What is a good open rate? How does my click through rate stack up against industry benchmarks? These are two of the most frequently asked questions by email marketers. While the sentiment is good, the reality is that these are the wrong questions. In this webinar, Skip Fidura, Global Client Services Director at dotmailer, demonstrates how this approach can lead to poor decision making and result in marketers undervaluing both their email lists and the performance of their email programs. He discusses when and where you should focus on metrics and then wraps up by answering the question, if not metrics, then what?

1. Measuring the Success of
your Email Campaigns
@SkipFidura
@litmusapp
@dotmailer
#EmailAnalytics

2. Slide 2@SkipFidura @litmusapp #EmailAnalytics
Topics
• Why do we use rates?
• How rates can lead to bad decisions.
• When and where you should use rates.
• If not rates, then what?

3. Slide 3@SkipFidura @litmusapp #EmailAnalytics
Why do we use rates?
• Percentages are a simple way of showing size or
scale or value
• In marketing, they are primarily used to:
– Express the ratio of people who took an action as a result of
the marketing message (e.g. Open Rate, Click Through Rate,
Conversion Rate, etc.)
– Compare results between campaigns which went to different
sized populations

4. Slide 4@SkipFidura @litmusapp #EmailAnalytics
Using Rates for Comparison
Birthday Email
Emails
Delivered
500
Open Rate 25%
Unique Opens 125
Promotional Email
Emails
Delivered
3,000,000
Open Rate 20%
Unique Opens 600,000

5. See how we used rate comparisons to
identify email trends.
GET THE DETAILS
Slide 5@SkipFidura @litmusapp #EmailAnalytics

6. Slide 6@SkipFidura @litmusapp #EmailAnalytics
Why do we use rates?
• Percentages are a simple way of showing size or
scale or value
• In marketing they are primarily used to:
– Express the ratio of people who took an action as a result of
the marketing message (e.g. Open Rate, Click Through Rate,
Conversion Rate, etc.)
– Compare results between campaigns which went to different
sized populations
• Percentages are also a great way to give credence to
small numbers

7. Slide 7@SkipFidura @litmusapp #EmailAnalytics
How Rates Can Lead to Bad Decisions
• Rates are easy to manipulate
• Email Success Metrics are not directly aligned with
your business drivers
• Rates can give too much credence to small numbers

8. Slide 8@SkipFidura @litmusapp #EmailAnalytics
How Rates Can Lead to Bad Decisions
• Rates are easy to
manipulate
• Email Success Metrics are
not directly aligned with
your business drivers
• Rates can give too much
credence to small numbers

9. Slide 9@SkipFidura @litmusapp #EmailAnalytics
Rates Alone Can Steer Us in the Wrong Direction
Camp 1
Open Rate 25%
Camp 2
Open Rate 25%
Camp 3
Open Rate 25%
Camp 4
Open Rate 25%
Open Rate 55%

10. Slide 10@SkipFidura @litmusapp #EmailAnalytics
Opens or Clicks?
Campaign A
Check out our new British Film of the
Month
Emails Delivered 10,000
Unique Opens 2,000
Open Rate 20%
Unique Clicks 200
Click Through Rate 2%
Click to Open Rate 10%
Campaign B
Check out Benedict Cumberbatch's
brand new film!
Emails Delivered 10,000
Unique Opens 1,500
Open Rate 15%
Unique Clicks 300
Click Through Rate 3%
Click to Open Rate 20%

11. There is more to your email
analytics than open rates.
TAKE A PEAK
Dive deeper. Learn about your
email list's level of engagement,
device usage, and geo-location.
Slide 11@SkipFidura @litmusapp #EmailAnalytics

12. Slide 12@SkipFidura @litmusapp #EmailAnalytics
When and Where You Should Use Rates
• Setting and using your
benchmark
• Looking at campaign
trends over time
• Comparative learning

13. Slide 13@SkipFidura @litmusapp #EmailAnalytics
If Not Rates, Then What?
• Identify the email metric that most
closely correlates with your key
business driver.
Case Study – Ecommerce Client
• Analysed the customer journey for
all purchases
• Recipients who have clicked on
two emails have the highest
conversion rates (63% Higher)
• Single clickers = most important

14. Slide 14@SkipFidura @litmusapp #EmailAnalytics
Recency Frequency Analysis
Days Since Last Click
180+ 90-179 60-89 30-59 0-29
NumberofClicks
0
1
2
3
4
5

15. Slide 15@SkipFidura @litmusapp #EmailAnalytics
Conclusions
• Rates are very effective at comparing results of
different sized campaigns
• Be careful that:
o Your rates are not being manipulated
o You are not overweighting small numbers
o You apply your rates to consistent populations
• Better ways to measure campaign effectiveness
are to
o Tie it to sales or another revenue metric
o Use Recency Frequency Analysis to track engagement over time

16. Gather the analytics you
need.
Unlimited email tests, page tests,
spam filter tests and Email Analytics
tracking codes.
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