Newsletters are necessary but involve a lot of tedious and repetitive work. They are hard to personalize for each customer and typically see lower engagement. But what if newsletters could be automated, like triggered abandoned cart emails? This use case shows how newsletters can be set on auto-pilot for maximum impact with minimal involvement.
Who should care about this use case?
Here’s a typical profile: Jane is an email marketer who runs all email & lifecycle marketing for her company. In an average week, Jane’s team is tasked with sending 1-2 newsletters, monitoring automated campaigns, working on ad-hoc requests from other teams, reporting on campaign performance, working on seasonal campaigns or promo emails, A/B testing existing content and planning future campaigns.
Challenges that this use case solves
One of the most time-consuming tasks for Jane’s team is newsletter creation. While newsletters help bring back a lot of traffic to the website, the trade-off is hours spent creating a brand new email for every send. Often this includes:
Redundant work – checking links and testing previews for every new email
No way to personalize a mass campaign, or worse, replicating email copies to change content for different audience segments
Much lower engagement and conversions than triggered emails
No time left for analysis, optimization, and strategic activities focused on conversion
Direct results and business impact of this use case
This use case will automate newsletters so they are sent to the right audience, at the right time, with hyper-personalized content. This helps teams to:
Reduce repetitive work by auto-populating content and using that time to focus on A/B testing, designing new scenarios, and analyzing campaign performance
See better metrics (open and click-through rates) with 1:1 personalization and automatically send at the time the customer is most likely to engage
Ultimately, realize business goals with more conversions and build a team that’s focused on smart work.
Actual numbers realized by a real-world implementation of these features by Exponea clients:
+17 MHs saved weekly
How does it work?
The desired results can be achieved by implementing three things:
Recommendations in Exponea automatically deliver personalized content to customers based on factors such as previous browsing history, predefined rules, or machine learning. Marketers can create a dynamic Recommendation ‘block’ and pull that into email templates, which saves time, avoids repetitive work, and helps in 1:1 personalization to make the content highly relevant for each customer.
Subject Line Personalization
Subject lines can be personalized for each customer using Jinja (Jinja is a Python-based templating language. Users can easily add Jinja to email templates using dropdown menus in Exponea) to make them more appealing. This could be as simple as including the first name of the customer or it can be populated with products or categories that the customer has a high affinity towards. Exponea determines this from browsing history data.
Optimal Email Send Time Prediction
Exponea predicts optimal send time for each customer based on a combination of data like browsing and purchase history and analysis of past open and click times. This leads to higher open and click-through rates.
Ecommerce company wants to increase email frequency & boost sales by serving relevant content
An eCommerce company in the US is scaling back on paid ads to cut costs. They now want to leverage more email marketing and want an increase in conversions from emails.
The marketing team has decided to increase frequency by sending a newsletter every week. But they know they won’t see an increase in conversion just by sending more emails. So they are looking at ways to make the content more relevant to each customer.
The marketing team will now have to create a new email every week and source new content for each send, as well as test each new email. This is time consuming and repetitive work. In addition to this, the team now has to get creative and find ways to personalize the content. By broadly classifying their audience and rule-setting they can personalize content to some degree. But this means an additional workload to try and create different versions of the same newsletter every week.
How Exponea can help:
The company can easily achieve these goals in a shorter amount of time and with less effort by utilizing Scenarios, Recommendations, and Optimal Send Time Prediction in Exponea.
The marketing team sets up a scenario, creates an Email Template, and turns on Optimal Send Time.
Every week, the email will be triggered based on rules specified in Scenarios.
It will then refer to the Recommendations engine to auto-populate all content in the template. This content can be kept the same for all customers or can be personalized on a 1:1 basis.
In this case, the content can show ‘personalized recommendations for you’ based on the receiver’s most recent purchase and browsing history.
If there are no recent events, the recommendations engine will look at the user’s interaction history like purchases, views, or cart updates.
If that also isn’t available, more fallback options are provided.
Further, Subject Line Personalization using Jinja can populate the customer name or product or category that they’re most likely to be interested in.
Finally, Optimal Send Time Prediction will automatically determine the best time for engagement for each customer and send the email at that time.
All the team needs to do is create a template and set up a scenario – one time. The rest is taken care of automatically every week, significantly reducing mundane, repetitive work. The team is now free to focus on more analytical and strategic initiatives like A/B testing content or figuring out what content people are clicking more on, all while reporting better engagement and conversions.
Please find technical implementation here
What’s a Customer Data Platform? The Definitive Guide to CDPs (2020)