Ditur x Alvas | Case Study

The problem: Scaling personal content with 12.000 products

With the size and footprint of such big operations, Ditur faced problems in making truly personal email content to their customers.

And to make that personal content at scale.

Especially including information about the individual watch that a person has shown interest in has been impossible so far. They simply have way too many products, to write unique texts to each recipient.

That’s why they started using Alvas.

The goal: Write individual product emails to every customer

Their goal was to improve the buying experience for customers who have viewed a product or abandoned a cart on their website, by including product-specific information in each email.

With Alvas, they used generative AI to write a unique set of texts for each automated email they sent to their customers that fit the criteria of having abandoned their basket or product.

The results: 78% increase in conversion rate

To truly see the effectiveness of this new AI, they set up a split test.

A total of 6517 emails were sent, half of those were written with Alvas.ai and the other half were their original email setup.

The effect of improving the buying experience for customers could be seen directly in the performance results.

Emails with Alvas.ai saw an increase in Open Rate by 10%, an increase in Click Rate by 20%, and an increase in Conversion Rate by 78% compared to the original emails that were sent out.

Initially, the team was also concerned about the quality of emails, and whether customers would notice or think badly about AI-generated content.

When they looked at unsubscribe rates, spam complaints, or complaints to customer support, they saw no difference in the AI-generated content.

After the initial split test, Ditur has now started using Alvas.ai on 100% of the relevant emails they send out and has implemented Alvas on the Danish, Swedish, and Norwegian shops.