In this presentation I share my experiences with lead score models and nurturing in Eloqua. The presentation is 30 pages and I share my best practice. Feel free to comment.

1. Lead Scoring
Program
Visma Software AB
Gunilla Thulin Bengtsson

2. Vision
Marketing drives an automated
lead process from MQL into the
sales process (solution selling)

3. Agenda
● Preparation
● Lead Score Model
● Nurturing
● SQL to sales organisation
● Follow up and tuning
● Results

4. Preparation

5. Preparation
Marketing
Agree on
● Profile Data
● Behaviour
● Where to send identified SQLs
Sales

6. Lead Score
Model

7. Profile data
Some examples of profile data that we use:
● Company data
○ Size (number of employees)
○ Revenue
○ Industry - Based on the Swedish Standard Industrial Classification (SNI)
● Personal data
○ Title

8. Profile data - example
● Title - maximum 25%
○ CFO 25%
○ Controller 25%
○ Chief Accountant 25%
○ CEO 25%
○ Owner/board member 25%
○ Other (not empty) 12%
● Revenue (MSEK) - maximum 25%
○ 50-100 15%
○ 100-500 25%
○ 500- 15%
● Industry - 50% - all equally important
○ Real estate company
○ Electricity suppliers
○ Insurance companies
Explanations:
Title can give maximum 25% of the total profile score. All listed titles
give maximum defined score. Any other title on the contact gives
50% och the 25%.
Revenue can also give maximum 25%, which the defined sweet spot
gives. Companies with a revenue of 50-100 MSEK and over 500
MSEK are also interesting but give a little less (15%)
Industry is the most important criteria and the defined industries
give 50% of the total profile score

9. Profile data collection
● Company data
○ Automatic collection of company information on forms
■ Requiring company name on forms gives a set of company data e.g.
organization number, revenue etc.
● Personal data
○ Titles
■ A predefined set of titles are now used in drop-down lists on forms
■ All old title data were cleaned and only the predefined titles are used

10. Engagement
● Top Funnel
○ Blog posts
○ Web page visits
○ General guides
● Middle Funnel
○ More web page visits
○ Guides specific to the solution
● Bottom funnel
○ Webinar
○ Trial
○ Demo
○ Price information
○ Reference cases
○ Contact form

11. Engagement - example
● ToFu 20%
○ 1 web page visit 14 days 20%
○ Relevant blog posts 12 months 20%
● MiFu 30%
○ Relevant guide 30 days 30%
○ Customer Cases 30 days 30%
○ 2 web page visits 14 days 30%
○ 3 web page visits 30 days 30%
● BoFu 50%
○ Trial 1 month 50%
○ Webinar 1 month 50%
○ Demo/contact 1 month 50%
○ 3 web page visits 14 day 38%
○ Price information 1 month 50%
○ Detailed functionality 1 month 50%

12. Engagement - challenges
● Find a reusable model
○ Our solution: ToFu/MiFu/BoFu “groups”

13. Lead Score Model
BEHAVIOUR
PROFILE
1 2 3 4
A SQL SQL
B SQL
C
D

14. Threshold values
Threshold values are the minimum score that
a contact needs to have to move from one
level to the next. Below an example on how
the values can be calculated:
● Profile threshold values
○ C: Minimum score > 0
○ B: Industry + lowest revenue fit
○ A: Industry + revenue + title fit
● Engagement threshold values
○ 3: Lowest engagement ⇒ we know that the
contact has done “something” related to this
model
○ 2: ToFu+MiFu engagement
○ 1: BoFu engagement
ENGAGEMENT
PROFILE
1 2 3 4
A SQL SQL
B SQL
C
D

15. Testing before launch
● Test
○ Profile scoring
○ Engagement scoring
○ Threshold values
● First lead score model - almost 20 versions before launch
○ Learning by doing
● Next models - just a few versions

16. Nuturing

17. Nurturing goal
BEHAVIOUR
PROFILE
1 2 3 4
A
B
C
D

18. Communication depending on score
SQL. Sent to sales
1. Adapted communication depending
on profile and behaviour
2. No communication - no fit based on
existing profile data
3. No communication - Shown
behaviour is not relevant for this
model
BEHAVIOUR
PROFILE
1 2 3 4
A SQL SQL
B SQL
C
D
2
31

19. ● Segment: Engagement score 1, 2 or 3
○ Excluded:
■ Already customer for this solution
■ Partners
■ Visma employees
● SQL check
○ For lead score A1, A2 or B1, the contact is added to an SQL
list (Shared List)
● A number of mails aimed to move the contact to
a higher lead score are sent
○ Dynamic content based on profile score for downloads
Nurture flow - example

20. Dynamic content based on profile score
● The CTA button “Hämta rapporten” is dynamic
content
○ Default: Link to form on visma.se
○ If profile score is A or B a blind form submit is used to
display the report directly

21. Send SQL to
Sales

22. SQL Program
● Segment: SQL list
(Contact added to list in nurture flow)
● Filter away unwanted
contacts (customers, Visma etc)
● Form submit to send an
SQL notification to the
sales organisation

23. Send SQL to sales - form submit

24. Notification Configuration
Email Header Form Notification (from settings)

25. Follow up and
tuning

26. Follow-up and tuning
● Part of monthly meeting between sales, marketing and product
development
● Follow up on
○ Lead score dashboard
○ Number of SQLs sent to sales
○ Quality of SQLs
● Tuning based on quality
○ Are the companies a fit? (profile)
○ Are the contacts interested enough? (engagement)
● Example of tuning
○ Change company revenue span
○ Change of thresholds
○ New assets that needs to be added to model

27. Results
...so far

28. Result so far
● 50% cost reduction to generate an SQL
● Increased number of SQLs
● Reduced CAC (Customer Acquisition Cost) payback time

29. Vision
Marketing drives an automated
lead process from MQL into the
sales process (solution selling)
YES

30. Respect
Reliability
Innovation
Competence
Team spirit