webinar: predictive lead scoring - what makes it so predictive?
TRANSCRIPT
Predictive Lead ScoringWhat Makes It So Predictive?
#predictiveleadscoring
Housekeeping
If you can see the slides and hear me please raise your hand in the GoToWebinar Dashboard
Your speakers
Dan Chiao Jessica Cross
#predictiveleadscoring
Today’s Webinar Agenda
1. How Predictive Lead Scoring is Different2. What Makes it Predictive3. Why You Need Predictive Lead Scoring to Stay
Competitive4. Q&A
To submit questions during the webinar, please tweet them:
#predictiveleadscoring @fliptop
#predictiveleadscoring
Conventional Lead Scoring
All Names
MQL
Prospect
Lead
Sales Lead
OpportunityCustomer
Behaviors
• Early stage content: +3• Attend webinar: +5• Visit any webpage/blog:
+1• Visit careers pages: -10
Demographics
#predictiveleadscoring
• Job Title: +20• Industry: +10• Uses CMS: +5• Uses Shopping Cart: +5• Generic email: -10
Target persona
VP of Sales• Job Title: +20• Attend webinar: +5• Visit any webpage/blog:
+1• Visit careers pages: -10
• Possible Score = 16
Lead Score
#predictiveleadscoring
Target persona
Social Media Manager• Early stage content: +3• Attend webinar: +5• Visit any webpage/blog:
+1• Watch demos: +5• Mid-stage content: +8• Late-stage content: +12
• Possible Score = 34
Lead Score
#predictiveleadscoring
Flaws with conventional lead scoring
94% of all MQLs will never convert
#predictiveleadscoring
Flaws with conventional lead scoring
52% of sales reps will not make their
quota
#predictiveleadscoring
What is Predictive Analytics?
• Process or analyzing current and historical facts to make predictions about future, or otherwise unknown events
How Predictive Lead Scoring Differs
Traditional Lead Scoring Predictive Lead Scoring
Based on assumptions Fitted to historical outcomes
Simple summation Statistical methodsLimited by causation Identifies correlationsUnbounded numerical score Probability of close
Expected revenue amountExpected sales cycle
Requires quarterly review Updates automatically#predictiveleadscoring
Traditional Lead Scoring
• Based on assumptions and intuition
• Requires consensus between Sales and Marketing teams
Predictive Lead Scoring
• Based on historical outcomes
• Removes friction between Sales and Marketing teams
#predictiveleadscoring
Lead Score
• Early stage content: +3• Attend webinar: +5• Visit any webpage/blog:
+1• Visit careers pages: -10• Mid-stage content: +8• Job Title: +20• Industry: +10• Uses CMS: +5• Uses Shopping Cart: +5• Generic email: -10
#predictiveleadscoring
Traditional Lead Scoring
• Simple summation• Assigns qualitative
weights to activities
Predictive Lead Scoring
• Uses statistical methods
• Machine learning
Score = 634
#predictiveleadscoring
Score = -10
Traditional Lead Scoring
• Unbounded numerical score
• Not tied to specific outcomes
Predictive Lead Scoring
• Bounded numerical score• Concrete outcomes
– Probability of close– Expected revenue– Expected close date
#predictiveleadscoring
Traditional Lead Scoring
• Limited to linear correlations
Predictive Lead Scoring
• Can identify non linear correlations
#predictiveleadscoring
Gather
inputs
Validate
inputsBuild Scorin
g
Deploy
Scoring
Refine Scorin
g
Iterative Process
Traditional Lead Scoring
• Requires frequent reviews to stay current
• Manually process to update scoring model
Predictive Lead Scoring
• Automatically updates predictive model with every new customer
Conventional lead scoring looks at just a few data points
Industry
Marketing activityJob title
LocationBudgetCompany size
#predictiveleadscoring
Lead Scoring
Industry
Email addressJob title
LocationBudgetCompany size
Gender
Marketing activity
Funding
Hiring
Technology Stack
Open job postingsSocial Presence
Age
Youtube URLSocial gender
Website form
LinkedIn URL
Founded Year
Email List
Tech SEO
Company Type
Invested Capital
Youtube views
Traffic Rank
Engine Optimizer
Facebook AdvertiserCRM Software
Accepts Payments
Tech Media
Market Value
Social Occupation
Facebook Shares
Facebook LikesStocks
Twitter URL
Net Income
Employees TotalTwitter Match Score
Social Profile Photo
Paid Analytics
Influence Score
Social Presence
Website form
Social Profile Photo
Open Job Postings
Funding
Business Twitter Followers
iPhone App
iPhone App RatingCompany Age
Android App
Influence Score
Android App Rating
Has WebsiteNAICS Code
USSIC Code
UKSIC Code
Industry Ranking
Market CapitalizationCash Balance
Sales Growth Percentage
Publicly listedAge GroupOpen Management Jobs
Open Legal Jobs
Employee Count
Has Disposable Email Non-Business EmailInvalid Phone Number
Uses PHP
Uses Apache
Content Delivery Network
Cross-Browser Compatibility
Uses DNS
Uses .NET
Uses Data Feeds
Has Forms
Uses PHP
Uses JavaScriptUses SlideshowsJavascript Menus
Name server Parked Domain
Influence Score
Open Job PostingsEmployee Count
Uses JavaName server
Engine Optimizer
Content Delivery NetworkUses Data Feeds
Uses NginxUses TooltipIncludes Videos
Uses Wordpress
Employees Total
Employee Count
Open Production JobsAndroid App
Engine Optimizer
HiringTech SEO
Traffic Rank
Social OccupationNet IncomeUses Slideshows
Parked DomainOpen Job Postings
Uses Ajax
Uses .NET
Publicly listedNon-Business Email
Uses DNSOpen Military-Specific Jobs
Industry Code
Engine Optimizer
Uses Perl
Uses Ajax
Uses Apache
Open Job Postings
Open Job PostingsIncludes Videos
Social Profile PhotoAge group
Uses Python
Uses TooltipJavaScript Menus
Has Forms
Open Job Postings
Includes Videos
Uses DNSUses Apache
Invested CapitalOpen Other jobs
#predictiveleadscoring
The classic process
Visit website: +5 points
#predictiveleadscoring
The Fliptop process
Historical Sales
3,500+ Signals / 40+ Data Sources
Machine LearningModel Tournament
#predictiveleadscoring
The Fliptop process
3,000+ Signals / 40+ Data Sources
Model is ready
Scored Lead
#predictiveleadscoring
Works with the technology you already use
#predictiveleadscoring
Intuit’s Results
57% Decrease in time to close for new business deals
Increase in revenue
Amount spent on new headcount to achieve results.
75%$0
Norman HappVice President of Sales
#predictiveleadscoring
“Fliptop helped us uncover great leads that had been incorrectly disqualified.
It was a ‘aha’ moment for sales and marketing.”
Rob BaileyCEO
Case Study
#predictiveleadscoring
Q&A – 10 Minutes
Thank you.Contact us for your own predictive lead scoring model
[email protected](888) 373-7533
Dan ChiaoVP of Engineering
Jessica CrossDir. Marketing
#predictiveleadscoring