charging for every target action we’ve added
● Charging for volume of tested pictures
6. Business Model
7. Marketing
o Direct sales to massive app owners
o SEO & landing page (planned)
o Affiliated marketing agencies
8. RoadmapNow: 1 served customer
July 2016: 5-10 manually served customersJuly 2016: AI proof of conceptSep 2016: first customer served with AI
9. TeamMichael RybakStrategy, R&D
Interests● Human perception & behavior● Algorithms & optimization
Experience● 3 years as an R&D team lead● 12 years as research engineer● 2 years as a project manager● 2 years as CEO & Coach of a
soft skills trainings startup
Education● 3 postgraduate programs in
management & leadership ● Red at TopCoder● Bronze medal at ACM’2003● Bronze medal at IOI’2001 ● M. Sc. in Computer Science,
Kyiv Shevchenko Univ ’2007
Mykola KomarevskyyStrategy, Business Development
Denis TroyanovR&D
Interests● Deep learning & computer
vision, neuroscience & AI
Experience● Video stream analysis
○ fire-detection system○ for warehouse safety○ commercially applied
● Computer vision for audience analysis:
○ 20%+ precision raise of face-processing technology core of a running business
Education● Computer vision school● B.Sc. in Computer Science
Interests● Technology in business and
society, machine learning
Experience● 7+ years of leadership in
software (cofounder, business development, CTO, product)
● 2+ years at McKinsey & Co., Business Technology
Education● MBA, Thunderbird School of
Global Management, USA● B.Sc. in Computer Science,
Shevchenko University of Kyiv● Coursera courses: Machine
Learning, Big Data, IoT
Your feedback & ideas
● Ecosystem○ Products?○ Technologies?○ Other applications & markets
of image sentiment ranking?
● Partnership○ Interested to become our beta client?○ Interested to become a partner (marketing agency)?○ Know someone who could be interested?
● Team○ Known ML specialists?
