With all the talk about predictive, a new question is emerging - can you identify prospects who are in-market but not on your site? Is intent data a good source of net new leads?

1. What’s the Deal with
I N T E N T D A T A ?

2. 1. What is 3rd-Party Intent Data?
2. Is it Predictive?
3. Is it a Good Source of Net New Leads?
4. How do I Measure the Impact?
5. Where do the Experts Come Out?
TOP 5 QUESTIONS

3. WHAT IS 3RD-PARTY INTENT DATA?
1

4. WHAT IS 3RD-PARTY INTENT DATA?
Two types of Intent Data:
Internal intent data
Activity that you’re capturing on your website, inside
your marketing automation system, or through
application logs. Because it is data you own, it is also
referred to as first-party data.
External intent data
Data collected by networks of b2b publishers either at
the IP level, or through user registration and shared
cookies. Because it is happening off your properties
this is often referred to as third-party intent data.

5. IS INTENT DATA PREDICTIVE?
2

6. Your Website Purchase
Responded
Engaged
Silent
Registered
Email Sent
Click
Form Fill
Download
Predictive Power
Internal Intent Data
Data captured by your marketing automation application, web analytics, and app logs.
IS INTENT DATA PREDICTIVE?

7. IS INTENT DATA PREDICTIVE?
Internal Intent Data
Data captured by your marketing automation application, web analytics, and app logs.
Registered Topic Match
Good Fit
Anonymous
Not a Match Weak Intensity
Match Rates
Bad Fit
Purchase
High Intensity
False Alarm
Pipeline Coverage

8. External Intent Data
Data providers include Bombora, TechTarget, IDG
Click
Click
Click
Form Fill
Download
Click
IP Lookup
Registered User
Cookie Sharing Across Sites
Silent
3rd Party Sites
Purchase
Vendors Website
Predictive Power
IS INTENT DATA PREDICTIVE?

9. External Intent Data
Data providers include Bombora, TechTarget, IDG
IS INTENT DATA PREDICTIVE?
IP Match
Topic Match High Intensity Good Fit
Unable to Match
Not a Match
Weak Intensity
Purchase
Bad Fit
False Alarm
Match Rates
Pipeline Coverage

10. A
B
C
D
1 2 3 4
0.0x 0.0x 0.0x 0.0x
0.0x 0.0x 0.0x 0.0x
0.0x 0.0x 0.0x 0.0x
0.0x 0.0x 0.0x 0.0x
behavior score
likelihood of conversion within the next 3 weeks
fit
score
good fit
to buy your
product
Predictive Scoring Matrix
Creating a 4x4 matrix helps visualize impact and effectiveness of your scoring
IS INTENT DATA PREDICTIVE?

11. Start with a Fit-First Approach
Fit scores are highly predictive offering instant insight and broad pipeline coverage
IS INTENT DATA PREDICTIVE?
A
B
C
D
6.2x
1.1x
0.6x
0.1x
behavior score
likelihood of conversion within the next 3 weeks
fit
score
good fit
to buy your
product

12. Add Behavioral Scoring
A good behavioral score should be able to predict an outcome in a set time window
IS INTENT DATA PREDICTIVE?
1 2 3 4
3.2x 0.7x 0.4x 0.0x
behavior score
likelihood of conversion within the next 3 weeks
fit
score
good fit
to buy your
product

13. Add Behavioral Scoring
A bad behavioral score is prone to false alarms and can’t light up your best prospects
IS INTENT DATA PREDICTIVE?
1 2 3 4
1.2x 1.0x 1.0x 0.9x
behavior score
likelihood of conversion within the next 3 weeks
fit
score
good fit
to buy your
product

14. The Ultimate Goal
Use the right set of predictive signals to get to a scoring matrix that looks like this
IS INTENT DATA PREDICTIVE?
A
B
C
D
1 2 3 4
8.2x 2.8x 1.2x 0.8x
2.2x 1.2x 0.6x 0.2x
1.4x 0.3x 0.2x 0.1x
0.4x 0.1x 0.0x 0.0x
behavior score
likelihood of conversion within the next 3 weeks
fit
score
good fit
to buy your
product

15. Comparison
IS INTENT DATA PREDICTIVE?
Pipeline CoveragePredictive Power
Fit Score
Internal Intent
External Intent
Measurement

16. IS INTENT A GOOD SOURCE OF
NET NEW LEADS?
3

17. IS INTENT DATA A GOOD SOURCE OF NET NEW LEADS?
New Accounts
Use third party intent data to identify
net new accounts that are in-market
to buy but not in your database. Up
to you to find the right contacts to
prospect into.
New Contacts
Use third party intent data to identify
net new contacts who are in-market
to buy but not in your database.
Volume is significantly lower that IP
matches and more expensive.
*Conversion multiplier could compare
conversion rates to other cold lists or to
inbound leads
1
Lead
Volume
Lead
Volume
Cost Per
“Good Lead”
$ Per
Task
1.0x $ $

18. IS INTENT DATA A GOOD SOURCE OF NET NEW LEADS?
Existing Accounts
Use third party intent data to append
a “buying stage” field to accounts
that already exist in your database.
Existing Contacts
Use third party intent data to append
a “buying state field to contacts that
already existing you your database.
*Conversion multiplier could compare
conversion rates to other cold lists or to
inbound leads
5%
Match
Rate
Surging and
Matched
Conversion
Multiplier
Missing
Data
.05% 1.0 95%

19. If you tell your reps that certain prospects are in-
market, and they end up on a wild goose chase,
you’ll be diverting them from more productivity
endeavors, and potentially lose
their trust.
IS INTENT DATA A GOOD SOURCE OF NET NEW LEADS?
Risk of Guessing Wrong

20. WHERE DO THE EXPERTS
COME OUT?
4

21. WHERE DO THE EXPERTS COME OUT?
Scott Fingerhut
VP Worldwide Marketing Demand Generation at Elastic
To me measuring intent is a requirement. It’s huge for not only identifying
short-term purchase potential, but matching the message to the readiness
for mid-and-long term buyers. With good intent insight you strive to make
every interaction more relevant and every relationship stronger. To use an
eHarmony analogy, having the perfect match is an important start but
sending the first intro e-mail with a proposition for marriage is not going to
lead to much..... in most cases
“

22. WHERE DO THE EXPERTS COME OUT?
Jon Miller
Co-Founder CEO of Engagio Former Co-Founder of Marketo
I’ve seen great success from using internal behavioral signals to
determine intent. Sales reps and SDRs learn over time which intent
signals work best for them, whether it is downloading a particular piece of
content, visiting a certain set of web pages, or clicking a particular kind of
ad. When they are looking at a list of prospects, they’ll naturally gravitate
to the signals they trust.
“

23. WHERE DO THE EXPERTS COME OUT?
Craig Rosenberg
Co-Founder and Chief Analyst, TOPO
I have seen positive ROI case studies with 3rdparty intent data identifying
net new leads, but it depends on the sources and the market.
For example there are companies that extract value from content
syndication leads... though most don’t. 3rd-party intent data is the SAME
THING except the media site doesn’t have to try to get them to download
your white paper - they can just tell you that they did. For some
companies, this concept can work if the conversion rates and cost per
good lead are manageable.
My hope is that all intent data can move beyond content consumption and
we can develop more predictive data points to identify intent. In other
words, it’s a good idea... but has to get better over time.
“

24. WHERE DO THE EXPERTS COME OUT?
Matt Heinz President
Heinz Marketing
Existing predictive models use demographic and firmographic data to
predict who is likely to buy and to some degree, what product they’re most
likely to select. The next leap forward is to accurately identify where
individuals are in their buying process and whether they’re likely to buy
soon. Today, first party intent data provides the best clues and broadest
pipeline coverage, but the more comprehensive view you can create, the
easier it is to tailor your follow-up messaging.
“

25. WHERE DO THE EXPERTS COME OUT?
Dan McGaw
Founder & CEO, EffinAmazing.com
I think 3rd party intent data for predictive lead generation sounds good in
theory. But the 3rd party data tends to be so limited and with so many
holes, the data does not make it predictive. I would have more faith in
buying lists of leads with emails and then running that through Infer to find
good fits.
“

26. WHERE DO THE EXPERTS COME OUT?
David Raab
Raab and Associates
Marketers and the technologist who support them need both the ideal
vision of how things would work in a world of perfect data (which isn’t
the same as a perfect world!) and the realistic understanding of what’s
likely to be practical within their planning horizon.
“

27. A
B
C
D
1 2 3 4
8.2x 2.8x 1.2x 0.8x
2.2x 1.2x 0.6x 0.2x
1.4x 0.3x 0.2x 0.1x
0.4x 0.1x 0.0x 0.0x
behavior score
likelihood of conversion within the next 3 weeks
fit
score
good fit
to buy your
product
1 Fit Score 3 External Intent2 Internal Intent
WHERE DO THE EXPERTS COME OUT?
Infer’s Approach

28. APPENDIX
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29. APPENDIX

30. Behavior
Employee Count
Geographic Location
Industry
Business Model
Technology Stack
Public Filings
Fit
Website Visits
Downloads
Email Clicks
Social Engagement
Application Usage
In Market Data
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