Average email reply rates can vary greatly, but some suggest they can hover around 1-5%. When Paddle, UK’s fastest growing software company, went to market with an outbound email strategy, they blew those numbers out of the water, consistently achieving reply rates of 30% or higher. In this webinar, we’ll dive into how the Paddle team executed their outbound strategy to catapult their success. Topics covered include: - Paddle’s phased approach - What data they required and how they sourced it - The tools and technologies used - Best practices learned along the way We encourage anyone with responsibility for B2B marketing, sales, revenue ops, growth, and customer data management to watch the reply of this engaging 1-hour webinar. Replay: https://www.hull.io/blog/webinar-recap-paddle-30-percent-reply-rate-cold-emails/

1. How to Achieve a
30% Reply Rate
on Cold Emails
Thank you for joining! The live broadcast will begin shortly after 2:00 PM to accommodate last minute attendees.
PRESENTED BY

2. Before we begin
● Got questions? Use the Questions
module!
○ We’ll address questions throughout the
presentation
○ If we have time at the end, we’ll run
through a few more
● Webinar replay will be sent to all
registrants within 48 hours

3. Speakers
Tim Liu
Head of Product
Harrison Rose
Co-founder
Aleksander Bury
Founder at GoodFit
and former Head of
Commercial Ops at Paddle
Brooke Bachesta
Senior Manager of Sales
Development

4. Paddle’s phased approach
Setup &
Gather Data
1
Activate
2
Analyze &
Iterate
3

5. Paddle’s approach: Phase 1
SETUP & GATHER DATA
Map the total addressable market, refine audience
Enrich accounts and prospects with data
Load and transform data in Hull
Build real-time segments in HullSetup &
Gather Data
1
STEPS IN PHASE 1:

6. Map the TAM, then refine your audience
● Any outbound strategy begins with knowing who
you’re going to target, knowing your
Total Addressable Market
● TAM = Prospects that have an actual need for your
product
● Relying on industry & revenues when identifying
TAM is not enough
● You also need to refine your audience and source
data points that fit your ICP
SETUP & GATHER DATA

7. Enrich accounts and prospects with data
Reason #1: Prioritization
Identifying accounts that are most likely to
buy your product and ordering them
accordingly
Reason #2: Hyper-Relevance
Sending messaging to prospects that identifies
the pains or needs they have
SETUP & GATHER DATA

8. Unify, then transform data in Hull
● Hull ingests data from all sources through
native integrations or webhooks
● Data transformation step turns raw data into
usable information
● Data transformation examples:
○ Generate an “average employee headcount”
number
○ Parsing technographic data to extract technology
you care about
What is the Hull Processor?
A real-time editing environment for
your customer data, the Hull
Processor lets you compute new
attributes from existing data and
update customer records on the fly.
The Hull Processor supports use
cases like:
● Data cleansing and
reformatting
● Data enrichment
● Custom mapping
● Custom scoring for contacts
and accounts
?
SETUP & GATHER DATA

9. Diving deeper: Segmentation in Hull
Build segments based on:
● Account and people attributes
○ Industry, employee count,
technographics, business model,
years since founding, job title,
status, etc.
● Behaviors and interactions
○ URL visited, # of website visits,
email opened, email clicked, app
logins, etc.
Segments are generated in real-time, with data pulled from any tool connected to Hull.
SETUP & GATHER DATA

10. Build real-time “micro segments” in Hull
● Two key requirements:
○ Segments had to be so specific to elicit
the response rates they were aiming for
○ Segments had to be dynamic (generated
in real-time) to accommodate for
changes in the data
● Needed to avoid “data
deterioration”
○ Email messaging based on stale data
could lead to unsubscribes and potential
lost business
SETUP & GATHER DATA

11. Phase 1 recap & questions
Setup &
Gather Data
1
SETUP & GATHER DATA
Map the total addressable market, refine audience
Enrich accounts and prospects with data
Load and transform data in Hull
Build real-time segments in Hull
STEPS IN PHASE 1:

12. Paddle’s approach: Phase 2
Write emails
Build sequences
Send!
Activate
2
ACTIVATE
STEPS IN PHASE 2:

13. Running Account Based Prospecting with Outreach
● Tandem prospecting
● Types of sequences
○ Automated
○ Manual
○ Call Heavy
○ Personalized
ACTIVATE

14. Sequence Type - Automated
● Completely automated. Leverages emails.
No calls or generic tasks
● Used sparingly when casting a wide net or
for intel. gathering
○ Automated Referral Request
○ Intel gathering
ACTIVATE

15. Sequence Type - Call Heavy
● Extra calls (50%+ of sequence is call)
● In some cases, we have “call only,” and the
ruleset allows for “double sequencing”
● Great for target accounts
ACTIVATE

16. Sequence Type - Manual
● Template + variables that require research
● Great for persona specific, industry generic
● Fantastic way to ramp up new reps into
“personalization”
ACTIVATE
+

17. Sequence Type - Personalized
● Blank email or sparse template with bare
bones value prop as first message
● “Varsity” level
● Leverage things like:
○ Self authored content
○ Linkedin profile self descriptions
○ Relationships/Insights
ACTIVATE

18. ACTIVATE

19. Diving deeper: Creating email variable tags using Hull
data transformation
{{Uplift On Increased Conversions}} generated by parsing
revenue into degree of impact. I.e. if less than $1M then ‘tens
of thousands’.
{{Percent Traffic Outside North America}}
calculated by obtaining global web traffic
counts as well as web traffic counts in the
USA and Canada.
{{Top Currencies}} generated
by identifying top 3 countries
driving web traffic to that
domain - Currencies that are
already supported.
ACTIVATE

20. Phase 2 recap & questions
Write emails
Build sequences
Send!
Activate
2
ACTIVATE
STEPS IN PHASE 2:

21. Paddle’s approach: Phase 3
Measure initial results in Outreach
Next-level reporting with Hull and data warehouse
Analyze &
Iterate
3
ANALYZE & ITERATE
STEPS IN PHASE 3:

22. Brass tacks: Are we doing the right activities?
ANALYZE & ITERATE

23. Digging In: Are the right sequences being used?
ANALYZE & ITERATE

24. Next-level reporting with a data warehouse
Performance Analysis
● Response rate is a great leading indicator
● Analyzing your opportunity creation and
win rates
Iteration
● Redefining your segments and identifying
new sub-segments
● Understanding your customer journey
ANALYZE & ITERATE

25. Phase 3 recap & questions
Measure initial results in Outreach
Next-level reporting with Hull and data warehouse
Analyze &
Iterate
3
ANALYZE & ITERATE

26. Recap: Paddle’s phased approach
Setup &
Gather Data
1
Activate
2
Analyze &
Iterate
3

27. Final questions?
PRESENTED BY

28. Thank you!
Tim Liu
Head of Product
Harrison Rose
Co-founder
Aleksander Bury
Founder at GoodFit
and former Head of
Commercial Ops at Paddle
Brooke Bachesta
Senior Manager of Sales
Development
hull.io paddle.com goodfit.io outreach.io