2016 xug conference big data: big deal for personalized communications or meh?

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XUG Conference Atlanta, GA November 14, 2016

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Page 1: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

XUG Conference Atlanta, GA

November 14, 2016

Page 2: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

● What is Big Data and why is it important?● How is Big Data being used for Marketing?● Big Data is a driver of Artificial Intelligence?● What is a Graph? Graph Database?

Accepting questions

goo.gl/slides/zzjzkj

Page 3: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

...or is it just ¯\_(ツ)_/¯

❏ Big Data

❏ Semantics

❏ Patterns

❏ Paths

❏ Answers

❏ Insights

Page 4: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Big Data

Page 6: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Beyond the Hype is Big Data Analytics

http://www.sciencedirect.com/science/article/pii/S0268401214001066

Text analyticstechniques that extract information from textual data.● Information extraction ● Text summarization● Question answering ● Sentiment analysis

Social Media analyticsanalysis of structured and unstructured data from social media channels.● Community detection● Social influence

analysis● Link prediction

Predictive analyticstechniques that predict future outcomes based on historical and current data.● Regression

techniques● Machine learning

techniques

Page 7: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Analytical Techniques

Page 8: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Why Big Data: Big Actionable Insights

Big Data NoSQL databases like MongoDB, CounchDB, Cassandra, DynamoDB, MarkLogic, and Neo4j.

Big Data processing tools such as Apache Hadoop, HDFS, HBase, MapReduce , Spark...

“data mining,” “data modeling”“predictive modeling.”

Page 9: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

● Big Data often uses a different, simpler, semantic data model

● Data is easily added and similar but different data is relatable

● Powerful tools allow new knowledge to be discovered and explored

Page 10: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Semanticsəˈ

Semantic data models utilize Graph data structures to link things to properties and to other things (think things not strings).

With the form Object - RelationType - Object.

For example:

Page 11: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Things not Strings

Page 12: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

_RA name: “Zushi Zam”_RB name: “iSush”

_RA LOCATED IN _P1_RB LOCATED IN _P1

_P1 location: “New York”

Graph Databases

_0 IS_FRIEND_OF _2_0 IS_FRIEND_OF _1

_2 LIKES _RA_1 LIKES _RB

_RB SERVES _C0_RA SERVES _C0_C0 cuisine: “Sushi”

Page 13: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Fuzzy Similarity

_bday1 birthDate “10-Oct-1799”_bday2 birthDate “Abt. 1798”_bday3 birthDate “09-Oct-1798:

_person perfBirthDate _bday1_person altBirthDate _bday2_person altBirthDate _bday2

Page 14: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Big Data and Linked Data

● Semantic data models basis for Linked Data● Open Datasets can extend LD objects● Linked Open Data (LOD) repositories offer

50B+ triples with 10B in DBpedia alone

Page 15: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Big Data -> Artificial Intelligence

1. Big Data

2. Cheap parallel computation

3. Better algorithms

“Fueled by technology advancements (e.g. big data processing power, advanced machine learning, predictive analytics and natural language processing) and by the marketing engines of tech heavyweights, media are latching onto AI as the next big technology trend.”

https://www.wired.com/2014/10/future-of-artificial-intelligence/

Page 16: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Artificial Intelligence Marketing Race

AI in common use● Search● Recommendation Systems● Programmatic Advertising● Marketing Forecasting● Speech / Text Recognition● Recommendations● Fraud and data breaches● Social semantics● Website design● Product pricing● Predictive customer service● Ad targeting● Speech recognition● Language recognition● Customer Segmentation● Sales forecasting● Image recognition ● Content generation● Bots, PAs and messengers

AI rapidly developing● Image recognition● Customer Segmentation● Content Generation● Personalization● Personalize Content, ● Recommendations and ● Site Experiences ● Lifetime Value (LTV) Algorithms● Whole Journey Optimize● Personalized Recommendations● A/B/N Testing to Create Unique,

Optimized Experiences

Page 17: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Will AIs want to use Electric Toasters?

“Blade Runner: Do Androids Dream of Electric Sheep? “

“AI is the new electricity,” he says. “Just as 100 years ago electricity transformed industry after industry, AI will now do the same.”Why Deep Learning is Suddenly Changing Your Life

“AI is like electricity, and that when it was first incorporated into appliances they were referred to by names such as “the electric toaster.” Now it’s just a toaster. ”Salesforce Einstein Proves that AI is Relative

Page 18: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Patterns

● Knowledge Representation

● Pattern recognition ● Machine Learning

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Machine Learning Deep Learning

● Facial recognition● Voice analysis● Best path analysis

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Customer Journey Modeling

● Patterns and goals● Machine Learning● Unsupervised Learning

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Append Enhance Expand Infer

AI as a Service IBM● IBM AlchemyLanguage● IBM Conversation● IBM Retrieve and Rank● IBM Personality Insights

AI as a Service Google● Prediction API● Sentiment Analysis● Purchase Prediction● Spam Comment Detection

AI as a Service Microsoft● Computer Vision API● Emotion API● Face API● Bing Speech API● Linguistic Analysis API● Text Analytics API● Recommendations API

AI as a Service Amazon● Content Personalization● Propensity Modeling● Customer Churn Prediction● Solution Recommendation● Amazon Alexa

Page 22: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Personality Propensity?

● Analytics vendors user Personality Profiles for messaging / targeting

● Richer models helped marketers to understand and predict behavior

● Use data that is available in datasets such as Acxiom and Experian

● Leverage digital content such as individual writing example or self-improvement surveys

Page 23: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Example: IBM Personality Insights

You are likely to...● be sensitive to ownership cost

when buying automobiles● have spent time volunteering● prefer quality when buying clothes

You are unlikely to...● prefer safety when buying

automobiles● volunteer to learn about social

causes● be influenced by brand names

when making product purchases

Page 24: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Matchmaker Matchmaker

● Cluster Targeting● Persona Segmentation● Journey Triggering● Personalization Variations● Emotive Predictors

● Conference Attendees● Skill Finders● Job Postings● Volunteer Opportunities● Geo Targeting

Page 25: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Example: Matching Jobs with Skills

● Recommended Skills● Job Opportunity Needs

Page 26: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Relational databases cannot easily have new varieties of data added

Similar but not exact data was difficult to associate, align, understand

Richer semantic models can generate new understanding, and questions

New questions generate more data, and knowledge - processes increasing autonomous

Page 27: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Answers

● Information Extraction● Deep Learning

Knowledge Bases● Pathfinding and Scoring● Speech Recognition● Natural Language

Processing● Reasoners and Question

Answers

Page 28: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

IBM Watson, Come here, I want...

Page 29: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

So what are the questions?

● How do marketers define successful customer experiences?

● How do customers define successful interactions with

brands?

● Does everyone want the same things?

● Isn’t the best price for the best product good enough?

● So many questions! Q&A conversations led to new

questions and to new insights about the nature of the

conversation.

Page 30: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Product, Price, Promotion, Place +

Page 31: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Dicks Sporting Goods CX

● One-to-one● Customized● Personalized● Emotionalized

Page 32: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

If Answers are Easy...

A lesson of big data is that finding answers to those questions is increasingly trivial with AI based machines.

The challenge is to ask the right questions.

As we'll see later the right question for personalizing messaging are Who, What and How?

Page 33: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Insights

What is the next best message

How can information be linked and analyzed to help us understand individuals and how they want to be communicated to individually?

How do I move from personalized communication to individualized conversations?

Page 34: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Customize, Personalize, Emotionalize

7 Questions with suggestions for ...

● What are the intended outcomes for each step?

● What data can we use as inputs to insight generation?

● What AI / Big Data Tools that can be considered?

Page 35: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Next Best Message 7 Questions

Why are we generating a message or conversation?

What do we start or continue a conversation about?

Who are we having a conversation with?

Where is the best place to send message / have a conversation?

When is the best time to send the next message?

With individualized information do we communicate personally?

How does an individual want to be talked with?

Page 36: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Why are we generating a message or conversation?

● Outcome○ Triggering○ Conditions

● Input○ Campaign Map○ Transaction History○ Behavioral Event

● Services○ IBM Conversation○ Microsoft Bot Framework○ Google DeepMind○ Amazon Machine Learning

Page 37: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

What do we start or continue a conversation about?

● Outcome○ Campaign Trigger○ Message Type

● Input○ Segmentation Cluster ○ Campaign Persona

● Services○ IBM Retrieve and Rank○ Microsoft Text Analysis API○ Google Purchase Prediction○ Amazon Propensity Modeling

Page 38: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Example: Myers-Briggs Type Indicator

“THE ARCHITECT”

INTJ personality types think strategically and see the big picture.

Have original minds and great drive for implementing their ideas and achieving their goals. Quickly see patterns in external events and develop long-range explanatory perspectives. When committed, organize a job and carry it through. Skeptical and independent, have high standards of competence and performance - for themselves and others.

Page 39: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Who are we having a conversation with?

● Output○ Segmenting○ Audience

● Input○ Campaign Recipients○ Segment Candidates○ GeoTargeted Customers

● Services○ IBM AlchemyLanuage○ Microsoft Linguistic Analysis○ Google Prediction API○ Amazon Churn Prediction

Page 40: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Example: PersonicX® Cluster Perspectives

Cluster #5: Active & Involved

Active & Involved households are wealthy empty nesters. At a mean age of 60, they are extremely well educated and still well compensated in professional and managerial white-collar jobs, as well as being active investors. With a third having lived at their residence for 6-14 years, and another third for 15+ years, these homeowners are well established in their communities. They are likely to own a recreation vehicle and enjoy travel to Hawaii and to national parks. Their substantial discretionary time and money are spent on high-quality clothing, dining out, golf and live theater. However, they are also community activists, belonging to charitable, religious and civic organizations.

Page 41: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Where is the best place to send message / have a conversation?

● Outcome○ Channeling○ Medium

● Input○ GeoFencing○ Device Preferences○ Geography profile

● Services○ IBM Conversation○ Microsoft Entity Linking○ Google Sentiment Analysis○ Amazon Alexa

Page 42: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

When is the best time to send the next message?

● Outcome○ Customizing○ Event Trigger

● Input○ Campaign Map○ TOD Best Practices○ Preferences○ Behavioral profile

● Services○ IBM Conversation○ Microsoft Entity Linking○ Google Prediction API○ Amazon Machine Learning

Page 43: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

With which individualized information do we communicate personally?

● Outcome○ Personalizing○ Message Content

● Input○ Cluster attributes ○ Demographic profile ○ Psychographic profile○ Personality profile

● Services○ Amazon Content Personalization○ Microsoft Recommendation API

Page 44: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Example: DiSC Profile Comparison

Jeff Stewart John Leininger Eric Remington

Disc: Dci Disc: Isd Disc: Cdi

is fairly aggressive, methodical, and results-driven, but can be approachable and supportive of others.

thrives in an unstructured environment, loves exploring new ideas, and occasionally makes gut-driven decisions that might seem risky.

is analytical, inventive, and craves tough problems to solve, but you can bore him easily with predictability.

Do: focus on a single, clear message (ex: "I am reaching out to get your opinion.")

Do: use personal anecdotes and information (ex: "I used to work in the same industry and want to get your perspective")

Do: ask straightforward, even yes or no questions (ex: "Would you like to meet about this?")

Don't: make any claims that cannot be backed up with proof (ex: "Our mutual friend wanted us to connect.")

Don't: be overly formal and cold (ex: "I have 30 minutes to review this information.")

Don't: use anecdotal expressions (ex: "I thought you might like this.")

Page 45: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

How does an individual want to be talked with?

● Outcome○ Emotionalizing

● Input○ Psychographic profile○ Temperament profile

● Services○ IBM Personality Insights○ Google Prediction API○ CrystalKnows Profile○ Traxion Customer Insights

Page 46: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Example: Traxion Temperament

Characteristics

● extroverted ● enthusiastic ● emotional ● sociable● impulsive● optimistic

You want to be the first to experience something, and never miss out on an opportunity.

Page 47: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Expressive, Analytical, Passive, Aggressive

Page 48: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Personas Are Not Personal

Personas are analogies, useful but not personal. What Is? Perse and meGraph

Page 49: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse OntologyΠέρση əː ˈ ɪ

Perse is an ontology and set of classes for creating and publishing a personalization profile with multiple facets or dimensions.

Page 50: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse Geography

● Current Residence

● Work Location

● Past Locales

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Perse Demography

● VCard Contact Info

● Myers-Briggs Type Indicator

● Acxiom Demographics

● Personicx Clusters

Page 52: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse Knowledge

● Education

● Recommendations

● References

● Patents

Page 53: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse Experience

● Job History

● Volunteer

● Projects

● Publications

Page 54: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse Skills

● LinkedIn Skills

● Personal Competencies

Page 55: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse Interests

● Acxion Interest Categories

● LinkedIn Interests

Page 56: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse Personality

● Watson Personality Insights

● Traxion Customer Insights

● Kersey Temperament Sorter

● DiSC Profiles

Page 57: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Perse MatchMaker

● Job Match

● Campaign Match

● Targeting Match

● Email Match

Page 58: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

meGraph Perse Personality Profile

Page 59: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Question Answerer Semantic Graph

Now what questions can we ask?

Let’s ask Alexa!

Page 60: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Right message at the right time in the right place with the right tone

● Effective use of good data with advanced models and

techniques can provide the margin of victory.

● Semantic models and information enhancement and

discovery can help with understanding how people want

to be communicated with.

● The right message at the right time in the right place

with the right tone can motivate customers along their

customer journey path.

Page 61: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

Take-a-Ways...

...can I have a ( ͡° ͜ʖ ͡°) ?

❖ What is and Why Big Data

❖ NoSQL and Graph Databases

❖ Big Blue and others Deliver Answers

❖ The Best One is the Next One

❖ Me Per Se

Page 62: 2016 XUG Conference   Big Data: Big Deal for Personalized Communications or Meh?

More Questions? Contact me @

https://www.linkedin.com/in/jeffreyastewart

Jeffrey StewartIT and Management Consultant

Asterius Media LLC

Email: [email protected]

[email protected]

Twitter: JeffreyAStewart

LinkedIn: jeffreyastewart

SlideShare: stewtrekk