Prof. Timothy Shea Charlton College of Business Southcoast E-Commerce Conference 2015

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1 Prof. Timothy Shea Charlton College of Business Southcoast E-Commerce Conference 2015

2 Web Analytics (a little) Text Analytics CEC: Customer Experience Management Final Video

3 The measurement, collection, analysis, and reporting of internet data for purposes of understanding and optimizing web usage Digital Analytics Association Google Analytics is the most popular

4 } Visit/Session Times someone interacted with the website } Bounce Rate The percentage of visits that are single page visits } Page View The time a single page (or a blog, duration Ad Banner...) is on the screen } Click Path The chronological sequence of page views within a visit or session There are many more

5 Who are my visitors? Are they who I want / target audience What are they doing (or trying to do)? What are they clicking on / not clicking on Are they getting it done? Are they able to complete their tasks easily? How can I get more of the people I want to the web site?

6 } The business goal is to complete a purchase: Home page 13,944 Search for ticket 11,924 Review Search Results 5,540 View Invoice 3,474 Submit Payment 2,829

7 } Definition: The process of deriving high-quality information from text or other unstructured data sources. Often includes Natural Language Processing percent of all corporate data is in some kind of unstructured form (e.g., text social media, , etc.) Unstructured corporate data is doubling in size every 18 months Tapping into these information sources is not an option, but a need to stay competitive

8 Law (court orders) Academic research (research articles themes) Finance (quarterly reports) Medicine (discharge summaries) Biology (molecular interactions) Technology (patent files) Marketing (customer comments) Government (web sites, e.g.,.pdf files)

9 } Youtube video Tutorial: Creating a Word Cloud at Wordle

10 Definition A technique used to detect favorable and unfavorable opinions toward specific products and services } Youtube video Sentiment Analysis: Feelings, not Facts Based on Twitter comments Negative: 27% Positive: 73%

11 Gartner s Magic Quadrant for Business Intelligence and Analy8cs Pla:orms h=p://www.gartner.com/technology/reprints.do?id=1-2ah4q85&ct=150224&st=sb

12 Product Name URL Angoss Knowledge WebMiner angoss.com Click Tracks clicktracks.com LiveStats from Deep Metrix deepmetrix.com Megaputer megaputer.com MicroStrategy microstrategy.com R Studio RapidMiner rapidminer.com/ SAS sas.com SPSS spss.com Web Trends webtrends.com XML Miner scientio.com

13

14 Feedback pretty good -- actions, especially integrated actions less so

15 Unstructured data

16 Collect more competitive data GE: Used a combination of feedback from its own customers, information from competitors brochures, general market data to uncover a popular service capability that it s competitors offered but GE did not. Enhance Key Driver Analysis Gaylord Hotels: Uncovered complaints about room noise. While not the highest volume complaint topic, room noise was highly correlated to a wouldn t recommend or wouldn t return score.

17 Build Sentiment-Based KPIs Verizon: Using social media data to analyze customer feedback after Hurricane Sandy, Verizon noticed customers in the impacted areas displayed very negative sentiment. The company uncovered the root cause (many customers moving into overage charges), devised a solution (waive overage charges for certain area codes) and communicated the change to customers. It saw sentiment return to normal within 24 hours of the customer communication

18 Test Hypotheses When EMC suspected language barriers were impacting the experience at its customer support locations, it turned to text analytics to investigate the hypothesis. It found the hypothesis to be true and implemented several changes (accent reduction training, opening up a customer service center in USA sentiment improved dramatically. Make Communications Adjustment Orbitz: Reviewed feedback after launching its new rewards/loyalty program. The text analytics identified customer confusion and led the company to clarify its policies and marketing communications for the program. Loyalty program grew dramatically.

19 } See: Big Data and the Rise of Augmented Intelligence: Sean Gourley at TEDxAuckland

20 THE END Q&A

21

22 } Integration of information gathered over the World Wide Web (including unstructured data). Web mining is used to understand customer behavior, evaluate the effectiveness of a particular Web site, and help quantify the success of a marketing campaign Content mining is used to examine data collected by search engines and Web spiders Usage mining is used to examine data related to a particular user's browser as well as data gathered by forms the user may have submitted during Web transactions.

23 Hit Single page visit Page view Bounce rate Event Exit rate Visit Page time viewed First visit Session duration Unique visitor Average page view Repeat visitor duration Return visitor Engagement time New visitor Page views per Impression average session Click path

24 User / Customer Website Weblogs Pre-Process Data Collecting Merging Cleaning Structuring - Identify users - Identify sessions - Identify page views - Identify visits Extract Knowledge Usage patterns User profiles Page profiles Visit profiles Customer value How to increase the customer value How to improve the Web site How to better the data

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