Webinar: Predictive Lead Scoring - What Makes It So Predictive?

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


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


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


• 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


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


Flaws with conventional lead scoring

94% of all MQLs will never convert


Flaws with conventional lead scoring

52% of sales reps will not make their

quota


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


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



• Simple summation• Assigns qualitative

weights to activities


• Uses statistical methods

• Machine learning

Score = 634


Score = -10


• Unbounded numerical score

• Not tied to specific outcomes


• Bounded numerical score• Concrete outcomes

– Probability of close– Expected revenue– Expected close date



• Limited to linear correlations


• Can identify non linear correlations


Gather

inputs

Validate

inputsBuild Scorin

g

Deploy

Scoring

Refine Scorin

g

Iterative Process


• Requires frequent reviews to stay current

• Manually process to update scoring model


• Automatically updates predictive model with every new customer

Conventional lead scoring looks at just a few data points

Industry

Marketing activityJob title

LocationBudgetCompany size


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


The classic process

Visit website: +5 points


The Fliptop process

Historical Sales

3,500+ Signals / 40+ Data Sources

Machine LearningModel Tournament


The Fliptop process

3,000+ Signals / 40+ Data Sources

Model is ready

Scored Lead


Works with the technology you already use


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


“Fliptop helped us uncover great leads that had been incorrectly disqualified.

It was a ‘aha’ moment for sales and marketing.”

Rob BaileyCEO

Case Study


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


Webinar: Predictive Lead Scoring - What Makes It So Predictive?

Marketing

Transcript of Webinar: Predictive Lead Scoring - What Makes It So Predictive?