CUSTOMISED PHOTO DATA SEARCH

Transcription

1 IMAGERIES 1 CUSTOMISED PHOTO DATA SEARCH HKFBS Business Administrative Paper 2017 Brought to you by Imageries

2 IMAGERIES 2 The Team ABOUT US Imageries proposes a personalised image recognition system named Customised Photo Data Search. Customers will then be recommended suitable matching fashion products based on their photo data without having to enter key search terms. We believe that Customised Photo Data Search is the next big image recognition solution that can revolutionise the online shopping experience. JAMES LIU SONG YU FOUNDER Business Analytics, Data Science, Machine Learning, Statistics NG SI HAN CO-FOUNDER Accounting, Finance, Marketing, HR

3 3 IMAGERIES 10:00 11:00 AM WELCOME MESSAGE Investment generally results in acquiring an asset, also called an investment. If the asset is available at a price worth investing, normally expected either to generate income, or to appreciate in value Today s Agenda Introduction & Current Gap Rising Trend Proposed Business Idea Customer Segmentation & Strategies Feasibility & Profitability Product Enhancement Potential Conclusion 11:00 12:00 PM ABOUT US Investment generally results in acquiring an asset, also called an investment. If the asset is available at a price worth investing, normally expected either to generate income, or to appreciate in value 12:00 01:00 PM MEET THE TEAM Investment generally results in acquiring an asset, also called an investment. If the asset is available at a price worth investing, normally expected either to generate income, or to appreciate in value 01:00 02:00 PM OUR PORTFOLIO Investment generally results in acquiring an asset, also called an investment. If the asset is available at a price worth investing, normally expected either to generate income, or to appreciate in value

4 IMAGERIES 4 E-commerce Landscape Highest record of 22.1 online transactions made per person per year in Asia Rising affluence of Asia s middle class E-commerce activities grow at over 23% per year with increasing emergence of new online shopping websites Introduction & Current Gap

5 IMAGERIES 5 Gap in Current E-commerce Experience Current online shopping recommendation tools use mainly collaborative filtering Lacks direct personalisation PREVIOUS PURCHASES Checked out by user OTHER PURCHASES Made by other users BROWSE HISTORY Cookies Introduction & Current Gap

6 IMAGERIES 6 Image Recognition The rising trend Gained popularity in recent years with the advent of deep learning model Adopted by companies such as Clarifai, ViSenze and Fashwell which provides a variety of image recognition solutions Includes Reverse Search, In-Video Search, Automated Product Tagging Rising Trend

7 7 IMAGERIES About Our Proposed Idea What s New? Using Customised Photo Data Search which taps on photo data stored in their devices What are we selling? A personalised image recognition software that can be implemented by fashion and ecommerce websites What is our solution? Linking the processing of user photo data on either their smartphones or computers with the image recognition system Proposed Business Idea

8 IMAGERIES 8 The following is a rundown of the prototype. Reebonz is a fashion e-commerce company that we have decided to use as an example. 1st Step Reebonz asking for permission to access user photo data 2nd Step User photo data (user carrying a Gucci handbag) retrieved from his/her phone 3rd Step Reebonz processes the photo data and through image recognition, recommends the user her matching fashion products at the homepage without the user having to key in any terms Proposed Business Idea

9 IMAGERIES 9 Unique Selling Points We believe that at Imageries, we are unique. ONLY CUSTOMISED PHOTO SEARCH SOLUTION CONVENIENCE CUSTOMISATION Proposed Business Idea

10 IMAGERIES 10 Customer Segmentation Demographic Size 1 2 Technological Capabilities 3 Growth Potential Middle to large-sized fashion E- commerce firms such as Reebonz, H&M, Zalora, Qoo10 Love, Bonito Usually more established and looking for better solutions to increase conversion rates Such firms usually have strong IT teams Lack IT expertise in the area of image recognition Experiencing growth in their online sales and has financial capabilities to expand The reason for targeting this group of fashion E-commerce firms is mainly because these firms do not yet use Customised Photo Data Search technology solutions in their recommendations. Proposed Business Idea Customer Segmentation & Strategies

11 IMAGERIES 11 B2B Marketing Strategies PRE-SALES Produce Webinars and Videos to benefit customers Host customer conferences POST-SALES Business Exhibitions-IBC Asia & UBM Asia ing potential E-commerce retail players in the market and providing trial session SALES Build a tech support team Develop customer relationships Customer Segmentation & Strategies

12 IMAGERIES 12 Feasibility/ Evaluation Strengths Weaknesses Opportunities Threats Customised E-commerce experience First-mover advantage Customers might not be receptive initially Off-the-shelf software requires further customisation Increasing usage of E-commerce websites Increasing demand for personalised online experience Largely improved accuracy of image recognition Easily replicated by large retail firms Highly competitive in the software industry Feasibility & Profitability

13 IMAGERIES ,000 Total Sales VS Total Costs VS Accumulated Profits Profitability Subscription Monthly Pricing Average Price of $2,000 per user Estimated Costs : Costs of Software Development, costs of Server Maintenance, Costs of Patent Application Dollars 300, , , , ,000 Breakeven in 4th year with a profit of $68, , Total Sales Total Costs Accumulated Profits Feasibility & Profitability

14 IMAGERIES 14 PRODUCT ENHANCEMENT Imageries believe that Customised Photo Data Search can be applied to different industries as well based on the following factors: An average user has a large data of photos stored in either his phone or on computer A user s personal taste and preference can be inferred from the photo data The potential is endless Product Enhancement Potential

15 IMAGERIES 15 Live Demonstration Prototype Conclusion

16 IMAGERIES 16 In 2018, E-Commerce will see much better 1:1 personalisation. It s going beyond just recommended products based on everyone else s buying habits, and instead, giving catered recommendations based on individual preferences. William Harris Founder & Growth Marker of Elumynt, LLC Conclusion