Semantic Web--Funding Analysis (Technical Insights) D2A2-TI March 2011
Table of Contents Executive Summary Research Outline Key Findings Research Methodology 1. Sectoral Analysis Current Technology Trends and Roadmap Governmental Grants and Stimulus Funding GAP Analysis: Technology Developer Community –Need for Funding 2. Assessment of Investor Ecosystems Investor Networks and Recent Investment Climate Future Plans and expectation of Investors
Table of Contents 3. Analyst Insights and Recommendations Investment Prospects & Opportunity Evaluation for Investors Smart Scouting & Procurement Strategies for Developers Key Contacts Hot Funding Deals About Frost & Sullivan
Key Findings 1 Twelve different semantic implementations have received funding in 2010 and early 2011. Nine different semantic implementations have been identified with scope for investments 2 Venture Capitals, Private Equity Investors and Angel Investors are the major financial contributors. The investment climate for the semantic web space was not very warm for the start ups. Big funding deals were sparse and accompanied by slightly higher number of smaller funding deals 3 Semantic Search Engines are expected to become prevalent in 2011 and the years ahead. Semantic Search could bring in new functionalities by providing direct as well as aggregated responses to factual queries posed 4 Companies which have acquired minimal initial capitalization, have been successful and then went for more traditional funding in a bigger round. Moreover, such products focus on catering to customer needs rather than concentrating on enhancing the capabilities of the core technology Venture Capitals would look forward to invest in companies which have a rich Intellectual Property portfolio. Mere execution plays with weak underlying technology are unlikely to attract funds, and customers in the long run Companies trying to venture into the semantic space should concentrate on developing solutions or add-ons that could address limitations of key participant solution offerings. For instance, refining search engine results and interesting add-ons for social networking ecosystems would add value Application arenas with a well defined business use case model and a definitive purpose of usage have acquired funding in the recent past. Semantic based mobile and web applications, which are bound to attract more consumers from the social computing space have been the areas of major interest for the funding agencies 5 6 7
Semantic Search - Technology Focus AreaCurrent Technology Trends (Contd…) SEARCH ENGINE EVOLUTION RDFa HTML5 Enhanced Visual Querying By Semantic Semantic Search Clustering and Visual Search Keywords Search Engine Semantic Indexing Search Engine Optimization (SEO) SEMANTIC SEARCH – THE PATH AHEAD Unstructured data could be organized and connected to deliver meaningful and customized search results Semantic search could help in refining search along two dimensions 2011 could witness more activities and efforts taken towards structuring data Structuring of information and data could eventually bring software agents back into the spotlight On the other hand, intelligent analysis of structured information to gain a deeper understanding is also bound to occur
GAP Analysis: Successful Deals and Need for Funding Companies which have realized that semantic space has more convergence than technology segmentation have been able to procure funds. A holistic systems approach to deliver a menu of models and algorithms for varied purposes has attracted funds Scientific research projects with limited applicability are of little interest to the funding bodies as they lack the potential to meet the in-demand commercial needs Application developers have been successful in acquiring indirect form of funding by selling or licensing their inhouse technologies or products. For instance Europe based Talis has acquired 18 million euros, by selling their library division Companies which have acquired minimal initial capitalization, have been successful and then went for more traditional funding in a bigger round. Moreover, such products focus on catering to customer needs rather than concentrating on enhancing the capabilities of the core technology Lack of business use cases and definite business models restrict funding inflow. Openly available data sources which have poor business models acquire negligible financial incentives since there are no serious investments due to the free model GAP ANALYSIS - Need For Funding Solutions competing against big competitors would require surplus amounts of funding and is accompanied by a high risk factor. Hence this has been an area of negligible interest for investors However, VC division of corporates and other key participants show interest in niche targeted search engines that are capable of rapidly enhancing existing services Companies have been successful in attracting Series A funding compared to others. Founders and investors in early stage seem to prove more on less capital. Series B and other later series funding investments translate to growth and financial aspects unlike Series A which is procured for the innovation or idea and hence has been difficult to procure Start-up companies like Bueda and AlphaLabs which have leveraged on the data explosion over the internet have good funding inflow
Promising Technology Segments for InvestmentInvestor Networks and Recent Investment Climate Key Areas of Investment Social Media Platform Open Data Platform Semantic Search Platform Content Management
The twelve key areas of investment in the semantic space for the year 2010 and early 2011
Major funding sources include Venture Capital firms, Private Equity firms and Angel Investors
Applications with the potential to serve diverse industry verticals have attracted investors
Advertising Tools Text Analysis Social Analytics Metadata Storage Platform Enterprise Processes Semantic Mobile and Web Apps Data Sets Querying Consumer Insights
Investment Prospects & Opportunity Evaluation for Investors Harvey Balls Table – Sneak Preview and Need for Evaluation
The Investment Prospects and Opportunity Evaluation for Investors is assessed by making use of the Harvey Balls Table
The purpose of this model is to rate the factors/characteristics/drivers/challenges affecting the technology. The shading of the harvey balls indicate (0-1-2-3-4)/(Low, Low-Med, Med, Med-High, High). The table shows the composite rating of each characteristic in the short, medium and long term (or in different regions)
The Harvey Balls table has been employed to assess the funding prospects based on four different criteria
Return On Investment (ROI): This reflects the prospect of the technology domain under consideration to deliver expected returns. A darker shading reflects the domain with relatively higher ROI.
Market Requirement (MR): This reflects the demand for the solution in the market which is created either by the technology push or market pull. A darker shading reflects the domain with high demand.
Time Line (TL): The timeline refers to the duration from research stage to commercialization of the solution. A solution that is likely to have a longer time before it is commercialized is represented to be having weak investment prospects (white harvey ball).
Market Concentration (MC): Market Concentration is based on the presence of start up companies or established ventures seeking investments. More the companies in need of funds, higher the market concentration and hence high investment prospects (represented in a darker shade)
The nine segments of the semantic space have been chosen on the basis of the viability and capability in terms of performance.
Low High Investment Prospects & Opportunity Evaluation for Investors (Contd…)
Low High Investment Prospects & Opportunity Evaluation for Investors (Contd…)
COLLABORATION STRATEGY INNOVATION STRATEGY RESEARCH STRATEGY PROCUREMENT STRATEGIES LICENSING STRATEGY INTELLECTUAL PROPERTY PRODUCT DEVELOPMENT STRATEGY Smart Scouting and Procurement Strategies for Developers
Viable Applications - Business-to-Consumer ModelSmart Scouting Strategies for Developers (Contd…) Personalized Task Manager Semantic Mobile Applications Semantic Social Networking Applications Semantic Desktops and Webtops E-learning Viable Applications for B2C Semantic Wikis Search Engine Enhancers Semantic Instant Messaging Web Browser Enhancement Intelligent User Interfaces