Lead Scoring in Salesforce.com Part Two – Advanced Lead Scoring February 26, 2009 Manticore Technology, Inc. Confidential – Copyright 2009. All rights reserved.

Today’s Webinar Agenda Adding Online Behavior to a Model Scoring Depreciation Multi-Model Lead Scoring Case Study: Intellitactics Michaela Dempsey – Director of Marketing, Intellitactics Q&A

Agenda

Adding Online Behavior to a Model

Scoring Depreciation

Multi-Model Lead Scoring

Case Study: Intellitactics

Michaela Dempsey – Director of Marketing, Intellitactics

Q&A

Introductions Christopher Doran Vice President, Marketing, Manticore Technology Member of Founding Manticore Team (2003) Responsible for company’s worldwide marketing efforts including PR, demand generation and strategic partnerships (including salesforce.com) Longtime thought leader in the area of demand generation and marketing automation

Christopher Doran

Vice President, Marketing, Manticore Technology

Member of Founding Manticore Team (2003)

Responsible for company’s worldwide marketing efforts including PR, demand generation and strategic partnerships (including salesforce.com)

Longtime thought leader in the area of demand generation and marketing automation

Scoring Components Similarity of Lead to Target Market + Behavior lead has exhibited to indicate likelihood of purchase Build in Salesforce.com -OR- Demand Generation Solution Need Demand Generation Solution to Accomplish “ Fit” “ Interest” Last Week This Week

Manticore Technology Leading provider of demand generation solutions Ideal combination of power and ease-of-use Unmatched integration with salesforce.com Industry leader - Founded in 2001

Leading provider of demand generation solutions

Ideal combination of power and ease-of-use

Unmatched integration with salesforce.com

Industry leader - Founded in 2001

Build “Fit” Score Example: Expanded Model Criteria Data Source Max Points High Qual Mod Qual Low Qual Negative Qual Industry Web Form 20 Automotive 20 Auto Parts 5 CPG 20 Size Web Form 10 75k-100k emp 10 40k-50k 5 50k-75k emp 10 30k-40k 5 Region Web Form 10 North America 10 Infrastruct. Web Form/ Sales 20 Salesforce.com 20 Siebel -20 Sugar -20

Problem with “Fit” Scoring QUESTION: If you purchase a list of leads with perfect score are they ready for sales? ANSWER: Obviously not. They may have no idea who you are or what your product or services are. We remedy by adding a scoring component called “ interest” or “behavior”. This is based on behavior a lead has taken to become a qualified lead.

QUESTION:

If you purchase a list of leads with perfect score are they ready for sales?

ANSWER:

Obviously not. They may have no idea who you are or what your product or services are.

STEP I - Build Activity List List out activities that give indication of a lead’s level of interest/buying propensity Contact forms – demo, trial, sales contact Download Collateral – datasheets, case studies, whitepapers Webinar attendance Organic search terms used PPC words clicked Number of pages viewed on website Frequency of visit to website Think negative behaviors as well!

List out activities that give indication of a lead’s level of interest/buying propensity

Contact forms – demo, trial, sales contact

Download Collateral – datasheets, case studies, whitepapers

Webinar attendance

Organic search terms used

PPC words clicked

Number of pages viewed on website

Frequency of visit to website

Think negative behaviors as well!

STEP II – Bucket By Indicator Create three to four buckets of actions based on what you think would be an indicator of level of interest: High Interest Moderate Interest These buckets should consider each action independent of other actions. Total “Interest” score will consider aggregate actions. Low Value Negative Value

Create three to four buckets of actions based on what you think would be an indicator of level of interest:

High Interest

Moderate Interest

Low Value

Negative Value

Sample Buckets High Value Sales contact form Demo/trial request Moderate Value High value PPC or Organic search term Whitepaper/Case Study Low Value Registered for webinar – didn’t attend Low value PPC word Datasheet Negative Value Excessive Career page

High Value

Sales contact form

Demo/trial request

Moderate Value

High value PPC or Organic search term

Whitepaper/Case Study

Low Value

Registered for webinar – didn’t attend

Low value PPC word

Datasheet

Negative Value

Excessive Career page

STEP III – Identify SQL Threshold Identify tentative score for “Interest” for lead to become sales qualified lead (SQL) For example – 15 points Think of this value independent yet relative to “fit” score Can’t have max “fit” as 1,000 and “interest” as 10 KEY POINT: Sales and marketing MUST agree on Score and threshold to become sales qualified lead (SQL)

Identify tentative score for “Interest” for lead to become sales qualified lead (SQL)

For example – 15 points

Think of this value independent yet relative to “fit” score

Can’t have max “fit” as 1,000 and “interest” as 10

STEP IV – Assign Value Take a first swag assigning “interest” score to each bucket High Value = 20 Mod Value = 10 Low Value = 5 Negative Value = -10 KEY POINT: Point Values don’t matter! – no difference between 10 point max score to 1,000 max score for Interest – what matters is their relativity to one another – and relationship to “Fit” score. Proposed SQL “Interest” Score Threshold - 15

Take a first swag assigning “interest” score to each bucket

High Value = 20

Mod Value = 10

Low Value = 5

Negative Value = -10

STEP V – Test, Iterate, Test Run through scenarios If a lead takes two moderate actions each worth 5 points (10 total) is this a sales qualified lead? If so, 10 should be threshold If not change threshold OR score values High Value = 22 Mod Value = 9 Low Value = 2 Negative Value = -5 Change Points SQL = 15 High Value = 20 Mod Value = 10 Low Value = 5 Negative Value = -10 Change Threshold SQL = 18

Run through scenarios

If a lead takes two moderate actions each worth 5 points (10 total) is this a sales qualified lead?

If so, 10 should be threshold

If not change threshold OR score values

High Value = 22

Mod Value = 9

Low Value = 2

Negative Value = -5

High Value = 20

Mod Value = 10

Low Value = 5

Negative Value = -10

STEP V – Test, Iterate, Test No lead scoring model is perfect – accept that Re-visit model as necessary (at least quarterly) Many factors can impact need to modify model: Change in online actions New PPC words New collateral, etc Macro Economic Climate Current Pipeline Marketing Mix Organizational Changes

No lead scoring model is perfect – accept that

Re-visit model as necessary (at least quarterly)

Many factors can impact need to modify model:

Change in online actions

New PPC words

New collateral, etc

Macro Economic Climate

Current Pipeline

Marketing Mix

Organizational Changes

Adding Score Depreciation SCENARIO: If a lead downloaded a whitepaper one year ago, what should be the interest score for that lead today? ANSWER: 0 To effectively score interest, you must add depreciation (decay) element to model This reduces the interest score by a certain percentage over time to correspond with decreasing level of interest

SCENARIO:

If a lead downloaded a whitepaper one year ago, what should be the interest score for that lead today?

ANSWER: 0

To effectively score interest, you must add depreciation (decay) element to model

This reduces the interest score by a certain percentage over time to correspond with decreasing level of interest

Depreciation Table Period of Time % Depreciation of Interest Score for the period of time Depreciation should be running against all your leads and contacts to ensure recency of interest is incorporated

Common Salesforce Sync Mistake KEY POINT: Relativity of “Interest” and “Fit” Score to one another is critical – deliver it to your sales team! EXAMPLE: Salesforce.com Field: QUESTION: What insight does sales have to the lead’s “fit” and “interest”? ANSWER: NONE! To be effective, sync, “Fit”, “Interest”, & Total Score into individual fields so that sales has insight into how the components create the score

Scenario Your company has ten different products in your portfolio Targets different verticals and business sizes Four Different sales groups New Lead enters your system “Joe Hotlead” Which sales group gets the lead? What product is Joe “Hot” for? How does your sales team know what product to sell Joe”? You don’t know.

Your company has ten different products in your portfolio

Targets different verticals and business sizes

Four Different sales groups

New Lead enters your system “Joe Hotlead”

Which sales group gets the lead?

What product is Joe “Hot” for?

How does your sales team know what product to sell Joe”?

Multi-Model Lead Scoring SOLUTION: Build Lead Scoring Models for various products in your portfolio Match inbound leads with their “Fit” with each target market and their “Interest” in each individual product Six different lead scoring models match leads with target markets Create model to match customers with cross-sell/up-sell opportunities

SOLUTION: Build Lead Scoring Models for various products in your portfolio

Match inbound leads with their “Fit” with each target market and their “Interest” in each individual product

Case Study: Intellitactics Michaela Dempsey Director of Marketing, Intellitactics Responsible for marketing activities including lead generation, web presence, customer relations programs, marcom and sales support activities. Prior to Intellitactics, Michaela was the Director of Demand Generation and Customer Advocate at EMC SMARTS. Michaela’s former positions include Senior Marketing Executive at RiverSoft, Product Marketing Manager at CrowdBurst, Director of Multi-Media at SDA .

Michaela Dempsey

Director of Marketing, Intellitactics

Responsible for marketing activities including lead generation, web presence, customer relations programs, marcom and sales support activities.

Prior to Intellitactics, Michaela was the Director of Demand Generation and Customer Advocate at EMC SMARTS.

Michaela’s former positions include Senior Marketing Executive at RiverSoft, Product Marketing Manager at CrowdBurst, Director of Multi-Media at SDA .

Advanced Lead Scoring Implement, Analyze & Improve! Michaela Dempsey Director of Marketing, Intellitactics

Advanced Lead Scoring Overview About Intellitactics Why Lead Nurturing Why Lead Scoring How to Create a Framework Sample of Our Framework What to Look for - Analyzing Data Refine for Improvement Results

About Intellitactics

Why Lead Nurturing

Why Lead Scoring

How to Create a Framework

Sample of Our Framework

What to Look for - Analyzing Data

Refine for Improvement

Results

About Intellitactics Intellitactics, headquartered in Reston, Virginia is a global B2B information security management technology company Intellitactics’ portfolio of products enable enterprise security managers to effectively and efficiently protect information assets from malicious insiders, fraud, data loss and criminal hackers 3000 companies around the world benefit from Intellitactics products and services either directly or through managed security service providers

Intellitactics, headquartered in Reston, Virginia is a global B2B information security management technology company

Intellitactics’ portfolio of products enable enterprise security managers to effectively and efficiently protect information assets from malicious insiders, fraud, data loss and criminal hackers

3000 companies around the world benefit from Intellitactics products and services either directly or through managed security service providers

Why Lead Nurturing Thousands of suspects in DB that needed incubation Analytic visibility into suspects patterns/trends Ability to “control” virtual behavior and influence Allocation of resources Provides marketing greater reach with existing budget/headcount Align marketing to sales Team is “Riding the Same Bus” Build a repeatable process Measurable return on investment for marketing dollars Critical knowledge on programs: working / not working Market interest knowledge

Thousands of suspects in DB that needed incubation

Analytic visibility into suspects patterns/trends

Ability to “control” virtual behavior and influence

Allocation of resources

Provides marketing greater reach with existing budget/headcount

Align marketing to sales

Team is “Riding the Same Bus”

Build a repeatable process

Measurable return on investment for marketing dollars

Critical knowledge on programs: working / not working

Market interest knowledge

Why Lead Scoring Suspects are entering the DB from multiple sources daily Suspects are self qualifying their companies for solutions without human interaction or very minimal interaction Impossible to manually detect the activity level of suspects and prioritize follow up With Lead Scoring your organization can: Actively monitor suspects digital body language and direct them through a controlled nurture process Receive immediate notification when a suspect reaches interest score Convert uncovered suspect into a qualified lead

Suspects are entering the DB from multiple sources daily

Suspects are self qualifying their companies for solutions without human interaction or very minimal interaction

Impossible to manually detect the activity level of suspects and prioritize follow up

With Lead Scoring your organization can:

Actively monitor suspects digital body language and direct them through a controlled nurture process

Receive immediate notification when a suspect reaches interest score

Convert uncovered suspect into a qualified lead

How to Create a Framework Critical Step 1: sales and marketing team to define key actions, trigger points and score values Critical Step 2: clean & segment DB before starting process Items to score Personal or demographic details on suspect Source of suspect Behavioral actions Items to negatively score Visiting career, management, ect. page No activity in x time Source of subject

Critical Step 1: sales and marketing team to define key actions, trigger points and score values

Critical Step 2: clean & segment DB before starting process

Items to score

Personal or demographic details on suspect

Source of suspect

Behavioral actions

Items to negatively score

Visiting career, management, ect. page

No activity in x time

Source of subject

Sample of Our Framework Suspect Personal/Demographic Data Title Location Etc Behavioral Data (positive and negative) Registrations Organic and Paid Search Website visits over time Multiple page visits Targeted page visits, targeted PDF visits Etc New Suspects Qualified Lead Pipeline Prospect Lead Scoring Prospects Customer Data Behavioral Data (positive and negative) Targeted/multiple page visits Requested PDF’s Registrations Etc New Customers & Up Sell Customers

Suspect Personal/Demographic Data

Title

Location

Etc

Behavioral Data (positive and negative)

Registrations

Organic and Paid Search

Website visits over time

Multiple page visits

Targeted page visits, targeted PDF visits

Etc

New Suspects

Qualified Lead Pipeline Prospect

Lead Scoring Prospects

Customer Data

Behavioral Data (positive and negative)

Targeted/multiple page visits

Requested PDF’s

Registrations

Etc

New Customers & Up Sell

Customers

What to Look For – Analyzing Data Repeatable overtime – “the Usual Suspects” You can only improve what you measure Test groups are critical

Repeatable overtime – “the Usual Suspects”

You can only improve what you measure

Test groups are critical

Refine for Improvement Marketing Sherpa Year End Survey: Jan 2009 39% of Marketers feel that they are underutilizing their automation system 29% of Marketers say utilization is only fair You are now ready for layering in different rule sets Sets for particular verticals Sets for particular products Sets for stages in the sales cycle One size does not fit all You will always be learning and refining

39% of Marketers feel that they are underutilizing their automation system

29% of Marketers say utilization is only fair

You are now ready for layering in different rule sets

Sets for particular verticals

Sets for particular products

Sets for stages in the sales cycle

One size does not fit all

You will always be learning and refining

Results 171% increase of sales opportunities accepted into pipeline Telemarketing follow-up calls 200% higher connect rate due to educated prospects Shortened sales cycle by 30% due to added efficiency of a coordinated buyers journey Qualifying about 60% of marketing prospects

171% increase of sales opportunities accepted into pipeline

Telemarketing follow-up calls 200% higher connect rate due to educated prospects

Shortened sales cycle by 30% due to added efficiency of a coordinated buyers journey

Qualifying about 60% of marketing prospects

Thank You To learn more about Intellitactics’ implementation or other companies having success with Manticore contact: [email_address]

To learn more about Intellitactics’ implementation

or other companies having success with Manticore contact: [email_address]

Q&A

Q&A

Contact Information Christopher Doran Vice President, Marketing, Manticore Technology [email_address] www.manticoretechnology.com Michaela Dempsey Director of Marketing, Intellitactics [email_address] www.intellitactics.com

Christopher Doran

Vice President, Marketing, Manticore Technology

[email_address]

www.manticoretechnology.com

Michaela Dempsey

Director of Marketing, Intellitactics

[email_address]

www.intellitactics.com