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A data-driven optimization process
that goes beyond lead capture
Optimizing the Lead
Brian Carroll
Executive Director, Revenue Optimization
MECLABS
2
Session Speaker
Brian Carroll
Executive Director of Revenue Optimization
MECLABS
Brian Carroll is Executive Director of Applied Research at MECLABS and
CEO of InTouch, part of the MECLABS Group. Author of the
bestseller, Lead Generation for the Complex Sale, Carroll is a leading
expert in lead generation and he's profiled and regularly quoted in
numerous publications.
Carroll also speaks to 20,000 people a year on improving sales
effectiveness and lead generation strategies. He has been profiled and
regularly quoted in numerous publications such as BtoB magazine,
Selling Power, The Wall Street Journal, Entrepreneur, Target Marketing,
Inc., Marketing News, DM News, MarketingProfs, MarketingSherpa,
Software CEO and CMO Magazine.
@brianjcarroll
3
MECLABS: A science lab with a consultancy
• More than 10 years of research
• 1,300+ major experiments
• Over 1 billion emails
• 10,000 sales-paths tested
• Hundreds of publications and
conferences
4
We build custom micro research labs within
companies around the world
Optimizing the Lead
Identify the right companies and people
Segment, score and prioritize
Initiate a memorable conversation
Nurture regardless of time to buy
1
2
3
4
Segment, score and prioritize
Initiate a memorable conversation
Nurture regardless of time to buy
2
3
4
Optimizing the Lead
Identify the right companies and people1
Case StudyTesting quality data and teleprospecting - How a
telecom firm reduced prospecting costs by over 60%
8
Response-to-Sales-Accepted-Lead
Conversion Rate 10% Lead-to-Sale
Conversion Rate 20%
8
Tele-
Prospecting
Funnel
Inside
Sales
Funnel
Dial
Connection
Conversation
Buyer Conversation
Qualified Account
Acknowledged Need
Sales-Ready Lead
Sales-Validated Leads
Dial
Connection
Conversation
Buyer Conversation
Valid Lead
Forecast
Verbal Commitment
Deal
1
9
Case Study
Background: A telecom organization engaged MECLABS for lead generation
Objective: To determine if higher-cost/higher-quality data can drive down
overall cost-per-lead, so we can focus on the most efficient list source.
Primary research question: Which campaign data source will drive the
most efficient value?
Test Design: Four multi-source lists, a user-generated list, and a single-
source list were tested under consistent experiment conditions, with 300
accounts and 80 hours of teleprospecting hours.
Experiment ID: Networking equipment company funnel optimization test
Location: MECLABS Primary Research Library
Test Protocol: CS31556
Research Notes:
1
10
Case Study: Test design
Per segment: 300 accounts, 80 hours of calling
*
Segments
Record
cost
Validated
Multi-source 1 $24.00 Phone – role-based
Multi-source 2 $14.50 Phone – title-based
Multi-source 3 $6.00 Phone – validated
Multi-source 4 $3.00 Email – validated
User-generated $1.00 Business cards
Single-source $0.49 No validation
1
11
Case Study: Per record cost
$0
$5
$10
$15
$20
$25
$30
Multi 1 Multi 2 Multi 3 Multi 4 User-gen Single
$24
$1
1
12
Case Study: Results
Segments
Record
cost
No longer with
company
Dials to
disqualify
Dials to sales-
ready lead
Multi-source 1 $24.00 1% 90 77
Multi-source 2 $14.50 .06% 53 110
Multi-source 3 $6.00 14% 27 127
Multi-source 4 $3.00 23% 26 135
User-generated $1.00 67% 11 240
Single-source $0.49 13.3% 7 210
1
13
Case Study: Results and ROI
Segments
Record
cost
Call-per-
lead
List
count
Leads
Cost-per-
lead
List cost
Multi-source 1 $24.00 77 1000 312 $373.45 $24,000
Multi-source 2 $14.50 110 1560 312 $496.00 $22,620
Multi-source 3 $6.00 127 2475 312 $536.58 $14,850
Multi-source 4 $3.00 135 2810 312 $546.75 $8,430
User-generated $1.00 240 9350 312 $954.00 $9,350
Single-source $0.49 210 13100 312 $828.95 $6,380
1
14
Case Study: Cost per lead
$0
$200
$400
$600
$800
$1,000
$1,200
Multi 1 Multi 2 Multi 3 Multi 4 User-gen Single
$954
$373
1
15
Case Study: Results and ROI
Segments
Record
cost
Call-per-
lead
List
count
Leads
Cost-
per-lead
List cost Call cost
Multi-source 1 $24.00 77 1000 312 $373.45 $24,000 $92,400
Multi-source 2 $14.50 110 1560 312 $496.00 $22,620 $132,132
Multi-source 3 $6.00 127 2475 312 $536.58 $14,850 $152,460
Multi-source 4 $3.00 135 2810 312 $546.75 $8,430 $162,278
User-generated $1.00 240 9350 312 $954.00 $9,350 $287,980
Single-source $0.49 210 13100 312 $828.95 $6,380 $252,175
1
16
Case Study: Cost of calling
$0
$50,000
$100,000
$150,000
$200,000
$250,000
$300,000
$350,000
Multi 1 Multi 2 Multi 3 Multi 4 User-gen Single
$288k
$92k
1
17
Case Study: Results
Segments Record cost
Cost-per-
lead
List cost Call cost Total cost
Multi 1 $24 $373 $24,000 $92,400 $116,400
User-gen $1 $954 $9,350 $287,980 $297,330
Difference ($14,650) $195,580 $180,930
60.85% Decrease in campaign costs
The $26/record list requires over 60% more list and
teleprospecting investment than the $1/record list
1
18
Case Study: Results
What you need to understand: The ‘best deal’ list results in a
campaign that is 2.5 more costly than the most efficient list.
*
60.85% Decrease in campaign costs
The $26/record list requires over 60% more list and
teleprospecting investment than the $1/record list
1
Identify the right companies and people
Key Takeaways
• “Cheap” data is really expensive.
• The less you spend on data, the more you will spend
on teleprospecting.
• We must see list acquisition as strategic, not simply
transactional.
1
Identify the right companies and people
Initiate a memorable conversation
Nurture regardless of time to buy
1
3
4
Optimizing the Lead
Segment, score and prioritize2
21
Sample Marketing and Sales Process
Lead
Capture
Segment and
Score Leads
Qualify and
Nurture
Sales
Engagement
Analyze
Results
Capture leads
Normalize data
Enrich data
Merge de-dupe
Segment leads
by potential
Apply lead score:
lead data
lead behavior
ULD
Qualify phone-
ready leads
Distribute sales-
ready leads
Analyze data
Close the loop
Leads converted
Sales pipeline
Sales closed
Overview deck
Opportunity
Approach deck
Proposal and LOA
Close
2
22
Step 1. Lead Capture
Web inquiries
Sales generated
Subscribers
Social media
Inquiries
Event registrants
and attendees
Webinar
registrants / inquiries
Enrich
data
Unusable
data
store
Merge and
de-dupe
Normalize
data
External
firmographic
data
2
23
Step 2. Segment & Score Leads
Segment for
Next Action
Sales Qualification & Discovery
Human
Interpretation
(qualitative)
Segmentation
based on
potential
(quantitative)Lead
Scoring
Phone Qualification & Discovery
Touch points
(e.g., what content have they engaged?)
Match Function and DM Role :
Champion/influencer or DMkr?
FIT? Meets minimum ICP :
> $Xmillion Rev. and industry fit
Candidate-Supplied Data
(e.g., Registration Forms)
Lead
Capture
Segment
& Score
Qualify &
Nurture
Sales
Engagement
Analyze
Results
Opportunity
Scoring
2
Case StudyHow an technology reduced cost per lead by 75%
Background: A B2B eDiscovery technology and services provider had 25
list sources available. Data was assigned to sales reps as new list sources
were attained without regard for list source performance.
Goal: To drive most efficient pipeline and revenue through
teleprospecting
Primary research question: Which list will drive the most efficient lead
generation?
Approach: Prioritize calling based on the quality and efficiency of the list
sources. Each source was called for 80 to 100 hours.
Experiment ID: (Protected)
Location: MECLABS Leads Group Library
Test Protocol Number: TP1226
Research Notes:

25
Experiment: Background
2
26
Experiment #2: The client request
• Marketing campaign and media
source driven lists
• Lists were prioritized
chronologically
• Focus on testing a new media
source
Other possible reasons:
• A lot of money was spent on
list/sponsorship
• Client liked X event
• Gut feel
2
27
Experiment #2: Results
List Source Leads Calls
DM
Contacts
Webcast 1/18/11 Registered 7 58 10
Show-6/16/2011 7 151 25
Webcast 1/18/11 Registered & Attended 3 85 17
2010 Los Angeles 2 67 10
Lead List 7.2 42 1550 163
Document Review 1 43 6
List 4/12/2011 2 87 8
Prospects_Bay Area_CA 4 185 14
2011 New York 8 372 48
Phase 2 list 5 245 28
Event list 5.5.2011 2 112 15
Google campaign 5-4-2011 1 62 3
2010 – Booth 9/23/10 3 267 18
Show - 5/20/2010 1 89 4
Phase 1 list 4 416 24
Notes list 2010-05-24 7 753 62
Expo and Conference 2010 5 570 53
Annual meeting 2010-11-15 8 968 105
Exchange list 2010-05-24 3 404 28
2010: webcast 7 972 94
Webcast - 2/10/11 3 454 44
Sponsorship summer 2010 1 162 10
One Master Append 2010-06-15 11 2259 132
List 5-5-2011 1 278 31
Final List 2010-06-24 1 578 40
Total 139 11187 992
2
28
List Source Leads Calls
DM
Contacts
Contact % Calls/Lead
Contact/
Lead
Webcast 1/18/11 Registered 7 58 10 17% 8 1
Show-6/16/2011 7 151 25 17% 22 4
Webcast 1/18/11 Registered & Attended 3 85 17 20% 28 6
2010 Los Angeles 2 67 10 15% 34 5
Lead List 7.2 42 1550 163 11% 37 4
Document Review 1 43 6 14% 43 6
List 4/12/2011 2 87 8 9% 44 4
Prospects_Bay Area_CA 4 185 14 8% 46 4
2011 New York 8 372 48 13% 47 6
Phase 2 list 5 245 28 11% 49 6
Event list 5.5.2011 2 112 15 13% 56 8
Google campaign 5-4-2011 1 62 3 5% 62 3
2010 – Booth 9/23/10 3 267 18 7% 89 6
Show - 5/20/2010 1 89 4 4% 89 4
Phase 1 list 4 416 24 6% 104 6
Notes list 2010-05-24 7 753 62 8% 108 9
Expo and Conference 2010 5 570 53 9% 114 11
Annual meeting 2010-11-15 8 968 105 11% 121 13
Exchange list 2010-05-24 3 404 28 7% 135 9
2010: webcast 7 972 94 10% 139 13
Webcast - 2/10/11 3 454 44 10% 151 15
Sponsorship summer 2010 1 162 10 6% 162 10
One Master Append 2010-06-15 11 2259 132 6% 205 12
List 5-5-2011 1 278 31 11% 278 31
Final List 2010-06-24 1 578 40 7% 578 40
Total 139 11187 992 9% 80 7
Experiment #2: Results
2
29
List Source Leads Calls
DM
Contacts
Contact % Calls/Lead
Contact/
Lead
Hours
Calling
Cost
Cost/Lead
Webcast 1/18/11 Registered 7 58 10 17% 8 1 6 $ 348 $ 50
Show-6/16/2011 7 151 25 17% 22 4 15 $ 906 $ 129
Webcast 1/18/11 Registered & Attended 3 85 17 20% 28 6 9 $ 510 $ 170
2010 Los Angeles 2 67 10 15% 34 5 7 $ 402 $ 201
Lead List 7.2 42 1550 163 11% 37 4 155 $ 9,300 $ 221
Document Review 1 43 6 14% 43 6 4 $ 258 $ 258
List 4/12/2011 2 87 8 9% 44 4 9 $ 522 $ 261
Prospects_Bay Area_CA 4 185 14 8% 46 4 19 $ 1,110 $ 278
2011 New York 8 372 48 13% 47 6 37 $ 2,232 $ 279
Phase 2 list 5 245 28 11% 49 6 25 $ 1,470 $ 294
Event list 5.5.2011 2 112 15 13% 56 8 11 $ 672 $ 336
Google campaign 5-4-2011 1 62 3 5% 62 3 6 $ 372 $ 372
2010 – Booth 9/23/10 3 267 18 7% 89 6 27 $ 1,602 $ 534
Show - 5/20/2010 1 89 4 4% 89 4 9 $ 534 $ 534
Phase 1 list 4 416 24 6% 104 6 42 $ 2,496 $ 624
Notes list 2010-05-24 7 753 62 8% 108 9 75 $ 4,518 $ 645
Expo and Conference 2010 5 570 53 9% 114 11 57 $ 3,420 $ 684
Annual meeting 2010-11-15 8 968 105 11% 121 13 97 $ 5,808 $ 726
Exchange list 2010-05-24 3 404 28 7% 135 9 40 $ 2,424 $ 808
2010: webcast 7 972 94 10% 139 13 97 $ 5,832 $ 833
Webcast - 2/10/11 3 454 44 10% 151 15 45 $ 2,724 $ 908
Sponsorship summer 2010 1 162 10 6% 162 10 16 $ 972 $ 972
One Master Append 2010-06-15 11 2259 132 6% 205 12 226 $ 13,554 $ 1,232
List 5-5-2011 1 278 31 11% 278 31 28 $ 1,668 $ 1,668
Final List 2010-06-24 1 578 40 7% 578 40 58 $ 3,468 $ 3,468
Total 139 11187 992 9% 80 7 1119 $ 67,122 $ 483
Experiment #2: Results
2
30
Experiment #2: Results (not prioritized)
List Source Leads Calls
DM
Contacts
Contact % Calls/Lead
Contact/
Lead
Hours Calling Cost Cost/Lead
2010 – Booth 9/23/10 3 267 18 7% 89 6 27 $ 1,602 $ 534
Show - 5/20/2010 1 89 4 4% 89 4 9 $ 534 $ 534
Phase 1 list 4 416 24 6% 104 6 42 $ 2,496 $ 624
Notes list 2010-05-24 7 753 62 8% 108 9 75 $ 4,518 $ 645
Expo and Conference 2010 5 570 53 9% 114 11 57 $ 3,420 $ 684
Annual meeting 2010-11-15 8 968 105 11% 121 13 97 $ 5,808 $ 726
Exchange list 2010-05-24 3 404 28 7% 135 9 40 $ 2,424 $ 808
2010: webcast 7 972 94 10% 139 13 97 $ 5,832 $ 833
Webcast - 2/10/11 3 454 44 10% 151 15 45 $ 2,724 $ 908
Sponsorship summer 2010 1 162 10 6% 162 10 16 $ 972 $ 972
One Master Append 2010-06-15 11 2259 132 6% 205 12 226 $ 13,554 $ 1,232
List 5-5-2011 1 278 31 11% 278 31 28 $ 1,668 $ 1,668
Final List 2010-06-24 1 578 40 7% 578 40 58 $ 3,468 $ 3,468
Total 55 8170 645 8% 149 12 817 $ 49,020 $ 891
2
31
List Source Leads Calls
DM
Contacts
Contact % Calls/Lead
Contact/
Lead
Hours
Calling
Cost
Cost/Lead
Webcast 1/18/11 Registered 7 58 10 17% 8 1 6 $ 348 $ 50
Show-6/16/2011 7 151 25 17% 22 4 15 $ 906 $ 129
Webcast 1/18/11 Registered & Attended 3 85 17 20% 28 6 9 $ 510 $ 170
2010 Los Angeles 2 67 10 15% 34 5 7 $ 402 $ 201
Lead List 7.2 42 1550 163 11% 37 4 155 $ 9,300 $ 221
Document Review 1 43 6 14% 43 6 4 $ 258 $ 258
List 4/12/2011 2 87 8 9% 44 4 9 $ 522 $ 261
Prospects_Bay Area_CA 4 185 14 8% 46 4 19 $ 1,110 $ 278
2011 New York 8 372 48 13% 47 6 37 $ 2,232 $ 279
Phase 2 list 5 245 28 11% 49 6 25 $ 1,470 $ 294
Event list 5.5.2011 2 112 15 13% 56 8 11 $ 672 $ 336
Google campaign 5-4-2011 1 62 3 5% 62 3 6 $ 372 $ 372
Total 84 3017 347 12% 36 4 301.7 $ 18,102 $ 216
Experiment #2: Results (prioritized)
2
Approach Calls/Lead Cost/Lead
Worst Case 149 $891
Average 80 $483
Optimized 36 $216
Difference 113 $675
What you need to understand: The overall calling cost per lead would
decrease by 76% if the calling team focused on the client’s most efficient lists.
32
Results
!
75% Decrease in calling cost per lead
2
Segment, score and prioritize: takeaways
• You don't always need to start with a new list. You can
optimize the ROI from your current lists by testing
and prioritizing.
• Testing lists gives you the ability to guide your
present and future marketing initiatives.
• Over time, testing will reveal patterns customer
behavior.
• However, in your testing, don’t neglect qualitative
analysis (e.g., conversations, questions, objections)
2
34
List Quality Guidelines
Bad: A disqualified lead for every 25 calls
Average: A disqualified lead for every 50 calls
Better: A disqualified lead for every 100 calls
Bad: A sales lead for every 100 calls
Average: A sales lead for every 50 calls
Better: A sales lead for every 25 calls
Dials to Sale: LOWER is better
Dials to Disqualifications: HIGHER is better
2
Identify the right companies and people
Segment, score and prioritize
Nurture regardless of time to buy
1
2
4
Optimizing the Lead
Initiate a memorable conversation3
36
Timing+
Relevance
Memorable
3
37
Timing+
Relevance
Memorable
TIME YOUR
TOUCHES
3
38
Lead Generation Model
INQUIRY CUSTOMER
Identify
Need
Make
Decision
3
39
Lead Generation Model
INQUIRY CUSTOMERLEAD
Research
Solutions
Identify
Need
Make
Decision
3
40
Lead Generation Model
INQUIRY CUSTOMERLEAD SALES-READY
LEAD
Research
Solutions
Develop
Short List
Identify
Need
Make
Decision
3
41
Lead Generation Model
INQUIRY CUSTOMERQUALIFIED
PROSPECT
LEAD SALES-READY
LEAD
Research
Solutions
Develop
Short List
Identify
Need
Review
Proposals
Make
Decision
3
42
Lead Generation Model
INQUIRY CUSTOMERQUALIFIED
PROSPECT
LEAD SALES-READY
LEAD
Research
Solutions
Develop
Short List
Identify
Need
Review
Proposals
Make
Decision
Branding
Advertising
PR
SEO
Website
Direct Mail
Events
Tradeshows
Webinars
Outbound
calls
Inbound
800#
Lead
Nurture
Opt-in
Email
Conference
Calls
Face to Face
Follow-up
3
43
Lead Generation Model
INQUIRY CUSTOMERQUALIFIED
PROSPECT
LEAD SALES-READY
LEAD
Research
Solutions
Develop
Short List
Identify
Need
Review
Proposals
Make
Decision
Branding
Advertising
PR
SEO
Website
Direct Mail
Outbound
calls
Inbound
800#
Lead
Nurture
Opt-in
Email
Conference
Calls
Face to Face
Follow-up
Broadly Targeted
Less Interactive
Less Measurable
Narrowly Targeted
Highly Interactive
Highly Measurable
3
Events
Tradeshows
Webinars
44
Multi-modal Lead Generation
3
Identify the right companies and people
Segment, score and prioritize
Initiate a memorable conversation
1
2
3
Optimizing the Lead
Nurture regardless of time to buy4
46
Case Study
Background: An IT management firm engaged MECLABS for lead generation
$80 million annual revenue
100 channel partners
27 sales people, 10 marketers
Objective: To determine if basic lead management can improve pipeline
Test Design: Creation of a ULD, lead qualification, lead nurturing, clear lead
handoff and feedback process.
Experiment ID: IT desktop management firm
Location: MECLABS Leads Group Research Library
Test Protocol: LG4028
Research Notes:
4
Case Study: Challenges
• < 2% lead-to-sale pipeline conversion
• Marketing felt leads were going into a “black hole”
• No closed-loop feedback process
• Unable to measure ROI
Moreactivitybutthesameresults
*
4
48
Case Study: The approach
Closed Loop
Feedback
Marketing
Pipeline
Sales
Pipeline
Customers
Returned
Prospects
Events, Events, Summits, Guides, Subscribers, Website, Teleprospecting
Sales Ready
Leads
Not a Fit
Sales
Generated
Leads
Existing
Clients
CRM
Measure ROI
HANDOFF
Level 3,4,5 Leads
Inquiries (Level 1)
Nurturing (Level 2)
4
49
Case Study: Results
375% Increase in sales-ready leads
200% Improved lead-to-sales opportunity
$4.9 M Additional sales pipeline in 8 months
4
50
Case Study: Results
375% Increase in sales-ready leads
200% Improved lead-to-sales opportunity
$4.9M Additional sales pipeline in 8 months
What you need to understand: By actively nurturing
and closing the loop, improved lead to sales
opportunity and pipeline increases are achieved*
4
51
Understand
Audience
Organize
Content
Track Results
and
Engagement
Execute
Tracks
Messaging
Strategy
A relevant, consistent conversation with viable potential customers,
regardless of their timing to buy.
•Touch
•Track
•Follow-
Up
1
•Touch
•Track
•Follow-
Up
2
•Touch
•Track
•Follow-
Up
3
•Touch
•Track
•Follow-
Up
4
Progressive Lead Movement Across Buying Stages
What is lead nurturing?
4
52
Align messaging to roles and needs
Connect with your personas:
• Project Leader
• CIO
• Contact Center
• Field Service Center
• Executive Sponsor
• Stakeholders
CIO Q1
Month 1 Free executive report via direct mail with follow-up call
Month 2 Invitation to executive roundtable via email with follow-up call
Month 3 Link to relevant Podcast via email with follow-up voicemail
IT Director Q1
Month 1 3rd party article via email and voicemail
Month 2 3rd party article via email with follow-up
Month 3 Link to relevant webinar via email with follow-up call
IT Manager Q1
Month 1 Relevant white paper via email with voicemail
Month 2 Direct mail piece
Month 3 Invitation to webcast via email with follow-up call
Multi-track lead nurturing timeline
Client Plan for Q1 Audience: 3 Contacts Deep
4
53
Align messaging to roles and needs
Connect with your personas:
• Project Leader
• CIO
• Contact Center
• Field Service Center
• Executive Sponsor
• Stakeholders
CIO Q1
Month 1 Free executive report via direct mail with follow-up call
Month 2 Invitation to executive roundtable via e-mail with follow-up call
Month 3 Link to relevant Podcast via e-mail with follow-up voicemail
IT Director Q1
Month 1 3rd party article via e-mail and voice mail
Month 2 3rd party article via e-mail with follow-up
Month 3 Link to relevant webinar via e-mail with follow-up call
IT Manager Q1
Month 1 Relevant white paper via e-mail with voice mail
Month 2 Direct mail piece
Month 3 Invitation to webcast via e-mail with follow-up call
Multi-track lead nurturing timeline
Client Plan for Q1 Audience: 3 Contacts Deep
BUILD YOUR
TRACKS
4
54
Repurpose quality content
Research chart
4
55
Repurpose quality content
Tactical tool download
Blog post
Video clipWebinar
Email
Research chart
4
56
Measure and refine
Tactical tool download
Blog post
Video clipWebinar
Email
Research chart
Registrants
Attendees
Replays
Views
Likes/Dislikes
Social Shares
Page views
Comments
Social Shares
Opens
Clickthroughs
Shares
Downloads
Social Shares
Lead Capture
4
Optimizing the Lead
Identify the right companies and people
Segment, score and prioritize
Initiate a memorable conversation
Nurture regardless of time to buy
1
2
3
4
58
Takeaways: Identify
Collaborate with your sales team to determine
and do list testing
1
59
Takeaways: Prioritize
Set up a process that allows your team
to increase pipeline velocity
2
60
Takeaways: Initiate
Match your conversation timing and
relevance with your customer’s stage
3
INQUIRY CUSTOMERQUALIFIED
PROSPECT
LEAD SALES-READY
LEAD
Research
Solutions
Develop
Short List
Identify
Need
Review
Proposals
Make
Decision
61
Takeaways: Nurture
Nurture leads, regardless of time to buy4
62
Submit your Research Application:
MECLABS.com/contact
Questions?
A data-driven optimization process
that goes beyond lead capture
Optimizing the Lead
Brian Carroll
Executive Director, Revenue Optimization
MECLABS

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Optimizing the Lead: A Data Driven Optimization Process - Brian Carroll

  • 1. A data-driven optimization process that goes beyond lead capture Optimizing the Lead Brian Carroll Executive Director, Revenue Optimization MECLABS
  • 2. 2 Session Speaker Brian Carroll Executive Director of Revenue Optimization MECLABS Brian Carroll is Executive Director of Applied Research at MECLABS and CEO of InTouch, part of the MECLABS Group. Author of the bestseller, Lead Generation for the Complex Sale, Carroll is a leading expert in lead generation and he's profiled and regularly quoted in numerous publications. Carroll also speaks to 20,000 people a year on improving sales effectiveness and lead generation strategies. He has been profiled and regularly quoted in numerous publications such as BtoB magazine, Selling Power, The Wall Street Journal, Entrepreneur, Target Marketing, Inc., Marketing News, DM News, MarketingProfs, MarketingSherpa, Software CEO and CMO Magazine. @brianjcarroll
  • 3. 3 MECLABS: A science lab with a consultancy • More than 10 years of research • 1,300+ major experiments • Over 1 billion emails • 10,000 sales-paths tested • Hundreds of publications and conferences
  • 4. 4 We build custom micro research labs within companies around the world
  • 5. Optimizing the Lead Identify the right companies and people Segment, score and prioritize Initiate a memorable conversation Nurture regardless of time to buy 1 2 3 4
  • 6. Segment, score and prioritize Initiate a memorable conversation Nurture regardless of time to buy 2 3 4 Optimizing the Lead Identify the right companies and people1
  • 7. Case StudyTesting quality data and teleprospecting - How a telecom firm reduced prospecting costs by over 60%
  • 8. 8 Response-to-Sales-Accepted-Lead Conversion Rate 10% Lead-to-Sale Conversion Rate 20% 8 Tele- Prospecting Funnel Inside Sales Funnel Dial Connection Conversation Buyer Conversation Qualified Account Acknowledged Need Sales-Ready Lead Sales-Validated Leads Dial Connection Conversation Buyer Conversation Valid Lead Forecast Verbal Commitment Deal 1
  • 9. 9 Case Study Background: A telecom organization engaged MECLABS for lead generation Objective: To determine if higher-cost/higher-quality data can drive down overall cost-per-lead, so we can focus on the most efficient list source. Primary research question: Which campaign data source will drive the most efficient value? Test Design: Four multi-source lists, a user-generated list, and a single- source list were tested under consistent experiment conditions, with 300 accounts and 80 hours of teleprospecting hours. Experiment ID: Networking equipment company funnel optimization test Location: MECLABS Primary Research Library Test Protocol: CS31556 Research Notes: 1
  • 10. 10 Case Study: Test design Per segment: 300 accounts, 80 hours of calling * Segments Record cost Validated Multi-source 1 $24.00 Phone – role-based Multi-source 2 $14.50 Phone – title-based Multi-source 3 $6.00 Phone – validated Multi-source 4 $3.00 Email – validated User-generated $1.00 Business cards Single-source $0.49 No validation 1
  • 11. 11 Case Study: Per record cost $0 $5 $10 $15 $20 $25 $30 Multi 1 Multi 2 Multi 3 Multi 4 User-gen Single $24 $1 1
  • 12. 12 Case Study: Results Segments Record cost No longer with company Dials to disqualify Dials to sales- ready lead Multi-source 1 $24.00 1% 90 77 Multi-source 2 $14.50 .06% 53 110 Multi-source 3 $6.00 14% 27 127 Multi-source 4 $3.00 23% 26 135 User-generated $1.00 67% 11 240 Single-source $0.49 13.3% 7 210 1
  • 13. 13 Case Study: Results and ROI Segments Record cost Call-per- lead List count Leads Cost-per- lead List cost Multi-source 1 $24.00 77 1000 312 $373.45 $24,000 Multi-source 2 $14.50 110 1560 312 $496.00 $22,620 Multi-source 3 $6.00 127 2475 312 $536.58 $14,850 Multi-source 4 $3.00 135 2810 312 $546.75 $8,430 User-generated $1.00 240 9350 312 $954.00 $9,350 Single-source $0.49 210 13100 312 $828.95 $6,380 1
  • 14. 14 Case Study: Cost per lead $0 $200 $400 $600 $800 $1,000 $1,200 Multi 1 Multi 2 Multi 3 Multi 4 User-gen Single $954 $373 1
  • 15. 15 Case Study: Results and ROI Segments Record cost Call-per- lead List count Leads Cost- per-lead List cost Call cost Multi-source 1 $24.00 77 1000 312 $373.45 $24,000 $92,400 Multi-source 2 $14.50 110 1560 312 $496.00 $22,620 $132,132 Multi-source 3 $6.00 127 2475 312 $536.58 $14,850 $152,460 Multi-source 4 $3.00 135 2810 312 $546.75 $8,430 $162,278 User-generated $1.00 240 9350 312 $954.00 $9,350 $287,980 Single-source $0.49 210 13100 312 $828.95 $6,380 $252,175 1
  • 16. 16 Case Study: Cost of calling $0 $50,000 $100,000 $150,000 $200,000 $250,000 $300,000 $350,000 Multi 1 Multi 2 Multi 3 Multi 4 User-gen Single $288k $92k 1
  • 17. 17 Case Study: Results Segments Record cost Cost-per- lead List cost Call cost Total cost Multi 1 $24 $373 $24,000 $92,400 $116,400 User-gen $1 $954 $9,350 $287,980 $297,330 Difference ($14,650) $195,580 $180,930 60.85% Decrease in campaign costs The $26/record list requires over 60% more list and teleprospecting investment than the $1/record list 1
  • 18. 18 Case Study: Results What you need to understand: The ‘best deal’ list results in a campaign that is 2.5 more costly than the most efficient list. * 60.85% Decrease in campaign costs The $26/record list requires over 60% more list and teleprospecting investment than the $1/record list 1
  • 19. Identify the right companies and people Key Takeaways • “Cheap” data is really expensive. • The less you spend on data, the more you will spend on teleprospecting. • We must see list acquisition as strategic, not simply transactional. 1
  • 20. Identify the right companies and people Initiate a memorable conversation Nurture regardless of time to buy 1 3 4 Optimizing the Lead Segment, score and prioritize2
  • 21. 21 Sample Marketing and Sales Process Lead Capture Segment and Score Leads Qualify and Nurture Sales Engagement Analyze Results Capture leads Normalize data Enrich data Merge de-dupe Segment leads by potential Apply lead score: lead data lead behavior ULD Qualify phone- ready leads Distribute sales- ready leads Analyze data Close the loop Leads converted Sales pipeline Sales closed Overview deck Opportunity Approach deck Proposal and LOA Close 2
  • 22. 22 Step 1. Lead Capture Web inquiries Sales generated Subscribers Social media Inquiries Event registrants and attendees Webinar registrants / inquiries Enrich data Unusable data store Merge and de-dupe Normalize data External firmographic data 2
  • 23. 23 Step 2. Segment & Score Leads Segment for Next Action Sales Qualification & Discovery Human Interpretation (qualitative) Segmentation based on potential (quantitative)Lead Scoring Phone Qualification & Discovery Touch points (e.g., what content have they engaged?) Match Function and DM Role : Champion/influencer or DMkr? FIT? Meets minimum ICP : > $Xmillion Rev. and industry fit Candidate-Supplied Data (e.g., Registration Forms) Lead Capture Segment & Score Qualify & Nurture Sales Engagement Analyze Results Opportunity Scoring 2
  • 24. Case StudyHow an technology reduced cost per lead by 75%
  • 25. Background: A B2B eDiscovery technology and services provider had 25 list sources available. Data was assigned to sales reps as new list sources were attained without regard for list source performance. Goal: To drive most efficient pipeline and revenue through teleprospecting Primary research question: Which list will drive the most efficient lead generation? Approach: Prioritize calling based on the quality and efficiency of the list sources. Each source was called for 80 to 100 hours. Experiment ID: (Protected) Location: MECLABS Leads Group Library Test Protocol Number: TP1226 Research Notes:  25 Experiment: Background 2
  • 26. 26 Experiment #2: The client request • Marketing campaign and media source driven lists • Lists were prioritized chronologically • Focus on testing a new media source Other possible reasons: • A lot of money was spent on list/sponsorship • Client liked X event • Gut feel 2
  • 27. 27 Experiment #2: Results List Source Leads Calls DM Contacts Webcast 1/18/11 Registered 7 58 10 Show-6/16/2011 7 151 25 Webcast 1/18/11 Registered & Attended 3 85 17 2010 Los Angeles 2 67 10 Lead List 7.2 42 1550 163 Document Review 1 43 6 List 4/12/2011 2 87 8 Prospects_Bay Area_CA 4 185 14 2011 New York 8 372 48 Phase 2 list 5 245 28 Event list 5.5.2011 2 112 15 Google campaign 5-4-2011 1 62 3 2010 – Booth 9/23/10 3 267 18 Show - 5/20/2010 1 89 4 Phase 1 list 4 416 24 Notes list 2010-05-24 7 753 62 Expo and Conference 2010 5 570 53 Annual meeting 2010-11-15 8 968 105 Exchange list 2010-05-24 3 404 28 2010: webcast 7 972 94 Webcast - 2/10/11 3 454 44 Sponsorship summer 2010 1 162 10 One Master Append 2010-06-15 11 2259 132 List 5-5-2011 1 278 31 Final List 2010-06-24 1 578 40 Total 139 11187 992 2
  • 28. 28 List Source Leads Calls DM Contacts Contact % Calls/Lead Contact/ Lead Webcast 1/18/11 Registered 7 58 10 17% 8 1 Show-6/16/2011 7 151 25 17% 22 4 Webcast 1/18/11 Registered & Attended 3 85 17 20% 28 6 2010 Los Angeles 2 67 10 15% 34 5 Lead List 7.2 42 1550 163 11% 37 4 Document Review 1 43 6 14% 43 6 List 4/12/2011 2 87 8 9% 44 4 Prospects_Bay Area_CA 4 185 14 8% 46 4 2011 New York 8 372 48 13% 47 6 Phase 2 list 5 245 28 11% 49 6 Event list 5.5.2011 2 112 15 13% 56 8 Google campaign 5-4-2011 1 62 3 5% 62 3 2010 – Booth 9/23/10 3 267 18 7% 89 6 Show - 5/20/2010 1 89 4 4% 89 4 Phase 1 list 4 416 24 6% 104 6 Notes list 2010-05-24 7 753 62 8% 108 9 Expo and Conference 2010 5 570 53 9% 114 11 Annual meeting 2010-11-15 8 968 105 11% 121 13 Exchange list 2010-05-24 3 404 28 7% 135 9 2010: webcast 7 972 94 10% 139 13 Webcast - 2/10/11 3 454 44 10% 151 15 Sponsorship summer 2010 1 162 10 6% 162 10 One Master Append 2010-06-15 11 2259 132 6% 205 12 List 5-5-2011 1 278 31 11% 278 31 Final List 2010-06-24 1 578 40 7% 578 40 Total 139 11187 992 9% 80 7 Experiment #2: Results 2
  • 29. 29 List Source Leads Calls DM Contacts Contact % Calls/Lead Contact/ Lead Hours Calling Cost Cost/Lead Webcast 1/18/11 Registered 7 58 10 17% 8 1 6 $ 348 $ 50 Show-6/16/2011 7 151 25 17% 22 4 15 $ 906 $ 129 Webcast 1/18/11 Registered & Attended 3 85 17 20% 28 6 9 $ 510 $ 170 2010 Los Angeles 2 67 10 15% 34 5 7 $ 402 $ 201 Lead List 7.2 42 1550 163 11% 37 4 155 $ 9,300 $ 221 Document Review 1 43 6 14% 43 6 4 $ 258 $ 258 List 4/12/2011 2 87 8 9% 44 4 9 $ 522 $ 261 Prospects_Bay Area_CA 4 185 14 8% 46 4 19 $ 1,110 $ 278 2011 New York 8 372 48 13% 47 6 37 $ 2,232 $ 279 Phase 2 list 5 245 28 11% 49 6 25 $ 1,470 $ 294 Event list 5.5.2011 2 112 15 13% 56 8 11 $ 672 $ 336 Google campaign 5-4-2011 1 62 3 5% 62 3 6 $ 372 $ 372 2010 – Booth 9/23/10 3 267 18 7% 89 6 27 $ 1,602 $ 534 Show - 5/20/2010 1 89 4 4% 89 4 9 $ 534 $ 534 Phase 1 list 4 416 24 6% 104 6 42 $ 2,496 $ 624 Notes list 2010-05-24 7 753 62 8% 108 9 75 $ 4,518 $ 645 Expo and Conference 2010 5 570 53 9% 114 11 57 $ 3,420 $ 684 Annual meeting 2010-11-15 8 968 105 11% 121 13 97 $ 5,808 $ 726 Exchange list 2010-05-24 3 404 28 7% 135 9 40 $ 2,424 $ 808 2010: webcast 7 972 94 10% 139 13 97 $ 5,832 $ 833 Webcast - 2/10/11 3 454 44 10% 151 15 45 $ 2,724 $ 908 Sponsorship summer 2010 1 162 10 6% 162 10 16 $ 972 $ 972 One Master Append 2010-06-15 11 2259 132 6% 205 12 226 $ 13,554 $ 1,232 List 5-5-2011 1 278 31 11% 278 31 28 $ 1,668 $ 1,668 Final List 2010-06-24 1 578 40 7% 578 40 58 $ 3,468 $ 3,468 Total 139 11187 992 9% 80 7 1119 $ 67,122 $ 483 Experiment #2: Results 2
  • 30. 30 Experiment #2: Results (not prioritized) List Source Leads Calls DM Contacts Contact % Calls/Lead Contact/ Lead Hours Calling Cost Cost/Lead 2010 – Booth 9/23/10 3 267 18 7% 89 6 27 $ 1,602 $ 534 Show - 5/20/2010 1 89 4 4% 89 4 9 $ 534 $ 534 Phase 1 list 4 416 24 6% 104 6 42 $ 2,496 $ 624 Notes list 2010-05-24 7 753 62 8% 108 9 75 $ 4,518 $ 645 Expo and Conference 2010 5 570 53 9% 114 11 57 $ 3,420 $ 684 Annual meeting 2010-11-15 8 968 105 11% 121 13 97 $ 5,808 $ 726 Exchange list 2010-05-24 3 404 28 7% 135 9 40 $ 2,424 $ 808 2010: webcast 7 972 94 10% 139 13 97 $ 5,832 $ 833 Webcast - 2/10/11 3 454 44 10% 151 15 45 $ 2,724 $ 908 Sponsorship summer 2010 1 162 10 6% 162 10 16 $ 972 $ 972 One Master Append 2010-06-15 11 2259 132 6% 205 12 226 $ 13,554 $ 1,232 List 5-5-2011 1 278 31 11% 278 31 28 $ 1,668 $ 1,668 Final List 2010-06-24 1 578 40 7% 578 40 58 $ 3,468 $ 3,468 Total 55 8170 645 8% 149 12 817 $ 49,020 $ 891 2
  • 31. 31 List Source Leads Calls DM Contacts Contact % Calls/Lead Contact/ Lead Hours Calling Cost Cost/Lead Webcast 1/18/11 Registered 7 58 10 17% 8 1 6 $ 348 $ 50 Show-6/16/2011 7 151 25 17% 22 4 15 $ 906 $ 129 Webcast 1/18/11 Registered & Attended 3 85 17 20% 28 6 9 $ 510 $ 170 2010 Los Angeles 2 67 10 15% 34 5 7 $ 402 $ 201 Lead List 7.2 42 1550 163 11% 37 4 155 $ 9,300 $ 221 Document Review 1 43 6 14% 43 6 4 $ 258 $ 258 List 4/12/2011 2 87 8 9% 44 4 9 $ 522 $ 261 Prospects_Bay Area_CA 4 185 14 8% 46 4 19 $ 1,110 $ 278 2011 New York 8 372 48 13% 47 6 37 $ 2,232 $ 279 Phase 2 list 5 245 28 11% 49 6 25 $ 1,470 $ 294 Event list 5.5.2011 2 112 15 13% 56 8 11 $ 672 $ 336 Google campaign 5-4-2011 1 62 3 5% 62 3 6 $ 372 $ 372 Total 84 3017 347 12% 36 4 301.7 $ 18,102 $ 216 Experiment #2: Results (prioritized) 2
  • 32. Approach Calls/Lead Cost/Lead Worst Case 149 $891 Average 80 $483 Optimized 36 $216 Difference 113 $675 What you need to understand: The overall calling cost per lead would decrease by 76% if the calling team focused on the client’s most efficient lists. 32 Results ! 75% Decrease in calling cost per lead 2
  • 33. Segment, score and prioritize: takeaways • You don't always need to start with a new list. You can optimize the ROI from your current lists by testing and prioritizing. • Testing lists gives you the ability to guide your present and future marketing initiatives. • Over time, testing will reveal patterns customer behavior. • However, in your testing, don’t neglect qualitative analysis (e.g., conversations, questions, objections) 2
  • 34. 34 List Quality Guidelines Bad: A disqualified lead for every 25 calls Average: A disqualified lead for every 50 calls Better: A disqualified lead for every 100 calls Bad: A sales lead for every 100 calls Average: A sales lead for every 50 calls Better: A sales lead for every 25 calls Dials to Sale: LOWER is better Dials to Disqualifications: HIGHER is better 2
  • 35. Identify the right companies and people Segment, score and prioritize Nurture regardless of time to buy 1 2 4 Optimizing the Lead Initiate a memorable conversation3
  • 38. 38 Lead Generation Model INQUIRY CUSTOMER Identify Need Make Decision 3
  • 39. 39 Lead Generation Model INQUIRY CUSTOMERLEAD Research Solutions Identify Need Make Decision 3
  • 40. 40 Lead Generation Model INQUIRY CUSTOMERLEAD SALES-READY LEAD Research Solutions Develop Short List Identify Need Make Decision 3
  • 41. 41 Lead Generation Model INQUIRY CUSTOMERQUALIFIED PROSPECT LEAD SALES-READY LEAD Research Solutions Develop Short List Identify Need Review Proposals Make Decision 3
  • 42. 42 Lead Generation Model INQUIRY CUSTOMERQUALIFIED PROSPECT LEAD SALES-READY LEAD Research Solutions Develop Short List Identify Need Review Proposals Make Decision Branding Advertising PR SEO Website Direct Mail Events Tradeshows Webinars Outbound calls Inbound 800# Lead Nurture Opt-in Email Conference Calls Face to Face Follow-up 3
  • 43. 43 Lead Generation Model INQUIRY CUSTOMERQUALIFIED PROSPECT LEAD SALES-READY LEAD Research Solutions Develop Short List Identify Need Review Proposals Make Decision Branding Advertising PR SEO Website Direct Mail Outbound calls Inbound 800# Lead Nurture Opt-in Email Conference Calls Face to Face Follow-up Broadly Targeted Less Interactive Less Measurable Narrowly Targeted Highly Interactive Highly Measurable 3 Events Tradeshows Webinars
  • 45. Identify the right companies and people Segment, score and prioritize Initiate a memorable conversation 1 2 3 Optimizing the Lead Nurture regardless of time to buy4
  • 46. 46 Case Study Background: An IT management firm engaged MECLABS for lead generation $80 million annual revenue 100 channel partners 27 sales people, 10 marketers Objective: To determine if basic lead management can improve pipeline Test Design: Creation of a ULD, lead qualification, lead nurturing, clear lead handoff and feedback process. Experiment ID: IT desktop management firm Location: MECLABS Leads Group Research Library Test Protocol: LG4028 Research Notes: 4
  • 47. Case Study: Challenges • < 2% lead-to-sale pipeline conversion • Marketing felt leads were going into a “black hole” • No closed-loop feedback process • Unable to measure ROI Moreactivitybutthesameresults * 4
  • 48. 48 Case Study: The approach Closed Loop Feedback Marketing Pipeline Sales Pipeline Customers Returned Prospects Events, Events, Summits, Guides, Subscribers, Website, Teleprospecting Sales Ready Leads Not a Fit Sales Generated Leads Existing Clients CRM Measure ROI HANDOFF Level 3,4,5 Leads Inquiries (Level 1) Nurturing (Level 2) 4
  • 49. 49 Case Study: Results 375% Increase in sales-ready leads 200% Improved lead-to-sales opportunity $4.9 M Additional sales pipeline in 8 months 4
  • 50. 50 Case Study: Results 375% Increase in sales-ready leads 200% Improved lead-to-sales opportunity $4.9M Additional sales pipeline in 8 months What you need to understand: By actively nurturing and closing the loop, improved lead to sales opportunity and pipeline increases are achieved* 4
  • 51. 51 Understand Audience Organize Content Track Results and Engagement Execute Tracks Messaging Strategy A relevant, consistent conversation with viable potential customers, regardless of their timing to buy. •Touch •Track •Follow- Up 1 •Touch •Track •Follow- Up 2 •Touch •Track •Follow- Up 3 •Touch •Track •Follow- Up 4 Progressive Lead Movement Across Buying Stages What is lead nurturing? 4
  • 52. 52 Align messaging to roles and needs Connect with your personas: • Project Leader • CIO • Contact Center • Field Service Center • Executive Sponsor • Stakeholders CIO Q1 Month 1 Free executive report via direct mail with follow-up call Month 2 Invitation to executive roundtable via email with follow-up call Month 3 Link to relevant Podcast via email with follow-up voicemail IT Director Q1 Month 1 3rd party article via email and voicemail Month 2 3rd party article via email with follow-up Month 3 Link to relevant webinar via email with follow-up call IT Manager Q1 Month 1 Relevant white paper via email with voicemail Month 2 Direct mail piece Month 3 Invitation to webcast via email with follow-up call Multi-track lead nurturing timeline Client Plan for Q1 Audience: 3 Contacts Deep 4
  • 53. 53 Align messaging to roles and needs Connect with your personas: • Project Leader • CIO • Contact Center • Field Service Center • Executive Sponsor • Stakeholders CIO Q1 Month 1 Free executive report via direct mail with follow-up call Month 2 Invitation to executive roundtable via e-mail with follow-up call Month 3 Link to relevant Podcast via e-mail with follow-up voicemail IT Director Q1 Month 1 3rd party article via e-mail and voice mail Month 2 3rd party article via e-mail with follow-up Month 3 Link to relevant webinar via e-mail with follow-up call IT Manager Q1 Month 1 Relevant white paper via e-mail with voice mail Month 2 Direct mail piece Month 3 Invitation to webcast via e-mail with follow-up call Multi-track lead nurturing timeline Client Plan for Q1 Audience: 3 Contacts Deep BUILD YOUR TRACKS 4
  • 55. 55 Repurpose quality content Tactical tool download Blog post Video clipWebinar Email Research chart 4
  • 56. 56 Measure and refine Tactical tool download Blog post Video clipWebinar Email Research chart Registrants Attendees Replays Views Likes/Dislikes Social Shares Page views Comments Social Shares Opens Clickthroughs Shares Downloads Social Shares Lead Capture 4
  • 57. Optimizing the Lead Identify the right companies and people Segment, score and prioritize Initiate a memorable conversation Nurture regardless of time to buy 1 2 3 4
  • 58. 58 Takeaways: Identify Collaborate with your sales team to determine and do list testing 1
  • 59. 59 Takeaways: Prioritize Set up a process that allows your team to increase pipeline velocity 2
  • 60. 60 Takeaways: Initiate Match your conversation timing and relevance with your customer’s stage 3 INQUIRY CUSTOMERQUALIFIED PROSPECT LEAD SALES-READY LEAD Research Solutions Develop Short List Identify Need Review Proposals Make Decision
  • 61. 61 Takeaways: Nurture Nurture leads, regardless of time to buy4
  • 62. 62 Submit your Research Application: MECLABS.com/contact
  • 64. A data-driven optimization process that goes beyond lead capture Optimizing the Lead Brian Carroll Executive Director, Revenue Optimization MECLABS

Editor's Notes

  1. Pamela intro
  2. Pamela intro
  3. The function match is happening automagically with IT (Jim) and Tanya (looking up revenue)
  4. Over the course of X weeks, the same callers, using the same scripts, called contacts at the same timeit was really driving the most pipeline and revenue. if it&apos;s three leads vs 50 leads, the client didn&apos;t care.
  5. Does not include cost of list – or of activity to get list (Ie PPC campaign, booth/expo fees and costs to execute)
  6. Does not include cost of list – or of activity to get list (Ie PPC campaign, booth/expo fees and costs to execute)
  7. Assumptions : 10 calls/hour, $6 per call
  8. Economics of having someone call manually – depends on the economics of the product Key accounts, larger ticket complex sales – senior executives worth the time – where the extra care mattersNot only intern, offshore resources available
  9. STEP 1: Understand your target audienceSTEP 2: Develop your messaging strategySTEP 3: Build your lead nurturing content librarySTEP 4: Execute multimodal and multi-touch conversationsSTEP 5: Track results and measure engagement
  10. Reference Mark and Jason
  11. Pamela intro