The Text Analytics Market(s)

Transcription

1 The Text Analytics Market(s) Competitive landscape and trends by Curt A. Monash, Ph.D. President, Monash Research Editor, Text Technologies

2 8 linguistics-based businesses Web search Public-facing site search Enterprise search & knowledge management Custom publishing Text mining and extraction Spam filtering Voice recognition Machine translation

3 Web search Giant oligopoly It's a huge business It's consolidating down to two vendors that matter If anybody but Google matters at all Startups aren't gaining traction Three kinds of search Navigational Informational Transactional

4 Web search vendor issues today Physical efficiency Adversarial information retrieval Monetization Regulation Branding

5 Future web search issues Better popularity metrics Better use of context Geography!! Sub-page retrieval Looking through security barriers Better UIs

6 Public-facing site search It has dual goals What the user actually wants What you want the user to see E-commerce and general search are separate businesses E-commerce = province of smaller vendors General = province of search, portal, or CMS vendors Hand-tagging is key

7 Enterprise search & KM (inward-facing) For decades there was only one kind of text analytics but that was asking too much of one technology Now enterprise search is more circumscribed but things are still convoluted Complex needs Multiple kinds of search Unique technical challenges Multiple purchase drivers Confused market One-size-fits-all strategy Users want portal integration Investment is fragmented

8 Kinds of enterprise search Find a specific document Find an answer Find ALL documents Find an expert

9 Technical challenges in enterprise search Documents may not exist Many formats Corpus weighting No good popularity metrics Security Ease of adoption!!!

10 Many reasons to buy enterprise search General productivity Sure beats looking through file cabinets Wouldn't it be nice if... KM dreams Compliance Thou shalt Not all the reasons are good

11 One-size-fits-all didn't work Overreaching had a lot to do with that E-commerce search isn't general search Text mining isn't search (or clustering) Custom publishing isn't exactly search

12 Custom publishing More precise than search Sophisticated extraction Focus on document parts Started with technical publishers (and intelligence) Expanded to Other technical documents Other publishers Players Mark Logic Various text miners Various search vendors

13 Bollixed enterprise search market landscape Multiple generations of vendors flamed out Verity Excalibur (endlessly backed by Allen & Company) Fulcrum et al. FAST Google has brand name, ease of installation Microsoft, Oracle, SAP, and Autonomy are all confused Products are sold for inappropriate apps Compliance is driving demand Small vendors are... small

14 Text mining Really about sophisticated extraction Apps and verticals mirror data mining The action is in sentiment analysis and ease of use Otherwise the industry seems tired

15 The original text mining apps: Early warning Source: July, 2006 post on Text Technologies Vehicle safety Other manufacturing/warranty analysis apps Reputation management Other customer sentiment apps Anti-terrorism Sarbanes-Oxley compliance (continued )

16 More early warning ( continued) Antifraud Stopping money laundering Clinical applications (some) Early insurance risk management apps Early experimental hedge fund apps Employee (dis)satisfaction (missing from the original list)

17 Customer/market intelligence Now drive text mining growth Internal Voice of the Customer came first Voice of the Market has blended in Sales, buying, and delivery practices are in line Departmental buying SaaS delivery Many vendors focus(ing) on this segment: Attensity Clarabridge SAS SPSS Expert System S.p.A

18 Three ways to use text mining Business intelligence Reports, dashboards Attensity, Clarabridge Predictive analytics Data mining SAS, SPSS Custom publishing nstein et al. Lots of partnerships

19 Six trends that could shake up the market Web/enterprise/messaging integration BI integration Universal message retention Portable personal profiles Electronic health records Voice command & control

20 Further information Curt A. Monash, Ph.D. President, Monash Research Editor, Text Technologies