A/B testing email content the right way will help you avoid the spam folder and increase engagement.
Have you ever wondered, while looking at your email engagement stats - why certain subject lines and email templates have significantly higher open rates than others? There must be other reasons beyond recipients manually opening certain emails more often, mustn't there? Well, you were correct. Inbox providers (like Google and Microsoft) use AI to compare what you send against other content which has received low engagement in the past (or been marked as dangerous/spam) to make automatic decisions for filtering emails.
Based on your content, some of the places outside the inbox where you could be landing are:
Therefore, beyond using intuition or consulting lists of supposedly ‘good’ or ‘bad’ keywords, you might find yourself left guessing what aspect of your email content is contributing towards where your message ranks within the inbox.
Ideally, we want to achieve primary inbox placement and even with an important tag on your message in some cases (if you’re getting very effective). Throughout this article, we’ll discuss how the ranking/filtering process works and how you can iterate content by A/B testing over time to achieve a better placement inside the inbox.
The key aspects of an email which contribute towards inbox placement can be summarised across the following points:
You’ll immediately want to know what keywords inside your emails are detracting from your performance and eliminate them. This draws most marketers to search for lists of the most ‘spammy’ keywords over emails (i.e Hubspot’s list of 394 email spamming keywords).
Unfortunately, as HubSpot states in their article; spam filters have become far more sophisticated in recent years and look at the general context around your keyword selection rather than just the density of specific keywords. We’ve also found most marketers in our customer base are already using little to none of the keywords from lists like the above.
Therefore, although lists of trigger keywords can help to add context, you’ll find yourself in the position of not knowing or not having data on the impact of the following content decisions:
To be able to accurately analyse content for inbox placement you need to be able to see the result of exactly where emails are landing in B2B inboxes. This means you can’t use a small segment of your prospect list, because you won’t have the ability to see and compare where your emails landed inside the inbox.
Our solution to this at Allegrow allows you to send two variations of your email to approximately 100 unique B2B email inboxes (each) from our network. As this process gets carried out we automatically use our search-ability on those mailboxes to report on what percentage of each email variation is landing in the primary inbox vs spam or promotion folders.
This allows you to compare at a high level the inbox placement between your A/B version of email content and draw conclusions around optimal email structure and specifically the best way to express your value proposition over email to land in the primary inbox.
Importantly the data set we’re using is from live B2B email accounts inside the Allegrow network, which means you’re always able to test new iterations and stay ahead of the curve as the filtering algorithms Google and Microsoft use update over time.
When you’re creating a content test you’ll want to ensure the data you get back is going to be actionable and provide maximum value to your go-to-market. So, I’ve summarised our key guidance on the criteria of a great content test:
If you’d like inspiration for aspects of your email templates that you could iterate for testing the B version. Then, here’s a list of 10 examples of changes you could make across content tests to get you started.
Iteration on the subject line is very low hanging fruit when it comes to getting better inbox placement and engagement. You want to think about finding a subject line that is short (keep it around 3 words or less for prospecting), relevant to your content and similar to emails your target prospect usually opens on a regular basis.
Less is usually more when it comes to email. Experiment with being more concise and how this impacts your inbox placement. We usually advise emails in a prospecting sequence to be between 1-4 lines of text. Any more than that, and you’re probably doing too much (over) selling. Try cutting your content down to 50% of the words and see if you get a lift in engagement and inbox placement.
Your choice of keywords and phrases used in the body of text, can of course impact your inbox placement and email sentiment considerably. You can look to test specific ‘buzzwords’ to your value proposition with alternatives or re-phrase content altogether. We advise your focus when testing this area should be to find a balance between language which reads well and is optimized for inbox placement.
Seeing as the overuse of links can be associated with spammy content for an outbound email - we advise a maximum of two links in your opening sequence email (including links in the footer). With content testing, you can quantify the impact of different types and quantities of links in your content on spam rate. (i.e. The impact of a Calendly link with a link to blog content).
The primary call to action which you use in your go-to-market emails can be one of the main similarities between your content and spammy content, if you don’t test and iterate the emails ‘ask’ correctly. As Gong's research shows; you should look to confirm a prospect's interest with the CTA, rather than asking for time in cold outreach. As this is 2X as effective compared to average outreach emails.
Given that your footer/signature structure is added to every single automated email, it’s worth optimising and paying attention to. The following details are typically included to build credibility/context with prospects: Full Name, Job title, Company Name, Website, Phone number, HQ/relevant regional address.
Many businesses are experimenting with using bold words or different font types in prospecting emails to stand out. You can test content to establish the implications these changes may have on the natural inbox placement of your emails.
You’ll typically want to separate content in single lines to ensure your emails do not look like ‘too much hard work’ to read when a prospect initially opens them. This inevitably means creating your content in a way that may seem to contain an unusual amount of paragraphs, while editing this structure you can test the impact of different changes on how often each version of your content will reach the primary inbox.
Both the job title and name of the sender being used for cold emails can influence prospect engagement. Some businesses choose to repurpose the profile of the company's leadership across all their sending accounts for this reason (e.g. the CRO, CEO etc). Whereas, other businesses prefer the continuity of each SDR having their own name used for outreach to contacts that are assigned to them. Seeing as this is a relatively new area of demand generation set-up to experiment with, you may want to test your content going out from different mailbox names to see what aspect of the difference is due to contact sentiment vs natural inbox placement.
Having the prospect's first name and company included in the email isn’t exactly pushing the boat out when it comes to personalization these days. However, the placement of personalisation tags and the quantity of them you use can influence inbox placement. Generally, it’s advised personalisation is most effective at the beginning and end of a prospecting email - but, don’t shy away from testing these general assumptions for yourself.
We can clarify, the content and structure of your email will affect which specific folder inside the inbox your email gets placed in automatically by email providers. This directly correlates to the engagement rates you see on campaigns. If you’re at the stage of only optimising your emails based on how the end recipient would read them - That’s the equivalent of creating a blog post and disregarding any technical SEO considerations.
To conclude, using an environment of real inboxes which are unique and not connected to your internal domains, will allow you to automatically monitor where different versions of your emails land. Therefore, you can start to take a more methodical and data-driven approach to email content.
If you're curious to see how this works inside Allegrow or have content testing added to your existing Allegrow plan, you can book a demo with us here.