This document discusses personalization strategies for B2B marketing. It recommends starting by personalizing high-value customer segments and high-traffic pages using existing content. Metrics like conversion rates should be evaluated across different audiences. Both rules-based and predictive personalization are described. Rules-based personalization has challenges around managing many rules and campaigns. Predictive personalization uses machine learning to optimize audiences and engagements without human intervention by learning from past performance and attribution. The document provides many examples of personalizing content, promotions, experiences and more across the customer journey.

1. FROM ZERO TO HERO:
STARTING AND SCALING B2B
PERSONALIZATION
Arun Sivashankaran
CEO, FunnelEnvy
arun@funnelenvy.com
@funnelenvy
Takeshi Young
Web Marketing Lead, Optimizely
takeshi@optimizely.com
@takeshiyoung

2. Personalization Goal
Increase conversions for highest value
customers (accounts) through highly
relevant campaigns that lead to
engagement
✓ Which customers are most valuable
and how do we identify them?
✓ What KPIs are we optimizing for and
what engagements lead to them?
✓ What are the most effective campaigns
that will lead to these engagements?
2
Content Context
Value
P13N

3. Establishing Value
3
Lead Value
(non-target acct)
$2,000
Lead Value
(target acct)
$20,000
Lead Mix
(Non Target / Target)
90% / 10%
Weighted Lead Value $5,600
No Personalization
Lead Value
(non-target acct)
$2,000
Lead Value
(target acct)
$20,000
Lead Mix
(Non Target / Target)
50% / 50%
Weighted Lead Value $11,000
Personalization

4. Two Primary Axes
✓ Segmentation
– Account
– Individual
✓ Engagement
– Content
– Offline / Events
– Stages
4
Value
Engagement

5. Account Based Segmentation
✓ Target accounts & tiers
✓ Industry
✓ Company size
✓ Technologies
✓ Existing customers
Segmentation & Engagement
5

6. Leads
MQL / SQL
Opportunities
Expansion
Renewal / Churn
Individual
Account

7. Evaluating Conversion Rates
7
Conversion Rate = 10%
entrances
completions
TOFU (tcompletion - tentrance ~ 0)
BOFU (tcompletion - tentrance >> 0)
Example: Visitor -> SAL CR over 12 weeks
8 weeks average to convert
wk 1
wk 2
wk 11
wk 12
…
11 weeks of opportunity
< 1 week of opportunity
Time based cohorts
ConversionRate
Time
Wk 1 Wk 2 Wk 3 Wk 12
Wk 1 Wk 2 Wk 3
Wk 11 Wk 12
t

8. Evaluating Audiences
8
Conversion Rate by Audience at tConversionrate
Time based Cohort
1 2 3 4
Strategic
Enterprise
Automotive
Healthcare

9. Opportunities across the customer journey
9
Use Case KPIs
Content personalization based on firmographics (e.g. industry) &
individual (e.g. role)
Account
engagement
Real time lead nurture MQL
Differentiated experiences for existing customers Expansions,
renewals, churn
Trial conversions, onboarding experience Retention, churn
Cross channel experiences (incl retargeting, chat) Any

10. Homepage Industry Personalization
10

11. TOFU: Gated Content
11
Industry Specific Offer Location Specific Offer
Default content offer

12. Personalized Promotions
12

13. Real Time Content Nurture
13
Segmentation by lead score and personalization by
vertical to drive incremental engagement to MQL
Default B2B Retail Travel

14. Existing Customers
14
Standard Homepage
Existing Customer

15. Getting Started Tips
1. Reuse existing content
1. Personalize high value segments with existing
content on high traffic, “generic” pages
2. Focus on high leverage opportunities for engagement
1. Pricing pages, high traffic pages
3. Understand addressable traffic
1. By audience, opportunity stage, impact
4. Define data integration & activation strategy
15

16. ABM Tiers
16

17. Personalized Hero Image
17

18. Request Demo Page
18

19. Chat Experiment
19

20. PPC Landing Page
20

21. Personalized Logos
21

22. Personalized Content
22

23. Lower Tier Visitors
23

24. Other Personalization
24

25. Scaling Personalization
25

26. Extensions
26

27. Leveraging 1st Party Data
27

28. Designing w/ P13n in Mind
✓ Modular design
✓ Data attributes
✓ Personalization mentality
28

29. Modular Design
29

30. Data Attributes
30

31. Personalization Mentality
31

32. Scaling: Process
✓ Strategy - Focus on high
value opportunities
✓ Research - Evidence to
support hypotheses
✓ Experimentation - Optimize
for time to learning
✓ Analysis & Attribution
32

33. Scaling: Rules Based Personalization
33
✓ Challenges with rules based
personalization
✓ Segmentation with a variety of data
sources
✓ Number of rules to manage
✓ Number of campaigns & engagements
to optimize for
✓ Static model - Not flexible to
accommodate changes or down funnel
outcomes without human intervention

34. 34
Data Activation Challenge
1st Party
CRM Marketing
Automation
Interna
l
Behavioral
Activity
3rd Party
Reverse Cookie
Data Activation Strategy:
Account & Individual
✓ Unified segmentation
✓ Identity management
✓ Real Time performance
✓ Decisioning / Insights
– Audiences
– Engagements
✓ Outcome reporting
– Attribution

35. Predictive Personalization in B2B
35
✓ Augmented intelligence - Marketers focus on the creative
elements (UX) while automating analytical decisioning (segments,
engagements, traffic)
✓ Must work in conjunction with rules based
✓ Adapts to changing conditions and down funnel outcomes without
human intervention
Propensity
Likelihood that
certain
audiences will
convert based
on previous
engagements
Prediction
Audiences &
engagements that will
maximize conversion
outcomes
Learning
Model updated in real
time based on
attribution

36. QUESTIONS / DISCUSSION
Arun Sivashankaran
CEO, FunnelEnvy
arun@funnelenvy.com
@funnelenvy
Takeshi Young
Web Marketing Lead, Optimizely
takeshi@optimizely.com
@takeshiyoung