crafting anftp.marketingsherpa.com/heap/presentations/emailsummit11...conversion rate of sales and...
TRANSCRIPT
Five elements that contribute to the success (or failure) of every email campaign
Crafting an Effective Email Message
Dr. Flint McGlaughlinCEO & Managing DirectorMECLABS
ABOUT THE RESEARCHEmail Messaging
Email Messaging
Dr. Flint McGlaughlin – Managing Director, MECLABS Group
Flint McGlaughlin is the Managing Director of MECLABS Group. The organization has partnered with key market leaders including, The New York Times, Microsoft Corporation, and Reuters Group.
Dr. McGlaughlin also serves as the Director of Enterprise Research at the Transforming Business Institute, University of Cambridge (UK), as the Chairman of the Board of Governors for St. Stephen’s University, and as a Trustee for Westminster Theological Centre. Dr. McGlaughlin originally studied Philosophy and Theology at the University of London’s Specialist Jesuit College.
Today, his primary research is focused on enterprise as transformative agent. His work has won multiple awards and has been quoted in more than 13,000 online and offline sources.
About the Research
Email Messaging
Core Offerings >>
MECLABS Sciences Group
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Applied Research
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Primary Research
• 974 case studies• 753 how‐to articles• 180 research briefs • 50 publication series
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About the Research
Email Messaging
MarketingExperiments was the first Internet‐based research lab to conduct experiments in optimizing the conversion rate of sales and marketing processes.
1992 Preliminary Research Begins
1997 Research Program Established
2001 First Research Report Published
2002 Testing of Research Partnership Model Begins
2003 Offer Response Optimization Theory Validated
2006 Patent Filings for Research Findings (10 Heuristics)
About the Research
EXPERIMENTEmail Messaging
Email Messaging
7
Experiment ID: (protected)Location: MarketingExperiments Research LibraryTest Protocol Number: TP2061
Background: An established financial institution offering online savings accounts
Goal: To increase clickthrough from an email message to the landing page
Primary research question: Which email design will produce the most clickthrough?
Approach: A/B email split test (variable cluster)
Research Notes:
Experiment
Email Messaging
8
Note the following things about the control:
• Utilizes graphical imagery throughout email
• Provides multiple calls‐to‐action
• Follows a typical clean landing page format
• Copy is difficult to read in some places
Experiment
Email Messaging
9
Note the following things about Treatment 1:
• Not many graphical elements
• Relies on copy‐rich messaging
• Has a personal letter‐style feel
• Links are embedded within the copy
Experiment
Email Messaging
10
Note the following things about Treatment 2:
• Utilizes graphical header to catch visitors eyes
• Organizes the content in a clean, easy‐to‐scan format
• Displays security guarantee seal
• Single clear call‐to‐action
Experiment
Email Messaging
11
Note the following things about Treatment 3:
• Similar to Treatment 2
• However, does not utilize graphical header
• Organizes the content in a clean, easy‐to‐scan format
• Displays security guarantee seal
• Single clear call‐to‐action
Experiment
Email Messaging
12
Control
Treatment 1
Treatment 2
Treatment 3
Experiment
Email Messaging
13
Email CTR Rel. Diff.
C – Control email 0.51%
T1 – Copy-rich email 0.73% 42.34%
T2 – Single CTA (w/ header) 0.63% 24.12%
T3 – Single CA (w/o header) 0.65% 26.27%
42% Increase in ClickthroughTreatment 1 (copy rich) outperformed the control by 42.34%
Experiment
Email Messaging
14
What was it about this email that generated the most response?
Experiment
Email Messaging
Rule‐based Optimization
Science‐basedOptimization
vs.
• Emphasize hero shots• Keep it above the fold• Avoid too much copy• Emphasize the Benefits• Don’t use reverse text• Don’t rely too much on Flash• Implement basket recovery emails• Avoid auto‐on audio
Practice
Methodology
Meta‐theory
Rules vs. Science
Email Messaging
eme = email messaging effectiveness indexrv = relevance to the consumerof = offer value (why)i = incentive to take actionf = friction elements of processa = anxiety elements of process
eme = rv(of + i) – (f + a) ©
Email Messaging Optimization Heuristic
Methodology
Email Messaging
eme = rv(of + i) – (f + a) ©
Email Messaging Optimization Heuristic
Methodology
During today’s presentation, we will be walking through each of the five elements in the heuristic above, analyzing the key components of a successful email message.
RELEVANCEEmail Messaging
Email Messaging
Relevance – The compatibility of the email message to the recipient’s motivations
eme = rv(of + i) – (f + a)©
eme = rv(of + i) – (f + a)
Email Messagingeme = rv(of + i) – (f + a)
Simple key statements are used to generate a relevant connection to the user:
• References to previous purchase patterns – “being a XXXXX account holder”
• Personal name “Monica” is used in the greeting
• Reference to personal behavior “saving for next your vacation, home, etc.”
Email Messaging
1. The relevance of an email can be based upon 1) the internal motivations of the recipient and 2) the external events surrounding a recipient.
eme = rv(of + i) – (f + a)
Key Principle
Email Messagingeme = rv(of + i) – (f + a)
Internal Relevance• Personal interests • Demographics• Shopping habits• Personality• Communication styles• Level of engagement
External Relevance• Seasonality• Special discounts• Limited‐time offers• News events• Competitive initiatives
Email Messaging
Now let’s look at an example of how we tied relevance into a holiday email campaign for one of our research partners …
eme = rv(of + i) – (f + a)
Email Messaging
Current Subscriber
Never Gifted
Current Subscriber
Has Gifted
Lapsed Subscriber
Never Gifted
LapsedSubscriber
Has Gifted
Never a Subscriber
Has Gifted
• This company segmented the current email list into five distinct groups (as seen above) for a holiday email campaign.
• They sent targeted email messages relevant to each group.
eme = rv(of + i) – (f + a)
Email Messaging
External Relevance: Uses the holiday season to motivate recipients – “It’s already too late to send through snail mail…”
Internal Relevance: Messaging ties into previous actions of the recipient – “You’ve recently given one of your friends…” as well as appealing to personality – “You know how great it is to be a subscriber…”
eme = rv(of + i) – (f + a)
Email Messaging
External Relevance: As before, this email uses the holiday season to motivate recipients.
Internal Relevance: Messaging speaks more to the subscriber who hasn’t sent a gift to anyone before – “Did you know you can give a… a subscription to….”
eme = rv(of + i) – (f + a)
OFFEREmail Messaging
Email Messaging
Offer – The value you promise in your email in exchange for a click
Value is the primary reason an ideal prospect would respond to you.
eme = rv(of + i) – (f + a)©
eme = rv(of + i) – (f + a)
Email Messagingeme = rv(of + i) – (f + a)
• Much of value proposition of this offer is the same in this test, with the exception of one critical element – the call‐to‐action.
ControlTreatment
Email Messagingeme = rv(of + i) – (f + a)
Learn more and open an account
Control CTA
Treatment CTA
Click here to earn more today!
Original: The call‐to‐action in the control is focused on what the prospect has to do (“learn & open”) rather than what they might get. This just creates anticipated Friction and Anxiety rather than Value.
Optimized: The new call‐to‐action focuses on what the email client gets (“earn more money”) if they are willing to click to the next step.
Email Messaging
1. Your communication of value begins in your subject lines and should be maintained throughout the entire conversion process.
eme = rv(of + i) – (f + a)
Key Principles
Email Messaging
Experiment from
eme = rv(of + i) – (f + a)
Experiment ID: (Protected)Location: MarketingSherpa Research LibraryTest Protocol Number: CS771
Background: This company offers prepackaged organic meals delivered to your home. They believed that the order minimum was hurting repeat sales. They began a promotion that reduced the minimum order. An email was developed to inform previous customers of this new order option.
Goal: To get recipients to open the email
Primary research question: Which subject line will receive the higher open rate?
Approach: A/B single‐factorial split test
Research Notes:
Email Messaging
Subject Line #1[Company Name]: A New Way To Order
• This email is being sent to previous customers.
• This subject line emphasizes a “New Way To Order,” but says nothing about why or how it is better.
eme = rv(of + i) – (f + a)
Experiment from
Email Messaging
Subject Line #2[Company Name]: Now only 2‐meal minimum order
• This subject line explains the benefit of the new order option.
eme = rv(of + i) – (f + a)
Experiment from
Email Messaging
25.3% Increase in Open RateResulting in greater subscriptions and revenue
eme = rv(of + i) – (f + a)
Email Subject line Open Rate (%)
Control – A New Way to Order 35.2
Treatment 1 – 2‐meal minimum order 44.1%
Relative Difference 25.3%
Experiment from
Email Messagingeme = rv(of + i) – (f + a)
1. Your communication of value begins in your subject lines and should be maintained throughout the entire conversion process.
2. In the body of the email, it is important to distinguish the difference between the product offer and the clickthrough offer. In many cases we conflate the two. To avoid this danger one must ask two questions:
• Q1: What is your objective?
• Q2: What is the best way to achieve your objective?
Key Principles
Email Messaging
What REALLY is the offer?
• You may think that the offer is the product that you want to sell, when in reality it is the additional information they receive in exchange for a click.
• What is the objective of your email? Is it to sell product or to get a click?
• If the goal is to get a click, then why are you trying to sell your product twice (email and landing page)? If we conflate our purpose, then we mitigate conversion.
eme = rv(of + i) – (f + a)
Email Messaging
38
Experiment ID: (protected)Location: MarketingExperiments Research LibraryTest Protocol Number: TP2063
Background: A financial organization offering a quarterly newsletter for business leaders. These emails often feature a single whitepaper download.
Goal: To generate more whitepaper downloads.
Primary research question: Which email design will produce the most downloads?
Approach: A/B email split test (variable cluster)
Research Notes:
eme = rv(of + i) – (f + a)
Email Messaging
39
eme = rv(of + i) – (f + a)
• The original version of the email provided an overview of the whitepaper download similar to what might be best practices for a landing page offer (strong headline, intro paragraph, bullet point, single CTA, etc.).
LOGO
Email Messaging
40
• In a radical testing strategy, our researchers wanted to test peaking the recipients interest by showing part of the article (title and first three paragraphs) that they could download.
• The hypothesis was that this would increase the value of “the click”.
eme = rv(of + i) – (f + a)
LOGO
Email Messaging
41
Test Designs Email CTR Relative Difference Download Rate Relative
Difference
Control 8.4% ‐ 18.2% ‐
Treatment 1 10.8% 28.6% 33.6% 84.6%
85% Increase in DownloadsTreatment 1 increased the rate of clickthrough rate by 29%
eme = rv(of + i) – (f + a)
What you need to understand: By focusing on piquing interest just enough to get a click in the email, not only did we generate more response from email recipients, but we also generated more white paper downloads on the landing page.
eme = rv(of + i) – (f + a)
INCENTIVEEmail Messaging
Email Messaging
Incentive – An appealing element introduced in your email to achieve a desired action.
eme = rv(of + i) – (f + a)©
eme = rv(of + i) – (f + a)
Email Messagingeme = rv(of + i) – (f + a)
Background: A student from our certification course in landing page optimization tested two different incentive options on a B2B email landing page seeking to promote the download of a specific white paper.
Goal: To improve landing page conversion rate while generating opt‐ins for ongoing communications
Primary research question: Which incentive will generate the most conversions?
Approach: A/B single‐factorial split test
Experiment ID: (Protected)Location: MarketingExperiments Research Library
Research Notes:
Email Messagingeme = rv(of + i) – (f + a)
“… a chance to win one of twenty $25 Amazon gift cards...”
“… a chance to win one of ten $50 Amazon gift cards...”
Incentive #1 Incentive #2
The cost of these offers was the same, but which do you think performed best?
Email Messaging
Subscription path CR Relative diff v. control
Incentive #1 43.0% ‐
Incentive #2 56.5% 31.4%
31% Increase in conversion rateThe second incentive outperformed the other by 31.4%
eme = rv(of + i) – (f + a)
Email Messaging
Ideal Incentive: Incentives must be tested. There is an “ideal incentive.”
Until you find an incentive that gives you a major ROI increase, you must assume you have not yet found the ideal incentive.
So how do you determine the ideal incentive?
eme = rv(of + i) – (f + a)
Friction Elements Incentives
ABANDON COMPLETION
Email Messaging
Background: An online people search company that was losing many orders due to cart abandonment. We wanted to find a way to recover as many of these orders as possible with a minimum incremental marketing spend.
Goal: To recover partially completed but abandoned orders through a sequence of basket recovery emails.
Primary research question: Which basket recovery sequence and offer will generate the most sales?
Approach: A/B split test (variable cluster)
Research Notes:
Experiment ID: (Protected)Location: MarketingExperiments Research Library
eme = rv(of + i) – (f + a)
Email Messaging
The table below shows the performance of the initial test, using a sequence of two email messages.
Note: With no additional marketing spend, the initial set of basket recovery email messages yielded 25 additional sales and $725 in additional revenue.
Email Description Emails Sent
CTP Clicks CTR Sales CR Price Net
Rev
Email Send – 1‐hr message ND 8,834 252 2.85% 24 9.52% $29.00 $696.00
Email Send – 24‐hr message ND 8,610 100 1.16% 1 1.00% $29.00 $29.00
EMAIL TOTALS 17,444 352 2.02% 25 7.10% $725.00
eme = rv(of + i) – (f + a)
Email Messaging
• We then added a third email to the sequence that offered a discount on the cost of the service as an incentive.
• The original price was $29.95, the discounted prices is $19.95 (33% off).
eme = rv(of + i) – (f + a)
Email Messaging
3 Message Series with Discount Incentive:
149% Increase in ConversionThe third email increased conversion rates by 149%
What you need to understand: Adding the discount incentive email boosted conversion rate for the series by over 149% (17.7% vs. 7.1%) and generated a more than 273% higher level of net revenue ($1,982 vs. $725). Conversion from click through to sale for the third email was over 43%.
Email Description Emails Sent
CTP Clicks CTR Sales CR Price Net Rev
Email Send – 1‐hr message ND 8,834 252 2.85% 24 9.52% $29.00 $696.00
Email Send – 24‐hr message ND 8,610 100 1.16% 1 1.00% $29.00 $29.00
Email Send – 5th day message ND 8,419 145 1.72% 63 43.45% $19.95 $1,256.85
EMAIL TOTALS 25,863 497 1.92% 88 17.71% $1,981.85
eme = rv(of + i) – (f + a)
Email Messaging
52
eme = rv(of + i) – (f + a) ©
Email Messaging Optimization Heuristic
Based on what we have covered so far, let’s begin to apply these principles to real‐life email campaigns submitted by our audience.
Live Optimization
eme = rv(of + i) – (f + a)
LIVE OPTIMIZATION #1Email Messaging
eme = rv(of + i) – (f + a) ©
Subject Line: The Best Coupons This Week ‐ 1/17/11 (with today's Deal of the Day!)
eme = rv(of + i) – (f + a) ©
Subject Line: Email‐Only 20 Farm Cash INSIDE!
Subject Line: You're just one step away
eme = rv(of + i) – (f + a) ©
Email Messaging
57
eme = rv(of + i) – (f + a) ©
Email Messaging Optimization Heuristic
We will now move on to covering the last two elements of the Email Messaging Optimization heuristic: Friction and Anxiety.
eme = rv(of + i) – (f + a)
eme = rv(of + i) – (f + a)
FRICTIONEmail Messaging
Email Messaging
Friction ― Psychological resistance to a given element in the email
eme = rv(of + i) – (f + a)
eme = rv(of + i) – (f + a)©
Email Messagingeme = rv(of + i) – (f + a)
In the original email, Friction is potentially caused by three factors:
1. Multiple visual elements competing for the recipient’s attention.
2. The eye‐path in this email is not being directed in the proper order.
3. Multiple unique calls‐to‐action from which the recipient must choose between
Email Messagingeme = rv(of + i) – (f + a)
Treatment changes:
• The competing visual elements have been removed
• The flow of the page is linear and emphasis is in proper order
• There is one main call to action (though in two hyperlinks) in this email message, minimizing the difficulty in the decision process
Email Messaging
1. Two common elements that create Friction in body copy are:
• Length
• Difficulty
eme = rv(of + i) – (f + a)
Key Principle
Email Messagingeme = rv(of + i) – (f + a)
Not this But this
Example: Length
Email Messagingeme = rv(of + i) – (f + a)
Not this But this
Example: Difficulty
Email Messaging
1. Two common elements that create Friction in body copy are:
• Length
• Difficulty
2. Friction is also generated by email messages that do not match proper thought sequence. Therefore, body copy must be specifically crafted to synchronize to the decision patterns of the recipient.
eme = rv(of + i) – (f + a)
Key Principle
Email Messaging
Re: The Research Results You Requested
Dear MarketingExperiments Subscriber,
As the Director of MECLABS Group, I felt it was important to personally inform you regarding one of the most significant breakthroughs in the history of our paid search experimentation.
In this study, we were able to reduce cost by 35% and yet increase conversion by 300%. You can find out more by clicking here.
Perhaps this breakthrough will help you improve your paid search ROI.
Dr. Flint McGlaughlinDirectorMECLABS Group
P.S. This link will only be active for 24 hours; we are trying to get this information to our subscribers before it reaches the media.
CAPTURE
First paragraphSubsequent paragraphs
Call‐to‐actionSignaturePostscript
Subject line/headlineSalutationOpening sentence
CONVINCE
CLOSE
eme = rv(of + i) – (f + a)
ANXIETYEmail Messaging
Email Messaging
Anxiety― Psychological concern stimulated by a given element in the email process
eme = rv(of + i) – (f + a) ©
eme = rv(of + i) – (f + a)
Email Messagingeme = rv(of + i) – (f + a)
The Original:• The tone and presentation
of this email does not seem personal, but rather appears and sounds like sales jargon.
• This does not reduce any of the inherit Anxiety already associated with the receiving of an email message.
Email Messagingeme = rv(of + i) – (f + a)
The Optimized:• This version uses a
letter style layout and personal copy tone in order to communicate on a more one‐to‐one level.
• This email is more like a personal letter than a hype‐filled sales offer.
Email Messaging
1. While website visitors are skeptical and cautious, the natural level of concern is even greater for email offer recipients.
eme = rv(of + i) – (f + a)
Key Principle
Email Messagingeme = rv(of + i) – (f + a)
Why is concern greater for emails?
• Are you more likely to be skeptical about a company you called for information or one who called you at home with the same offer?
• The very nature of email, as an outbound or “push” marketing channel, causes it to need to overcome the extra measure of distrust and skepticism.
• We need an extraordinary amount of over‐correction to overcome this extra measure of anxiety and distrust.
Email Messagingeme = rv(of + i) – (f + a)
Experiment ID: (Protected)Location: MarketingExperiments Research LibraryTest Protocol Number: TP2002
Background: MarketingExperiments sent out two emails promoting their Landing Page Optimization course. One used the familiar academic tone in the subject line and body copy, while in the other we tested a more informal and sales‐like tone.
Goal: To establish whether the familiar academic tone or a less formal one would result in more course registrations.
Secondary research question: Will the familiar academic tone or a more informal sales‐oriented tone result in more registrations? (pretty repetitive)
Approach: A/B split test (variable cluster)
Research Notes:
Email Messaging
Familiar academic approach
Subject line: MarketingExperiments—An increase of 541%‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
Take the MarketingExperiments Landing Page Optimization Certification Course
Dear MarketingExperiments Subscriber,
Our Landing Page Optimization Certification Course for subscription sites begins on April 26, 2007.
Passing this test will impact your business and personal career in two important ways:
1. The study and application of all that you learn, including our unique Conversion Index, will help you increase revenues for your business almost immediately.
2. When you pass the course, you will receive a Certification Certificate which you can add to your résumé and use to advance your career.
eme = rv(of + i) – (f + a)
Email Messaging
Subject line: MarketingExperiments—A Porsche or a Corolla?‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
Take the MarketingExperiments Landing Page Optimization Certification Course . . . and change gear for ever.
Dear MarketingExperiments Subscriber,
Ask yourself a question.
Think of one of your company’s key Web site landing pages and ask yourself whether it’s more like a Porsche 911 or a Toyota Corolla.
Is it a high‐performance page, fully optimized to maximize conversion rates?
Or is it a Corolla . . . to which you have been adding cup holders and new upholstery in the hope that these little tweaks will enhance its performance?
Sales‐tone approach
eme = rv(of + i) – (f + a)
Email Messaging
29% Increase in CTRResulting in twice the number of subscribers
eme = rv(of + i) – (f + a)
Email Messages CTR (%)
Email 1 – Academic 1.75%
Email 2 – Sales 1.35%
Relative Difference 29.3%
Email Messagingeme = rv(of + i) – (f + a)
Do our emails look like this?
Email Messaging
The Prospect’s Protest (A Problem)
I. I am not a target; I am a person: Don’t market tome, communicate withme.
II. Don’t wear out my name, and don’t call me “friend,” until we know each other.
III. When you say “sell,” I hear “hype.” Clarity trumps persuasion. Don’t sell; say.
IV. I don’t buy from companies; I buy from people. And here’s a clue:
V. I dislike companies for the same reason I dislike people.
VI. Stop bragging. It’s disgusting.
eme = rv(of + i) – (f + a)
Email Messaging
The Prospect’s Protest (A Problem)
VII. And why is your marketing “voice” different from your real “voice”? The people I trust don’t patronize me.
VIII. In all cases, where the quality of the information is debatable, I will always resort to the quality of the source. My trust is not for sale. You need to earn it.
IX. Dazzle me gradually: tell me what you can’t do, and I might believe you when you tell me what you can do.
X. In case you still don’t “get it,” I don’t trust you. Your copy is arrogant, your motives seem selfish, and your claims sound inflated. If you want to change how I buy, first change how you market.
eme = rv(of + i) – (f + a)
Email Messaging
The MarketingExperiments Creed (A Response)
We believe that people buy from people, that people don’t buy from companies, from stores, or from web sites; people buy from people. Marketing is not about programs; it is about relationships.
We believe that brand is just reputation; marketing is just conversation, and buying is an act of trust. Trust is earned with two elements: 1) integrity and 2) effectiveness. Both demand that you put the interest of the customer first.
We believe that testing trumps speculation and that clarity trumps persuasion. Marketers need to base their decisions on honest data, and customers need to base their decisions on honest claims.
eme = rv(of + i) – (f + a)
ARTICLE ONE
ARTICLE TWO
ARTICLE THREE
Email Messaging
81
eme = rv(of + i) – (f + a) ©
Email Messaging Optimization Heuristic
Now let’s apply all the principles we have learned today to the following real‐life email campaigns submitted by the audience.
eme = rv(of + i) – (f + a)
eme = rv(of + i) – (f + a) ©
Subject Line: Do More With Less!
eme = rv(of + i) – (f + a) ©
Subject Line: Make Your Escape
eme = rv(of + i) – (f + a) ©
Subject Line: Aldrich eChemFiles, a New Product Showcase
ADDITIONAL RESOURCESEmail Messaging
Email MessagingAdditional Resources
1. RESOURCE #1 – Complete Online Email Certification Course Eight hours of research‐driven training on how to create effective email campaigns from building a list to converting email‐related landing pages.
2. RESOURCE #2 – Free Email Optimization Web Clinic On February 9th, MarketingExperiments will be hosting a one‐hour web clinic focused on optimizing audience‐submitted email campaigns.
3. RESOURCE #3 – MarketingExperiments Research JournalFree copies (limited amount) of the Q3 Research Journal that features the most recent discoveries from our online marketing research.
For more information, please visit the MECLABS booth
ENDEmail Messaging
APPENDIX – FREQUENCY TESTEmail Messaging
Email Messaging
Background: Large ecommerce company with strong online presence.
Goal: To find the optimal send frequency for a segment of their email list.
Primary research question: Which email frequency will generate the most revenue without increasing the rate of unsubscription?
Approach: A/B email frequency test ran over a period of 60 days.
Experiment ID: (Protected)Location: MarketingExperiments Research Library
Research Notes:
eme = rv(of + i) – (f + a)
Email Messaging
This group was currently sending emails with a frequency ranging from once a week to multiple times a day. But what was the the optimal frequency?
Optimal Frequency
Email Sends
Total Revenue
Unsubscribes
eme = rv(of + i) – (f + a)
Email Messaging
Three weeksTwo weeks10 daysWeek5 Days3 Days2 Days
• Took a segment of their large subscriber base (more than one billion emails a year)
• Segmented that group into seven different email frequencies mentioned above hoping to find the frequency “sweet‐spot”
Full ListTest list Frequency
eme = rv(of + i) – (f + a)
Email Messaging
What do you think will be the optimal monthly frequency for this company?
1. 1‐2 per month
2. 3‐4 per month
3. 6‐9 per month
4. 10‐15 per month
eme = rv(of + i) – (f + a)
Email Messaging
• Projected monthly revenue rose consistently with increasing send frequency and the amount of sends did not have a significant impact on the overall rate of transaction.
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
100,000
2 4 6 8 10 12 14
Estim
ated
Reven
ue ($
/mo)
Send Frequency (sends/mo)
Estimated Monthly Revenue vs. Email Send Frequency
eme = rv(of + i) – (f + a)
Email Messaging
• Though projected unsubscribes rise with more sends…
0
500
1,000
1,500
2,000
2,500
3,000
3,500
2 4 6 8 10 12 14
Ave No. Unsub
s. per M
onth
Send Frequency (sends/mo)
Average No. Unsubs Per Month at Each Send Frequency
eme = rv(of + i) – (f + a)
Email Messaging
• …the unsubscribe rate on a per‐message basis does not rise significantly.
• This does not suggest a greater level of irritation, but rather simply more unsubscribe opportunities offered at higher frequencies.
eme = rv(of + i) – (f + a)
Email Messaging
• Open‐rate also does not appear to be significantly influenced by send frequency within the range of frequencies tested.
• There is no significant correlation evident between send frequency and open rate.
eme = rv(of + i) – (f + a)
Email Messaging
3x Increase in Projected Monthly RevenueIncreasing email frequency yields three times the projected revenue
What you need to understand: When sending email at the rate of once a week this company is missing three times the amount of revenue it could be making if sending once every other day without negatively affecting unsubscribes or opens.
020,00040,00060,00080,000100,000
2 4 6 8 10 12 14
Estim
ated
Reven
ue ($
/mo)
Send Frequency (sends/mo)
Estimated Monthly Revenue vs. Email Send Frequency
eme = rv(of + i) – (f + a)
Email Messaging
• Optimal email frequency is strongly related to the relationship you have with your lists and their motivations.
• There is not a “one‐size‐fits‐all” for email frequency. You need to test.
• Keep in mind that there might be different optimal frequencies for different segments of your own house lists.
What does this all mean?
eme = rv(of + i) – (f + a)