Mutjutin is a massage tool that 51,250 people already have in their pockets. Mutjutin has worked with Trustmary for a long time. In the early stages of the collaboration, we wrote about a test we did together with Mutjutin. You can read more about it here: How we increased sales by 139.16% with testimonials while reducing advertising budget by 21.81%
In the first phase, the collaboration focused on gathering new reviews, in the second phase on putting them to use on the website in a simple way. In the third phase we started to utilizing the references in advertising, and most recently we’ve started to do conversion optimization and A/B testing to figure out how to get the most out of the references.
“We use the Trustmary tool daily. We have automized the feedback collection process and now we ask each customer for their feedback automatically. At the same time, we’re collecting reviews from them. We then pick the best reviews from the pool of answers and use them in advertising and on the website. When the feedback collection is automated like this, the time spent with the tool itself is minimal,” says Jesse Ala-Lahti, the CEO of Mutjutin.
Mutjutin is a great example of a company that has a lot of potential for using reviews and social proof to boost their sales due to their high customer satisfaction. Even though over a thousand people have rated their services, their NPS score is still a staggering 56.
When the customer satisfaction is on a high level, the responses also generate a lot of positive reviews. The current number of positive reviews collected is 131, but new reviews are received almost daily. Here are some examples of reviews received by Mutjutin:
“The daily headaches are almost gone. Suitably small, very handy. Easy to use in many situations: in front of the TV. Affordable price, easy to order. ” – Mervi
As we discovered during the test we did about a year ago which we referred to in the beginning of this post, using social proof is an effective way to improve the advertising for a product like Mutjutin.
“Reviews still play a central role in our ad texts and, in a way, serve as the backbone of our advertising. Of course, in addition to reviews, ads must contain more than just the reviews. That being said, the effectiveness of our advertising would be significantly lower without reviews. With the help of reviews, you can also find new angles for your advertising”, Ala-Lahti explains.
In a recent experiment with Mutjutin, we started to utilize reviews through notifications on product pages. Below is an example of a review popping up from the bottom corner as a notification:
The starting point for the experiment was that the effectiveness of the reviews had already been seen and proven in advertising and on the website, but we wanted to test whether the product page conversion rates could be further developed by highlighting the best recommendations for the product page visitor in form of a notification.
From the 131 reviews collected for the test, the best ones were selected and the notifications were built using the Trustmary tool and an A / B test was created around them.
The notifications ended up being triggered with a 5 second delay from loading the product page, however, segmenting users to two groups:
1. Persons to whom the notification is triggered (approximately 50% of visitors)
2. Persons who were filtered to not see notification (approximately 50% of visitors)
The conversion rate and its development was measured among users who had browsed the product page for 5 seconds or more and by dividing that group into two parts: those who see the notification and those who do not.
The test period was initially defined to be August. At the end of August, it was decided that the test would run for a little longer in order to collect data for the duration of the new campaign as well. In the end, the test period finally turned out to be 1.8.-8.9..
The result of the test was that the conversion rate of those who browsed the product page for more than 5 seconds was increased from 7.36% to 9.03% by using review notifications.
Thus, for the entire test period, 7180 visitors saw the notification and 8423 visitors were filtered into the group that did not see notifications. Those who saw the notification made 648 purchases and 620 purchases were made from the filtered group. The Other category contains visitors who did not meet the set criteria, i.e. they practically bought the product without spending more than 5 seconds on the product page.
There is enough volume in the test that we can with almost absolute certainty say that the recommendations have significantly increased the conversion rate of the product page.
“The results of the test were pleasing and also really significant from a business point of view. A 22.6% increase in the conversion rate means that our annual sales will grow by tens of thousands of euros”, Ala-Lahti sums up his experience.