Measuring marketing can be painful, especially if your sales and marketing data live in different tools. Each of the tools has reports you can look at, but none won't tell you what works and what's bleeding money. In this session, Outfunnel co-founder Purde (ex-Pipedrive) shares the different ways he’s analyzed marketing effectiveness and adds practical tips for early-stage companies.

1. Andrus Purde, Outfunnel CEO & cofounder
Revenue forensics
what really works in marketing (in a multi-app world)

2. Andrus who?
CEO & co-founder of
Outfunnel
Marketer. Entrepreneur.
Stand-up comedy
enthusiast. Pipedrive and
Skype alumni. Angel
investor. Dad.

3. A sales and marketing workflow platform
that works across all your revenue tools

4. What this talk will cover
Three tips for making Revenue Forensics easier
1.
One joke
2.
3.
A couple of things we've learned at Outfunnel by combining sales and
marketing data

5. Revenue forensics
(aka measuring
sales and
marketing) is easy
(for 10,5% of companies)

6. Do we need to
measure all of
marketing?
Probably not.

7. What's better than Jim
Collins' "hedgehog
strategy"?

8. http://bit.ly/2Hedgehog

9. Revenue forensics for paid search is
(relatively) straightforward…
https://bit.ly/MKTattribution

10. Measuring SEO/content tricky due
to standard source definitions

11. Tip #1: redefine
definitions for
Organic and
Direct
https://bit.ly/LeadSourceDefs

12. Findability
forensics: blog
posts drive most
of the SEO traffic
but less than
half of leads https://bit.ly/MKTattribution

13. Lead source
forensics:
volumes and
conversion rates
vary a lot
Sidenote: here and beyond based on first-touch
attribution, usually most useful for early-stage
companies
https://bit.ly/MKTattribution
Findability
Findability
Findability
Word-of-mouth
?

14. Tip #2: auto-capture lead source (in
your CRM)

15. Do we need
machine
learning for
Revenue
Forensics?

16. Email clicks are a
strong
conversion
signal, email
opens matter too
https://bit.ly/PredLeadScore

17. Web visits
correlate well
with deals that
convert
https://bit.ly/PredLeadScore
Sidenote: the model we trained on Outfunnel data worked on roughly half the companies tested

18. Do we need
machine
learning for
Revenue
Forensics?
The answer: not
necessarily. But tip #3
is to have all marketing
data in one place (e.g.
your CRM)

19. "It is better to know
some of the questions
than all of the
answers.”
— James Thurber
andrus@outfunnel.com
@andruspurde