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Deciphering a prospect’s digital body language and then using it to serve them timely and relevant content so you can send true marketing qualified leads to the sales team is at the top of most marketers “things to do" list for 2012. Learn how Axios Systems used Eloqua to develop a simple yet powerful, fully automated process with surprising results. This session will cover how to: Define a marketing qualified lead so the entire organisation is on board Build a lead scoring model to follow up on the best leads first Develop a lead nurture programme to keep warming up leads until they are ready to speak to sales Align with sales on important metrics to grow revenue
Citation preview
Greg Staunton, Marketing Campaign Manager
Axios Systems
Digital Body Language:
Deciphering your prospects„ online behaviour
2
Contents
• About Axios Systems
• Axios lead flow – Pre 2012
• What is Digital Body Language?
• What can we decipher, why?
• How can we decipher this data?
• How can we manipulate it?
• Lead Nurturing
• Defining Marketing Qualified Leads
• Sales / Marketing alignment through common metrics
• Results
3
About Axios Systems
• IT Service Management Software Vendor
• SaaS & On-Premise
• 300 Employees
• 16 Offices
• Business in over 50 countries
• Ranked as leaders by Gartner & Forrester
• £50 Million+ Global Turnover
4
Axios lead flow – Pre 2012
5
Axios lead flow – Pre 2012
6
Axios lead flow – Pre 2012
7
Axios lead flow – Pre 2012
8
Axios lead flow – Pre 2012
• Any form submission was a lead
• 38,742 “leads” passed to sales last year
• 5% Move to Opportunity – 1937 Converted
• 1 hour spent per lead -1114 working weeks to process
• 21 people to process this per year
• 201K active marketing database
• 20% active marketing database passed to sales annually
• Massive Sales Resource Loss
• Unknown Opportunity Loss
• SOMETHING HAD TO CHANGE
9
What is Digital Body Language?
Digital Body Language is the aggregate of all the digital activity
you see from an individual. Each email that is opened or clicked,
each web visit, each form, each search on Google, each
referral from a social media property, and each webinar
attended are part of the prospect's digital body language.
Steve Woods, Eloqua Inc.
http://digitalbodylanguage.blogspot.com/2009/06/what-
exactly-is-digital-body-language.html
10
What can we decipher, why?
What can we decipher:
Precisely which stage the prospect is at in the buying cycle
Why:
So we can pass over “Marketing Qualified Leads” to sales
resulting in:
• Increased sales win rate
• Increased company revenue
• Increased revenue per deal
11
How can we decipher this data?
Consumer Decision Making Process
• Problem Recognition - Something has happened
• Information Search - What are your options
• Evaluation of Alternatives - Which solution is best
• Purchase - The final decision
• Post Purchase Behaviour - Was that a good decision
Problem
Recognition
Information
Search
Evaluation of
Alternatives
Purchase Post Purchase
Behaviour
12
How did Axios Systems decipher this data?
Problem Recognition Information Search Evaluation of Alternatives
Whitepapers
Webcasts
Opens Email
Blog visitors
Social Media
Product Factsheets
Product webpage
Pricing webpage
Case Studies
Demo Request
Lead Scoring – Build an implicit model
• Define stages in your buying cycle
• Create a list of all existing and planned marketing collateral
• Place collateral in each stage of the buying cycle
13
How did Axios Systems decipher this data?
Problem Recognition Information Search Evaluation of Alternatives
5 x Whitepapers
4 x Planned
Whitepapers
------------------------------
2 x Product
Factsheets
----------------------------
1 x Case Study
-----------------------------------
Lead Scoring – Practical
• 5 x existing whitepapers, 4 x Planned whitepapers
• 2 x product factsheet, None Planned
• 1 x case study, None Planned
14
How Axios Systems decipher this data?
Problem Recognition Information Search Evaluation of Alternatives
5 x Whitepapers
4 x Planned
Whitepapers
------------------------------
Each: 1 point
Max: 9 point
2 x Product
Factsheets
----------------------------
Each: 18 points
Max: 36 points + HPS Problem Recognition
Max: 45 points
1 x Case Study
-----------------------------------
Each: 91 points
Max: 91 points
Lead Scoring – Practical
• Use bracketing for scoring – Otherwise it wont work
• Develop Lead Rating - <18 = 3, <91 = 2, >90 = 1
15
The Axios Systems Implicit Lead Scoring Model
16
How can we manipulate this data?
• Lead Nurturing Campaign
Push the right type of content, at the right time to the right
person depending on their stage in the buying cycle to
stimulate their progression from stage to stage
• Defining a Marketing Qualified Lead
Define with sales, exactly which contacts are sales ready by
their terms for hand over
17
How did Axios Systems manipulate this data?
Problem Recognition Information Search Evaluation of Alternatives
LN-Whitepaper_1
LN-Whitepaper_2
LN-Whitepaper_3
LN-Whitepaper_4
LN-Whitepaper_5
LN-ProductF_1
LN-ProductF_2
LN-CaseStudy_1
Lead Nurturing Campaign
• Develop emails to push content during engagement
• Create rules to send the next level of emails
18
Lead Nurturing Campaign
Problem Recognition Track – 19 Emails (Touchpoints)
19
Lead Nurturing Campaign
Solution Search Track – 19 Emails (Touchpoints)
20
Lead Nurturing Campaign
Shortlisting Track – 5 Emails (Product Bundles)
21
Lead Nurturing Campaign
RFP Track – 10 Emails (Industry Sectors)
22
Problem Recognition Track
23
Information Track
24
Rules to place contacts into Information Search
25
Lead Nurture Results?
Email Results (Aggregate)
26
Lead Nurture Results
Landing Page Performance (Individual)
27
Lead Nurture Results
Email Performance (Individual)
28
Defining Marketing Qualified Leads
A Marketing Qualified Lead is a prospect:
• That could do business with you
AND
• That is at the right stage of engagement for sales to talk to
You must create a sales feedback loop so sales can help you
update your criteria.
29
Defining Marketing Qualified Leads
Consumer Decision Making Process
• Problem Recognition - Something has happened
• Information Search - What are your options
• Evaluation of Alternatives - Which solution is best
• Purchase - The final decision
• Post Purchase Behaviour - Was that a good decision
Problem
Recognition
Information
Search
Evaluation of
Alternatives
Purchase Post Purchase
Behaviour
30
Defining Marketing Qualified Leads
• Implicit Lead Scoring Model
• Explicit Lead Scoring Model
31
Sales / Marketing alignment through common metrics
Funnel Status
• Marketing Qualified Lead (MQL)
• Sales Accepted Lead (SAL)
• Sales Rejected Lead (SRL)
• Sales Qualified Lead (SQL)
• Sales Recycled Lead (SRC)
• Win/Loss
32
Sales / Marketing alignment through common metrics
7.15 Million Dollars MQL – Marketing Target
33
The results… So far…
• 1165 MQLs passed to sales in 3 months
• 88% less volume
• 60% currently move to opportunity
• 2760 (predicted) converted
• 70% more opportunities than last year
• Sales concentrate on selling, not filtering
• Marketing Prediction of £55 Million Turnover
• 10% increase in revenue directly attributed to DBL 2.0
34
Thank You
Any questions?