Analyze a database to create an email strategy
1. Download all your sent email campaigns from the past year, including metrics like open rate, click rate, revenue, and unsubscribe rate.
2. Open your campaigns in a spreadsheet program like Excel, and sort by highest open rate.
Copy and paste this data into a separate spreadsheet. Do the same for click rates and revenue, if applicable. Include only large sends. If you’ve sent an email to a small segment of 20 people, for example, this will have a much higher open rate and click rate than an email to 200k people, which can skew the results.
3. Take the top 10-20 open rates and create another column, then go through each individual email and tag it in your new column, the one you just created, by offer type.
Was the content of the email a % discount email, a particular product or service type, a holiday or a special event like Black Friday or Christmas, focused email?
4. Perform the same action as the step above for revenue and click rate, to see what offers or email types have yielded the best results over time.
It’s a good idea to cross-reference open rate and click rate. Find the emails that have both high open rates. A good target is 15% plus, and a good click rate, 1.5% or above.
5. Analyze your list and look at the content of each of these emails to determine what worked well.
For example, it can be the offer, the product, the timing, or the event type. Use this information to create a list of future campaigns and the relevant offers or messaging. While revenue per email is a very useful metric, it should be noted that revenue is often affected by a user’s onsite experience, rather than just the email content. This is why it’s recommended to use click rate as the main indicator of engagement.
6. Download or pull a list of clickers or buyers for each of your best performing emails from your email marketing platform.
7. Look for common traits amongst these users to develop or improve your buyer persona by answering the following questions:
Are the users mainly male/female? Are they predominantly located in a certain location? What age are they? What offers or benefits are they engaging with? Such as discounts or product type. Is there a common signup source for these users? Like Facebook campaigns, organic traffic, or Google Ads. You may end up having several buyer personas. For example, males aged under 25 from Europe engaged most with offer A, and females over 25 from the U.S engaged more with offer or product B. You can use this information to create specific segments with unique offers tailored to each buyer persona. Take notes of the most common location users are from, as this will affect your sending times, language, and region specific holiday promotions.
8. Use the collected data of your customers to create actionable insights about the benefits and offers you should highlight for each buyer persona.
For example, if you find users are 18-25 year old females in tertiary education, you know they are most likely price-sensitive and active on social media. So you would highlight pricing in your messaging and focus list-building efforts on social media platforms.
9. Segment your master list or full database, based on your buyer personas.
Develop tailored messaging and offers for each segment, based on benefit or product type that’s most relevant to them. Examples of segments include location, past buyer behavior, gender, life-cycle stage, interests, engagement, and age. Targeted campaigns and offers could include demographic-specific events like Father’s Day or regional holiday events like St. Patrick’s Day. The more targeted the content of an email, the higher the open rates and click through rates will tend to be. This results in a better sender reputation as most inboxes prioritize user engagement and action like opening, clicking, forwarding, when deciding on your sender reputation and inbox placement.