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Scoring Lead Propensity, Thinking
Beyond Obvious!
November 11, 2021.
● Importance of Lead Scoring & Industry Stats
● Lead Scoring - Traditional Vs Modern Approach
● Dataiku-Tatvic Differentiation
● Our Lead Scoring Model - A Quick Walkthrough
● Digital Maturity Assessment
2
Our Agenda
3
Speakers
Head - Solutions Development
Tatvic Analytics
Bismayy Mohapatra
Lead Partner Solution Architect
Dataiku
Tarun Lalwani Kaushal Bhatt
Head - Marketing & Partnerships
Tatvic Analytics
Abhishek
Pathak
Lead Data Scientist
Tatvic Analytics
c
4
Scoring Lead Propensity, Thinking Beyond
Obvious!
1
Lead Scoring
5
“Lead scoring is a methodology used to rank prospects
(or leads) against a scale that represents the perceived
value each prospect represents to the enterprise.The
resulting score is used to determine which leads [sales
and marketing teams] will engage, in order of priority”
Defined By: Sirius Decisions, a research firm
6
Interesting Stats to share!
70%
According to a Garner study, 70%
of leads are lost because of poor
follow-up practices.
77%
Marketing Sherpa study states companies
who use lead scoring regularly see a 77%
higher lead generation ROI over
companies who do not
7
Another Stat!
A Kentico study found 38% of businesses surveyed experienced higher
lead to sale conversion rates thanks to lead scoring
38%
The Traditional Way of Lead Scoring
8
Limited Data access to
profile/ score Leads
Rule based scoring by
Contact Center team
Lack of continuous
optimization process
User Profiling Data from
CRM tools
The New Way of Lead Scoring
9
Digital User Behavior from
Analytics tools
User Profiling Data from
CRM tools
Machine Learning Algorithms
Real-time scoring High degree of accuracy Automated & Scalable
10
Why User Behavior data is a must in Lead Scoring?
74% 16% 10%
Site/ App Behavior Traffic Source User Profile
Sessions, page visits, time
spent, tenure, day of week,
time of day, micro events
Channel, source, medium,
campaigns (for all sessions
and lead session)
Age, gender, location (city /
region),Device Category,
Browser, Operating System
11
Lead Scoring Solution
80
60
ML Models
Logistic
Regression
Random
Forest
Dense Neural
Network
95
40
25 10
Leads with high Propensity to
convert
Leads with medium
Propensity to convert
Leads with low Propensity to
convert
Contact Center
Activation
Remarketing &
Prospecting
Campaigns
Leads and
Conversions data
Online Behavior
data from
Website and App
Email/ SMS
Activation
12
Lead Scoring Decision Tree looks like
c
13
A Real-World Customer Success Story
2
14
Success Story
● Contact Center Team wanted to
differentiate between unqualified and
qualified leads quickly and efficiently
for prioritizing their calling efforts
● Marketing team wanted to make use of
rich online behavior data of qualified
leads for customer segmentation and
targeted paid marketing campaigns
15
22%
Higher Conversion Rate
18x
Higher ROAS from high
propensity audiences
32%
Higher Leads
61%
Lower Cost Per Lead
Contact Center Activation Prospecting and
Remarketing Campaigns
Outcome
c
16
The Dataiku DSS Platform
4
Code your way
• Code freely with Jupyter, R, Python IDEs,
any package, isolated environments,
and full Git integration
• Have full programmatic control with full-
fledged API for models, pipelines,
automation
Leverage advanced tech
• No need to master the underlying
infrastructure
• Connect, explore and navigate
• Combine point and click with R, SQL,
Python
and leverage code snippets
• Packaging of cloud services
Point & click
• Search, connect to, and explore data
from preconnected or local systems
• Data wrangling, (auto) machine learning
directly through visual and click interfaces
• Dashboarding, advanced statistics
and data visualization
Don’t get distracted
• Self-provision of compute resources
including cloud-based elastic processing
for large volumes of data, users or
services
• Expedite wrangling with facilitated
connections to SQL, HDFS, cloud storage,
NoSQL, HDFS, APIs,...
Orchestrate advanced flows
• Build check, metrics, and warnings
on top of your data flows
• Orchestrate simple and complex
data flows in minutes for continuous
value generation
Ensure impact
• Low effort CI / CD through orchestrated
pipelines with optional automatic checks
• Create deployment artifacts
• Deploy your models as containerized APIs
• Showcase insights with webapps (Shiny,
Flask, Bokeh) and deploy in Kubernetes
package for reuse by the target population
Upskill
• Gain exposure to more advanced
usage of data within a controlled
environment
emb = Embedding(vocabulary_size,
embedding_size,
input_length=text_length,
<
>
ABC = XZY
123 = 789
!@£ = ^&*
Spreadsheet
wizards
Python
expert
Statistician
Data Scientist
Analyst
High
code
Low
code
No
code
Build on shoulders of giants
• Use packaged plug-ins and full apps
to deliver data scientist-grade projects
with business expert insights
• Copy and paste past projects, data
and models for reuse
Human and readable
• Understand projects, from data
connection to trained models
Empower Everyone From Low to Full Code
GE Aviation’s analytics projects can be
moved to production in <2 minutes
A Pre-Integrated Framework to Drive
Large-Scale Impact in Minutes vs. Days
One global investment bank scaled to 500+
users and 2000+ projects
Aviva became x5 more efficient in
developing AI products
Business
Analysts
Business
Owner
Data
Scientist
Data
Engineer
Ideation Validation
Business rules
monitoring
Data Preparation Auto Modeling
Data Preparation Modeling
Refactoring Deployment Operation
(Value)
19
Benefits & A Quick Recap
● Faster Time to Market for deployment
○ From 4+ weeks to less than 10 days for a Lead Scoring use case
○ Visual EDA to Quick Interactive Dashboards to Multiple Algos to Retraining Pipelines
○ Time savings on coding transformation recipes from scratch and pipeline deployment
● AI Democratization within multiple teams
○ No Black Box, Fully Customizable
○ Data Science Team
○ Data Engineering Team
○ Data Analytics & BI Team
● Access and exposure to conduct variety of DS use cases via DSS
○ Visitor/ Lead Scoring
○ Lifetime Value Modelling
○ Video Classification
○ Sentiment Analysis
○ Recommendation Engine
c
20
Assess Your Digital Maturity
5
Which Digital Maturity Stage do you Fall in?
The Digital Maturity Framework is a critical tool to realize the full potential of data-driven marketing
strategies across your business. It has been designed by BCG in collaboration with Google.
Campaigns are executed
mainly using external data
and direct buys with
limited link to sales
Some use of owned or 1P data
in automated buying with single
channel optimization and
testing
Dynamic execution
across multiple channels,
optimized towards individual
customer business outcomes
Data integrated or activated
across channels with
demonstrated link to ROI or
sales
Nascent Emerging Connected Multi-Moment
Find more details at : BCG's Digital Maturity Framework
21
Media Centric Tech Centric Data Centric Automation Centric
How Does Organizations Benefit
Nascent
Efficiency
Effectiveness
1
2
3
Multi-moment
Emerging
Connected
Up to
+20%
revenue
Up to
−30%
cost
As one advances
Digital Maturity to a
Multi-Moment Stage,
Customers have
reported gains in
Profitability and Cost
Savings
Ref: Google + BCG Study
Overall score
The overall score is an aggregate of the 5 dimensions we measured
using equal weighting. Both qualitative questions and a quantitative
account analysis were considered. The individual scores below can
guide future areas of focus. Emerging
(1.9 out of 4)
Emerging Emerging Emerging Nascent Connected
Audience Assets Access Attribution Automation Organization
Connected
Maturity Assessment Scorecard
Retail
BFSI
Travel & Leisure
Education
Automotive
Technology
CPG
Media & Telecom
How Does Your Industry Perform?
Nascent Emerging Connected Multi-Moment
c
25
Thank You
+91 72010 00406
hello@tatvic.com

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Dataiku tatvic webinar presentation

  • 1. c Scoring Lead Propensity, Thinking Beyond Obvious! November 11, 2021.
  • 2. ● Importance of Lead Scoring & Industry Stats ● Lead Scoring - Traditional Vs Modern Approach ● Dataiku-Tatvic Differentiation ● Our Lead Scoring Model - A Quick Walkthrough ● Digital Maturity Assessment 2 Our Agenda
  • 3. 3 Speakers Head - Solutions Development Tatvic Analytics Bismayy Mohapatra Lead Partner Solution Architect Dataiku Tarun Lalwani Kaushal Bhatt Head - Marketing & Partnerships Tatvic Analytics Abhishek Pathak Lead Data Scientist Tatvic Analytics
  • 4. c 4 Scoring Lead Propensity, Thinking Beyond Obvious! 1
  • 5. Lead Scoring 5 “Lead scoring is a methodology used to rank prospects (or leads) against a scale that represents the perceived value each prospect represents to the enterprise.The resulting score is used to determine which leads [sales and marketing teams] will engage, in order of priority” Defined By: Sirius Decisions, a research firm
  • 6. 6 Interesting Stats to share! 70% According to a Garner study, 70% of leads are lost because of poor follow-up practices. 77% Marketing Sherpa study states companies who use lead scoring regularly see a 77% higher lead generation ROI over companies who do not
  • 7. 7 Another Stat! A Kentico study found 38% of businesses surveyed experienced higher lead to sale conversion rates thanks to lead scoring 38%
  • 8. The Traditional Way of Lead Scoring 8 Limited Data access to profile/ score Leads Rule based scoring by Contact Center team Lack of continuous optimization process User Profiling Data from CRM tools
  • 9. The New Way of Lead Scoring 9 Digital User Behavior from Analytics tools User Profiling Data from CRM tools Machine Learning Algorithms Real-time scoring High degree of accuracy Automated & Scalable
  • 10. 10 Why User Behavior data is a must in Lead Scoring? 74% 16% 10% Site/ App Behavior Traffic Source User Profile Sessions, page visits, time spent, tenure, day of week, time of day, micro events Channel, source, medium, campaigns (for all sessions and lead session) Age, gender, location (city / region),Device Category, Browser, Operating System
  • 11. 11 Lead Scoring Solution 80 60 ML Models Logistic Regression Random Forest Dense Neural Network 95 40 25 10 Leads with high Propensity to convert Leads with medium Propensity to convert Leads with low Propensity to convert Contact Center Activation Remarketing & Prospecting Campaigns Leads and Conversions data Online Behavior data from Website and App Email/ SMS Activation
  • 12. 12 Lead Scoring Decision Tree looks like
  • 13. c 13 A Real-World Customer Success Story 2
  • 14. 14 Success Story ● Contact Center Team wanted to differentiate between unqualified and qualified leads quickly and efficiently for prioritizing their calling efforts ● Marketing team wanted to make use of rich online behavior data of qualified leads for customer segmentation and targeted paid marketing campaigns
  • 15. 15 22% Higher Conversion Rate 18x Higher ROAS from high propensity audiences 32% Higher Leads 61% Lower Cost Per Lead Contact Center Activation Prospecting and Remarketing Campaigns Outcome
  • 16. c 16 The Dataiku DSS Platform 4
  • 17. Code your way • Code freely with Jupyter, R, Python IDEs, any package, isolated environments, and full Git integration • Have full programmatic control with full- fledged API for models, pipelines, automation Leverage advanced tech • No need to master the underlying infrastructure • Connect, explore and navigate • Combine point and click with R, SQL, Python and leverage code snippets • Packaging of cloud services Point & click • Search, connect to, and explore data from preconnected or local systems • Data wrangling, (auto) machine learning directly through visual and click interfaces • Dashboarding, advanced statistics and data visualization Don’t get distracted • Self-provision of compute resources including cloud-based elastic processing for large volumes of data, users or services • Expedite wrangling with facilitated connections to SQL, HDFS, cloud storage, NoSQL, HDFS, APIs,... Orchestrate advanced flows • Build check, metrics, and warnings on top of your data flows • Orchestrate simple and complex data flows in minutes for continuous value generation Ensure impact • Low effort CI / CD through orchestrated pipelines with optional automatic checks • Create deployment artifacts • Deploy your models as containerized APIs • Showcase insights with webapps (Shiny, Flask, Bokeh) and deploy in Kubernetes package for reuse by the target population Upskill • Gain exposure to more advanced usage of data within a controlled environment emb = Embedding(vocabulary_size, embedding_size, input_length=text_length, < > ABC = XZY 123 = 789 !@£ = ^&* Spreadsheet wizards Python expert Statistician Data Scientist Analyst High code Low code No code Build on shoulders of giants • Use packaged plug-ins and full apps to deliver data scientist-grade projects with business expert insights • Copy and paste past projects, data and models for reuse Human and readable • Understand projects, from data connection to trained models Empower Everyone From Low to Full Code
  • 18. GE Aviation’s analytics projects can be moved to production in <2 minutes A Pre-Integrated Framework to Drive Large-Scale Impact in Minutes vs. Days One global investment bank scaled to 500+ users and 2000+ projects Aviva became x5 more efficient in developing AI products Business Analysts Business Owner Data Scientist Data Engineer Ideation Validation Business rules monitoring Data Preparation Auto Modeling Data Preparation Modeling Refactoring Deployment Operation (Value)
  • 19. 19 Benefits & A Quick Recap ● Faster Time to Market for deployment ○ From 4+ weeks to less than 10 days for a Lead Scoring use case ○ Visual EDA to Quick Interactive Dashboards to Multiple Algos to Retraining Pipelines ○ Time savings on coding transformation recipes from scratch and pipeline deployment ● AI Democratization within multiple teams ○ No Black Box, Fully Customizable ○ Data Science Team ○ Data Engineering Team ○ Data Analytics & BI Team ● Access and exposure to conduct variety of DS use cases via DSS ○ Visitor/ Lead Scoring ○ Lifetime Value Modelling ○ Video Classification ○ Sentiment Analysis ○ Recommendation Engine
  • 21. Which Digital Maturity Stage do you Fall in? The Digital Maturity Framework is a critical tool to realize the full potential of data-driven marketing strategies across your business. It has been designed by BCG in collaboration with Google. Campaigns are executed mainly using external data and direct buys with limited link to sales Some use of owned or 1P data in automated buying with single channel optimization and testing Dynamic execution across multiple channels, optimized towards individual customer business outcomes Data integrated or activated across channels with demonstrated link to ROI or sales Nascent Emerging Connected Multi-Moment Find more details at : BCG's Digital Maturity Framework 21 Media Centric Tech Centric Data Centric Automation Centric
  • 22. How Does Organizations Benefit Nascent Efficiency Effectiveness 1 2 3 Multi-moment Emerging Connected Up to +20% revenue Up to −30% cost As one advances Digital Maturity to a Multi-Moment Stage, Customers have reported gains in Profitability and Cost Savings Ref: Google + BCG Study
  • 23. Overall score The overall score is an aggregate of the 5 dimensions we measured using equal weighting. Both qualitative questions and a quantitative account analysis were considered. The individual scores below can guide future areas of focus. Emerging (1.9 out of 4) Emerging Emerging Emerging Nascent Connected Audience Assets Access Attribution Automation Organization Connected Maturity Assessment Scorecard
  • 24. Retail BFSI Travel & Leisure Education Automotive Technology CPG Media & Telecom How Does Your Industry Perform? Nascent Emerging Connected Multi-Moment
  • 25. c 25 Thank You +91 72010 00406 hello@tatvic.com