Office-Expert Case Study: Email Marketing for Office Supplies Shop – How to Get Customers to Spend More Than $100k Per Month

Results: Blocks with product recommendations generated up to 10% of income from the website.

The Client

Office-Expert is an online store that has been providing Kazakhstan offices with necessary office supplies and services since 2011. The company's clients include small private entrepreneurs and representatives of large businesses.

1. Office-expert.kz Success Story: Email Newsletter on a New Platform with ROMI at 440%.
2. Office-Expert.kz Success Story: How CDP Integration Generated Up to 50% of All Revenue From Triggers.

The Challenge

This time, the Office Expert team asked us to develop the website into a communication channel with clients. They also requested an increase in sales with an emphasis on cross-selling and upselling.

To keep the website as helpful and relevant as possible, it is vital to tailor content for a variety of online store visitors. Additionally, the maximum level of conversions will be achieved when users interact with the site.

The Solution

To accomplish our goals, we decided to implement product recommendations on the site. Based on the data collected by CDP (Customer Data Platform) web-tracking, eSputnik generates personal recommendations that will be shown to site visitors.

Artificial intelligence algorithms select goods for recommendation blocks by taking into account users' interests and their activity on the site, such as previously viewed products and categories, previous orders, abandoned carts, and similar factors.

Here is what we did: 

1. We completed a brief that indicated the following.

• Website pages to place the recommendation blocks.
• Product card design preferences.
• Recommended goods selection algorithms.
• Titles for recommendation blocks.

2. We set up web tracking.
3. We prepared a product feed.

The client started by setting up product recommendations on the product card page and the error 404 page.

We also A/B-tested the effectiveness of two blocks on the product card page – the "Personal recommendations" block based on user purchases and the "Similar products" block based on product category, name, price, and description.

Thanks to testing, we discovered that the "Similar Products" block was more efficient, and we decided to keep it.

The Results

In total, blocks with recommendations generated up to 10% more revenue from the site. Not only that, purchases from blocks with recommendations on the product page card had a conversion rate of 4.6% to 5.4%.

Testimonials

Daniyar Shaimergenov, CMO Office-Expert: