Boosting Mass Email Campaign Success x2 with Personalized Product Recommendations

Triggered emails are known to be more effective than bulk campaigns. According to our study of 610 ecommerce projects, the CTR (click-through rate) of mass emails is only 0.02%, while triggered emails have a 0.21% CTR.

This means you will receive almost ten times more conversions per triggered email than per mass email. There are several reasons for this:

• Greater Relevance and Perfect Timing: Triggered communication happens in response to a customer’s action—like signing up, making a purchase, or browsing pages. This means the content of the email is more relevant and reaches the subscriber when they are most interested in engaging.
• Personalization: Triggered emails often include personalized recommendations or offers based on the user’s past activity or interests. This includes when you address them by name, remind them about previously viewed products, or propose a selection of similar items.

In contrast, mass emails generate almost twice as much traffic to websites and apps because they are sent to a larger audience.

Striving to increase communication effectiveness, marketers often face low engagement and conversion rates. Mass emails don’t perform well enough since they don’t match the needs and interests of the recipients. Hence, each subscriber receives the same content. Therefore, the conversion rate is still higher in triggered emails: according to Yespo, the conversion rate for mass emails is 3.06%, while for triggered emails, it’s 5.22%.

The same goes for two other metrics — AOV (Average Order Value) and LTV (Customer Lifetime Value). Unlike mass emails, triggered emails use techniques to increase order value more frequently, such as upselling and cross-selling. Thanks to personalization and timely communication, welcome, post-purchase, and other triggered emails boost customer loyalty and engagement, encouraging them to stay with you longer.

We’re used to achieving high email campaign effectiveness only when we have enough information about the customer and the message reaches them at the right moment or as a response to a specific event.

However, mass emails can increase sales, profits, and customer loyalty if they include just one element: personalized product recommendations.

Next, we will consider the tasks this tool helps businesses solve and explore the process of generating personalized product recommendations in mass email campaigns. Additionally, we'll look at examples from companies like Comfy and Liki24. We will also show the results that businesses can achieve by adding recommendation blocks to emails.

Benefits of Personalized Recommendations in Mass Email Campaigns

Recommendation blocks are often used on websites, in mobile apps, and in triggered emails. Adding personalized selections to bulk email campaigns can make this channel even more profitable. Notably, product recommendations solve several problems:

1. Improving Personalization. 49% of consumers feel frustrated when they receive irrelevant content. 42% are dissatisfied when messages do not reflect their desires and needs.

Mass emails can be tailored to each subscriber's requests and interests, thanks to product recommendations. This increases the effectiveness of the email channel, as 80% of consumers are more likely to purchase from a company that offers a personalized experience.

1. Reducing Email Creation Time. Preparing a promotional email involves two key stages: selecting the target audience (segmenting the database) and filling the email with content. While basic segmentation (by gender, age, location, etc.) doesn’t take much time, creating micro-segments requires meticulous work from the marketer. However, even such promotional emails won’t be personalized for each individual subscriber.

To manually personalize content, marketers need to increase the number of email versions and segments, each consisting of only 3–10 contacts. This is a highly inefficient process when done manually.

Instead, marketers can use artificial intelligence. Algorithms will then select recommended items for each subscriber, and all necessary elements (prices, names, and images of products) will be automatically inserted into the email from the product feed.

Additionally, the likelihood of errors in selecting relevant products is reduced. Artificial intelligence recognizes human behavior patterns and more accurately selects products that may interest a specific customer.

How Product Recommendations for Mass Campaigns are Generated

The mathematical model behind Yespo AI algorithms is based on analyzing a large amount of customer data. It processes online behavior, including:

• interactions with products such as views, wishlist additions, cart additions, and purchases;
• actions on the website and app, such as search queries, favorite product categories, etc.

The neural network identifies behavioral patterns and recognizes preferences by studying a customer's history. This allows the algorithms to predict which products might interest a specific person.

The relevance of products for the recommendation block is determined based on scoring. The model assigns each product a score indicating its suitability as a recommendation for the user. Yespo's developers set a lower scoring threshold to filter out irrelevant options.

In Yespo, a marketer can set up extra conditions for the algorithms to consider when adding products to recommendation blocks. These product parameters can include:

• A minimum discount size;
• Brands the customer has recently shown interest in;
• New arrivals in categories the customer has viewed, and more.

Learn more about generating personalized product recommendations >>

How Ukrainian Retailers Boost Mass Campaign Rates: Insights from Comfy and Liki24

To measure the effectiveness of implementing recommendations in promo campaigns, we compared the indicators of emails over two months. 

Here are the types of emails we compared:

• with personalized selections generated by Yespo AI algorithms;
• with the same products for all subscribers, chosen manually by marketing specialists on our clients' teams.

Read on to learn how this has impacted conversions, average order value, and companies` website traffic.

Case Studies

Comfy

A well-known Ukrainian retailer Comfy added personalized product recommendations to its promotional email campaigns in the "Product of the Day" and "Day/Night Sale" sections. The company sent these emails to over 2.2 million subscribers.

Algorithms selected products for the recommendation blocks based on customer behavior data. We set up custom conditions for the recommendation block by adding 4 products from the "Best" category. Also, we included up to 6 bestsellers in the emails for new subscribers that had no history of engagement with the site by then.

After Comfy implemented personalized recommendations in mass emails, the company received the following results:

Liki24 

Liki24 decided to use a block with personalized recommendations along with its product selection. Such emails were sent to more than 70K subscribers.

So we got the following results:

Conclusions

Mass email campaigns are a great way to drive traffic to your website and app. However, they often don't perform as well as trigger emails because they have lower CTR and conversions. This happens because they lack personalization, which is what customers want. You can easily use personalized product recommendations to make mass campaigns more effective and profitable.

Yespo's AI algorithms take much of the work off marketers' hands, saving time, preventing mistakes in email creation, and tailoring product recommendations for each customer. Real-world examples from retailers like Comfy and Liki24 show that personalized blocks outperform standard selections by:

• Generating more clicks to the website and app;
• Achieving higher conversion rates;
• Increasing the average order value.

Consider the specifics of your business and target audience to maximize the use of product recommendations in mass email campaigns. Yespo specialists will happily tailor algorithms and strategies to generate product recommendations specifically for your company. Once the set of algorithms is defined, developers create a special module that marketers can easily add to promotional emails using a drag-and-drop editor.

If you want to implement such personalized recommendations in your campaigns, book a demo call or contact your customer success manager.

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