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Email marketing statistics and trends

Email marketing statistics and trends

Many marketers have emphasised webinars, social media, video marketing, or anything shiny they come across, knowing that trusted revenue streams like email marketing will deliver and they no longer need their focus. But anything new and exciting shouldn’t distract you completely from the fundamental and effective methods of marketing.

Email generates $42 for every $1 spent which is an astounding 4,2000% ROI. So it may be old, but it’s not old hat. Plus, more than three-quarters of marketers report the effectiveness of their emails is improving, or at least holding steady.

So, what is the email marketing landscape of this year, and how can you best use it to your advantage?

Email Marketing Statistics

Email marketing statistics and trends


B2B Email Marketing Statistics

B2C Email Marketing Statistics

Email marketing statistics and trends



Email Marketing Demographics

  • 99% of email users check their inbox every day, with some checking 20 times a day. Of those people, 58% of consumers check their email first thing in the morning
  • 40% of consumers say they have at least 50 unread emails in their inbox.
  • Emails sent by independent artists, writers, and performers have the highest open rate at 34.4%, followed by education (34.1%) and travel and tourism (32.6%).
  • On average, the highest email click-through rate goes to the Consulting services industry at 25%, with Administrative and Business Support services in second at 20%, and Home and Building services in third at nearly 19%.
  • 26% of retail emails bounce, putting it well above the 9% average bounce rate for all industries
  • 20% of retail, e-commerce, and consumer goods and services companies are personalizing emails based on gender, race, and ethnicity, versus 11% in 2019.
  • 59% of Millennials primarily use their smartphone to check email, while 67% of Generation Z scan their inbox on mobile
  • 74% of Baby Boomers think email is the most personal channel to receive communications from brands, followed by 72% of Gen X, 64% of Millennials, and 60% of Gen Z
  • 91% of women in the US use email, compared to 89% of men
  • Asian Americans are the most popular email users in the US (92%), followed by white users (91%), African American users (88%), Hispanic users (85%), and American Indian or Alaskan Native users (83%).

Automation Statistics

Segmentation and Personalisation Statistics

  • Marketers who use segmented campaigns note as much as a 760% increase in revenue
  • 20% of retail, ecommerce, and consumer goods and services companies are personalising emails based on gender, race, and ethnicity.
  • Segmented email campaigns show 50% higher CTR than untargeted campaigns.
  • The top 3 reasons for using personalisation in email marketing are improved open rate (82%), higher CTR (75%), and better customer satisfaction (58%).
  • The top 3 email marketing tactics are: list segmentation (51%), personalisation (50%), and triggered emails (45%).
  • During a SuperOffice email marketing experiment, a segmented email campaign earned a 94% open rate and a 38% CTR, versus a 42% open rate and 4.5% CTR in a non-segmented email campaign.
  • Hyper-personalisation out-performs every form of ecommerce marketing combined 20-fold, Deloitte.


Email marketing statistics and trends


Marketers who send segmented campaigns notice a 760% increase in revenue.

  • 88% of users agree they are more likely to respond to an email favourably if it looks like it’s been specifically created for them.
  • 62% of emails are opened thanks to a personalised subject line.
  • By addressing the recipient by their name, you can increase open rates and CTR up to 35%.
  • 10% of respondents are annoyed by too little or no personalization.
  • According to the respondents, the most frustrating things about personalisation are: recommending items that don’t match their interests (34%), expired offers (24%), name misspelling (15%), inappropriate season or location offers (14%), already purchased promotions (13%).
  • Emails with personalized subject lines can increase open rates by 26%.
  • Segmented email campaigns caused a 760% increase in revenue.
  • Segmented campaigns had 100.95% clicks compared to non-segmented emails globally
  • Through proper targeting, marketers can drive three times the revenue per email of broadcast emails
  • 74% of marketers said that customer engagement increases through targeted personalisation

Click-Through & Open Rates Statistics

  • The average open rate for email newsletters across all industries is 21.33%
  • Friday is the best day to send emails, with the highest open (18.9%) and click-through rates (2.7%)
  • Emails related to the Government and Non-profit sectors receive the highest open rates
  • Plain-text emails perform better, even though most respondents preferred image-based HTML emails.
  • 63% of people said that they open an email to find discounts
  • Welcome emails have the highest open rates (91.43%) with an average CTR of 26.9%, outperforming other email marketing types.
  • The average click-to-open rate for all industries is 14.1%.


Mobile Email Marketing Statistics


It is important to see what happens in reality, retailers, and marketers get duped into believing segmentation is personalisation. Because lumping a load of people in a category together does not work, considering you are in a room of 12 people, you could make significant distinctions between you and them, to the point where anyone telling you that you are all the same, would be furious. It’s the same with your marketing, don’t forget that as recipients open your emails. Segmentation is not personal it is just a smaller and smaller group of diverse tastes and interests. This is the equivalent of sending an email to everyone who bought a red item, or an XL size, it is painful when you measure the effect. Segmenting is marketing marginalisation.

The solution is hyper-personalisation software. Which uses data captured from each consumer as they visit your site, including what they look at, return to most often, etc. It then aligns this with both that individual’s buying history and their perpetual purchases, to rank every SKU on your site by the greatest likelihood of imminent purchase. Instead of waiting to convince that person to buy a specific product, (this season’s stock for example) it uses a predictive analytics algorithm to work out what has been achieved already, and simply capitalise on it.

Thanks to predictive models in email marketing, marketers can now sift through copious amounts of customer data to make key customer engagement decisions. Such data-heavy approaches have given marketers today the opportunity to pinpoint customers’ needs at ‘quantum-esc’ levels, making the future of email marketing brighter than ever!

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