[CASE STUDY] + 780% in Monthly Revenue in just 6 Months

In this article we will analyze in detail how we helped one of our clients to multiply their monthly turnover by about 8 times.

Initial Situation

The customer comes to us because he is dissatisfied with the results obtained up to that moment.

Previously partnering with other agencies, this Shopify ecommerce already had a history and, among others, had the following KPIs on a monthly basis:

Revenue Medium Cart Conversion rate Revenue per user
xxx 22.2 0.58% € 0.25

Our business

Those who know us know very well that our support focuses on 2 main areas:

  • Programming of front-end solutions and A / B test for CRO and average trolley increase
  • Management of data driven marketing campaigns with the sole aim of selling

Programming Service

All the programming activity focused mainly on the following aspects:

  • creation of useful elements to increase the conversion rate
  • creation of useful elements to increase the average shopping cart
  • inclusion of elements of social proof and trustability

Here are some examples of custom sections and blocks that we have created for the purpose.

Quick add-to cart keys on all product cards

quick add keys

Progress bar free shipping

Progress bar free shipping

Bundle in product page 

Product page bundle

Toast product on offer

Toast product on offer

As always, for both new and existing themes , we have also created sets of settings , like the ones below, so that the customer can independently manage all aspects of the new elements added to the website:

Custom Hoculus settings

Clearly there was no lack of A / B Tests to verify that these elements actually made improvements in terms of average revenue per user (Find out what an A / B Test is and a detailed example of how it is done ) .

Marketing Service

Our data-driven marketing activity is based on a simple rule: what sells works .

With this client, the initial goal was to plan the strategy on Google ads and Meta ads (Facebook and Instagram) in order to turn the majority of visitors into buyers.

By analyzing data , content , texts , campaign structures and much more, we noticed how the previous activity was only focused on communication, without being able to convince users to buy in any way (campaigns on Facebook and Instagram had as a goal: click on the link, reach and only a few rare offers were promoted with a conversion goal).

The first step was to set up search campaigns aimed at covering the traffic related to the keywords related to the brand and max performance campaigns to take advantage of shopping , displays and videos . In this way we made sure to effectively capture the attention of aware users and turn them into customers .

In the meantime, we have activated collaborations with micro-influencers to generate UGC (user-generated contents) in line with the brand, which were able to create interest , interactions and contents to be used on Meta ads.

This activity turned out to be anything but trivial, in fact it always involves a phase of research , negotiation (usually we are able to work in exchange for goods), contractualization and follow-up to make sure that everything goes according to what was agreed.

Once we obtained the UGCs, we also created ad hoc creativity capable of communicating directly and persuasively on the reasons for buying the customer's products.


At this point, we have structured the campaigns on Meta ads in order to effectively cover all levels of the funnel , without taking anything for granted, with the aim of generating the maximum number of conversions and reaching the turnover targets.

Our approach in marketing, as well as in the programming part, is based on tests that allow us to validate the initial hypotheses with real and statistically relevant data.

Through an iterative process , we have progressively tested , optimized and scaled the campaigns, eventually spending several hundred euros a day to achieve the set goals .

Current situation

After a 3- month development-only period followed by another 3 months of development and marketing, the monthly KPIs became the following:

Monthly turnover Medium Cart Conversion rate Revenue per user
Before xxx € 22.2 0.58% € 0.25
After xxx € 62.28 2.41% € 1.12
Variation + 780% + 180% + 315% + 348%

Trend of the average cart

average order value

Conversion rate trend

conversion rate

Trend in revenue per user

Revenue per user

If you want to learn more about these topics and receive free advice for your e-commerce, do not hesitate to contact us!

FIND OUT HOW WE CAN HELP YOU

Book a free consultation now

Book now