The Clear Advantage: Using Artificial Intelligence to Create a Learning Model for Training

Preston Faykus, Founder & CEO RankMiner Predictive Analytics pfaykus@rankminer.com 469.387.3865

Introduction – Who is RankMiner

•  RankMiner, Inc. a US corporation headquartered in St. Petersburg, FL www.rankminer.com

•  Founders specialized in data and voice analytics with a focus on innovative applications built with machine learning

Overview 1.  Introduction to Artificial Intelligence (“AI”)

2.  Bird’s-eye overview

3. Current applications

4.  Innovations made using AI relating to call centers

5.  Leading developments

Introduction to AI What AT is like today… •  Process enormous amounts of data

•  Classify new observations according to past observations

•  Forecast details of future events

•  Solving complicated – but practical! – problems

What AI can’t yet do… •  Making connections at an abstract level

•  Higher order reasoning

•  Self-actualization

The Power of Using Artificial Intelligence Tsunami of data in Call Centers

•  Call Volume – thousands of calls made per day

•  Metadata – tens to hundreds of

thousands bits of information generated per day

•  Business Outcomes – defined and

discovered daily •  How does it all Inter-relate? •  How can humans analyze all of this

data fast and efficiently?

The Power of Using Artificial Intelligence

Artificial Intelligence or, Machine Learning is the process of designing, tuning and employing algorithms to identify patterns in large, seemingly unrelated datasets, and predict future patterns.

The Power of Using Artificial Intelligence

3 Main Types of Machine Learning

• Unsupervised: discovering hidden properties of data

• Supervised learning: classifying new data from known properties

• Reinforcement learning: making the best decisions now to maximize long-term reward

Innovations using Unsupervised Learning • Give cross-sell suggestions to consumers • Organize consumers into target markets / calling campaigns • Search engine optimization Basic Ideas: • Start with a population and determine distinguishing characteristics • Organize data with generic/suggested labels

Innovations using Supervised Learning • Proactively identify fraudulent transactions •  IVR call routing • Speaker identification Basic Ideas: • Use historical labeled data as examples • Answer True/False or multiple choice questions

Innovations using Reinforcement Learning • Determine payment / cost adjustments • Adjust employee commissions / incentive programs • Guided sales negotiations Basic Ideas: • Many more choices in the decision-making process (typically) • No knowledge of ultimate result, only of immediate return

Well-known applications

• Unsupervised learning: Google search, Amazon ”if you like X…”, Netflix “Top picks for you”

• Supervised learning: BoA automatic fraud detection, Apple Siri, Microsoft WhisperID

• Reinforcement learning: Deep Blue, IBM Watson, Geico instant online quotes

AI Uses in Call Centers •  Evaluate 100% of Your Call Volume

•  Audio Analysis

–  Extract and create audio Feature Vectors (FV)

–  Identify Emotions and Behaviors –  Know not only what was said, but also

how it was said

•  Metadata Analysis – Algorithms used to identify key parameters of structured data –  links vocal insights to data sources more

closely related to business outcomes –  include pieces as part of feature vector –  use other pieces to categorize business

outcomes into supervised learning choices (“classes”)

AI Uses in Call Centers

Predictive model building process

•  Feature vectors paint a picture to each class

•  Big data <==> huge number of

dimensions to base decisions on •  End result: a decision-making

policy to take in new data (e.g. calls) and associate them with a class and ultimately the anticipated business outcome

AI Uses in Call Centers •  Deploy Automated Analysis

Algorithms –  Optimized Call Analysis

Algorithms –  Optimized Metadata

Analysis Algorithms –  All future calls and related

metadata are analyzed

•  Deploy Optimal Prediction Model(s) –  Can have one or more

prediction models –  Predicts Business Outcomes

for all future calls

AI Uses in Call Centers •  Call Center business

success is based primarily on interaction between customer & agent

•  How to automatically improve opportunity for success? –  Customer Predictive

Model –  New Hire Predictive

Model –  Agent Predictive Model

AI Uses in Call Centers •  Analyze 100% of Floor

Agent calls •  Use Agent Prediction

Model to identify Good / Average / Poor calls

•  Quickly identify Floor Agents in need of additional training

•  Implementations show 21.6% increase in Floor Agent revenue

AI Uses in Call Centers

•  Soft Skills –  Floor Agent Engagement –  Empathy & Helpfulness –  Active listening

•  Correlate with: –  Payment –  Sells –  Customer Satisfaction

•  Identify Floor Agents in need of help…their success is your success

AI Uses in Call Centers •  QA Staff can not evaluate all calls –  Use predictions as a queueing

mechanism –  Database driven scorecard

templates –  Immediate insight for Supervisors

and Management

•  Use existing QA process to improve predictive model –  Verify model prediction –  QA identified trends to improve

model performance

•  Implementations show productivity improvements in Quality Assurance of over 50%

AI Uses in Call Centers

•  Discover new factors leading to SUCCESSFUL business outcomes –  Increase Floor Agent revenue

streams –  Accelerate conversion cycle –  Increase Floor Agent ROI

•  Upgrade Business Practices –  Hire Floor Agents with successful

attributes –  Train Floor Agents for success –  Quickly identify and react to

“bad” trends to prevent loss of revenue

–  Quickly identify and react to “good” trends to increase revenue and build a successful culture

Leading Developments

•  Automated Reinforcement Learning – Business Environments

constantly change – Prediction Model(s)

dynamically updated – Analysis Algorithms dynamically

updated

•  Allows continuous uninterrupted evaluation of 100% of call volume 24/7

SUMMARY •  Machine Learning based on AI is changing the way call centers operate –  Analyze all data, including

audio for emotions and behaviors

–  Discover new trends and factors for success

•  Increase revenues –  Improve Floor Agent success –  Improve QA efficiency –  Improve Management insight –  Create a culture of success

Questions

Preston Faykus, Founder & CEO RankMiner Predictive Analytics pfaykus@rankminer.com 469.387.3865