using unstructured text data to stay ahead of market trends and quantify customer perception

Using Unstructured Text Data to Stay Ahead of Market Trends and Quantify Customer Perception

Presented by:Swaroop Johnson, Consultant (Analytics)

July 13, 2016

of data generated is unstructured in nature, and growing exponentially

of business executives complain that they have too much unstructured text data and are unable to interpret them

There are incremental insights to be generated from the text data given willingly by your customers

Our text analytics services cover all phases of the product life cycle, and the customer journey

Imagine being able to predict future trends before it actually happens

And then design a product based on customer feedback, and product reviews

And track each customertouchpoint to identifycustomer queries andevaluate your customerexperience program

To evaluate net sentiment of your customer base with deeper analysis and insights than ever before

Discover a new side of story telling by

discovering hidden insights from unused

sources of data

80%

40%

© 2016 Blueocean Market Intelligence

Enabling incremental insight generation through comprehensive coverage of data sources

New Product Development• Key opinion leader blogs• Feedback/comments• Product reviews

Customer Interaction Analysis• Call centre data• Feedback/comments• Call logs

Digital Research• Technology blogs and forums• Technical papers• Journals and magazines

Customer Experience Management•Microblogging sites/social media data• Feedback/user comments• Product reviews

Brand Monitoring• Customer feedback• Survey Data• Social media/Twitter data

Fraud Detection• Emails•Historical claims documents• Financial statements

Some Practical Applications of Text Analytics

© 2016 Blueocean Market Intelligence 4

Aspect Extraction Text Classification Sentiment Analysis

Summarization Article Extraction Topic Modelling

Our Solutions

T

Customer Experience Management

Time and cost for identification of customer and employee issues will be reduced

Brand Monitoring Help companies to keep a tab of the health of their companies brand image by analyzing trends over a period of time

Digital ResearchReduces time related to topics and document searches by grouping documents

Examples

• Extract interesting and non-trivial patterns or knowledge from unstructured text documents• Identify different aspects /components of a single problem• Overall sentiments for a specific aspect under the business scenario can be extracted• Determine the underlying conditions that give rise to the reasons for the problem/phenomenon

“the restaurant is situated at an excellent location and the food is very delicious. there are fresh barbeques served over the table as starters including vegetables mutton chicken fish and prawns. all too good to enjoy. the main course and desserts are available over the buffet table and the food variety is quite a lot to choose from both between veg and non-veg. well maintained and good seating arrangement ideal for business parties or with friends. the only drawback was that the seats are limited and during rush hours the guests need to wait until they get their turn. however it was a very good eating experience along with work mates.”

Information extraction for deeper analysis of the business problem

Net Sentiment

0.489 (indicates positive sentiment)

Different aspects of the user review

Location Excellent

Food Delicious

Reservation Bad

Experience Good

Service Good

Entities

Variety Excellent

Non veg Good

Main course Bad

Barbeque Fresh*

Desserts Good


Topic Modelling to Understand Customer Perception

Based on the article that we identified we were able to extract insights relevant to the marketing, and competition for XXX’s new YYY range of processors

Topic modelling and article extraction solutions were deployed to create a story that divided the entire 384 comments into 20 topics

These insights can be used to understand what customers are speaking and how they perceive Intel’s new range of processors, as well as evaluate the marketing and branding strategy

Customers have expressed that YYY processors enable power savings

Marketing Insights

Customers feel YYY X86 provides high performance with low power consumption

End users feel YYY processors are worth upgrading to as it a good improvement over previous generations

Oracle’s AAA solves the heartbleed issue

End users consider AAA to be a bit expensive

Customers have rated XXX’s X86 processors as the most efficient out there beating AAA

Competitive Insights


Breaking down consumer reviews to aspects so as to understand purchase drivers, and drivers of positive, and negative sentiments (1 of 3)Client: Technology

Approach

Industry: Technology/Product/Smart Watch

Business Challenge The client, one of the leading chipset manufacturers wanted to understand the fall in

demand for its in-house smart watch product by studying consumer reviews from two most popular online retail channels amazon.com, and bestbuy.com

The partner wanted to identify top purchase drivers, and identify the reasons behind negative sentiments, and the top activities the fitness tracker was used for

Aspect Extraction

• Identifying the key purchase drivers

• Understand drivers of positive, and negative sentiments

• Top use cases of the product were identified

• Time wise trends with drill down abilities to identify reasons for declining trend

Business Impact:

Lexicon Based POS Tagging

Tools used:UTAP, R, Python, KWIQVIS, SQL Server 2014,

14© 2016 Blueocean Market Intelligence

Breaking down consumer reviews to aspects so as to understand purchase drivers, and drivers of positive, and negative sentiments (2 of 3)

Results

Identifying the key purchase drivers

Understand drivers of positive, and negative sentiments

Top use cases of the product were identified

Business Impact:

Wrist Band Painful, Wears, Complaint, Flawed,

Issues, Irritation, Return, Burn

Sync Crashed, Restart, Fiasco, iPhone,

Unstable, Sadly

REM Validity, Quality, Incorrect, Poor

Bluetooth App, Phone, Unpair, Mediocre, Worst

Fitbit Versus, Comparison, Awesome,

Biking

Firmware iPhone, Confusion, Pathetic,

Miserable, Fix, Crappy, Unresponsive

Top Aspects across Star Ratings And Their Associations1 and 2 star rating 3 and 4 star ratings 5 star rating

Battery Life Phenomenal, Fantastic, Charge,

Reliable, Activities, Great

Screen Impressive, Suit, Pretty, Customize,

Perfect

App Phone, iPhone, Mapmyrun, Pair,

Update, Comfortable, Great, Personalized

Heart rate Accuracy, Appreciate, Run, Reliable,

Fantastic, Customizable, Notifications, Swimming

Waterproof Shower, Heart rate, Notification,

Appreciate, Traveling, Reliable, Swimming

Notification Text, Voicemail, Smart, Calendar,

Reminders, Customizable

App Phone, Update, Watch, Interface,

Sync, Good, Annoy, Reconnect

Heart Rate Sleep, Aerobic, Dancing, Positives,

Runners, Comfort, Stylish, Accurate

4% 8% 19% 4% 26% 32% 7%

Highly Negative Negative Slightly Negative Neutral Slightly Positive Positive Highly Positive

Aspect Extraction


Breaking down consumer reviews to aspects so as to understand purchase drivers, and drivers of positive, and negative sentiments (3 of 3)Output

An interactive dashboard to enable understanding of customer perceptions, enabling the partner to identify drivers of positive, and negative sentiments, based on time wise trends.

Consumer reviews are color coded with star ratings distributions, with drill downs available, for each individual sentiment, and particular aspect

Aspect Extraction


Introducing

• User friendly, flexible user interface: One touch data pre-processing (removal of junk/stop words/URLs, lemmatization etc...)

• Automated text classification: Query classification for deeper and better understanding of customer queries

• Makes text classification 60% faster than traditional methods

• Preview screens for data extraction, and data cleansing

• Sliders and input boxes for easy definition of parameters and data split

• Pre-defined classification and sampling performed with the click of a button

• Get Accuracy Score, Confusion Matrix Score and Classification Report to be downloaded in .pdf/.doc format

Unstructured Text Analytics Platform (UTAP)


WINNERInnovative Technology of the Year 2016

Big Data and Analytics Awards

Low cost per comment, making it economic for large data volumesEconomic

Ability to handles millions of rows of textual data per dayScalability

Each step of the unstructured text classification process is pre-builtAutomated

Comprehensive coverage of data sources (structured and unstructured)Comprehensive

Value add through innovative platforms


Summary

80% of data generated today is unstructured in nature – CANNOT be ignored any more1

2

3

5

4

Call center data, social media comments/posts, open ended survey data etc. are some of the sources of unstructured data

Incremental insights related to customer perception/trends/sentiments can be extracted by mining unstructured data

Determine the underlying conditions that give rise to the reasons for the sentiment/perception/customer issue

Unstructured Text Analytics Platform (UTAP) make the text classification exercise easier, faster, and efficient

Digital Research help companies stay ahead in identifying upcoming trends6


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www.blueoceanmi.com

Thank YouFor more information: Swaroop Johnson

Consultant (Analytics)

Blueocean Market IntelligenceEmail: [email protected] Website: www.blueoceanmi.com

United States| United Kingdom | Dubai | India | Singapore

http://www.blueoceanmi.com/

mailto:[email protected]

using unstructured text data to stay ahead of market trends and quantify customer perception

Data & Analytics