Case study: E-commerce backend optimization boosts revenue by 66%

Case study: PolarSport

How ecommerce backend optimization increased revenue by 66%

Company: PolarSport

Industry: Mountain Equipment

E-commerce system: Magento 2

The following case study is a reprint from the original PolarSport Case Study prepared by Alpacode.

Alpacode is a partnership alliance of two e-commerce companies Virtua and Hatimeria.

About the Customer

Polar Sport is one of the largest outdoor retail chains in Poland. The owners come from a mountain guide’s environment and understand their customers’ needs. They have ten stores in the biggest cities in Poland.

The store has been optimized for Core Web Vitals and passed all tests, showing significant speed improvement. You can read about it here.

However, optimization is a constant process that may require further actions, especially after some time.

Results

An increase of up to 66% in revenue
● 6,53 % in conversion rate
● 64,57% in transactions
● 0,91% in avg order value

Comparision y/y before (1-31.10.2021) and after optimization 1-31.10.2022

Avg Page Load Time
Decrease 41%

Page Views
Increase 42,65%

Users
● All users increase 46,09%
● New users increase 46,06%
● Sessions increase 41,01%

What we did

1. Slim down and cleaning of the database (from almost 12GB to 5GB), cleaning customer logs and unnecessary report tables. Database cleaning takes place cyclically on an ongoing basis, which strongly prevents it from swelling. It wasn’t just a one-time cleaning.
2. Improvement of the mechanism for cleaning outdated quotes (carts data) in the database.
3. Introduction of a mechanism for removing temp tables after reindexing.
4. Server changes, PHP upgrades, Percona and Varnish.
5. Removal of unused plugins and modules: 24 unnecessary modules have been removed.
6. PDP profiling: disabling the wishlist and unused reports, code optimization.
7. Profiling custom listings, code optimization.
8. Blocking unwanted indexing robots and specifying the subpages they have access to (through the robots.txt file and appropriate SEO changes).

Results in NewRelic

A decrease in web transaction time from 2000-3000ms to 1000-1500ms,
including:

• MySQL times down from 1000-1500ms to 500-600ms
• Drop in PHP times from 1000-1200ms to 600-700ms
• Increasing and maintaining Apdex score for the End User from around 0.91 to around 0.97

NewRelic – results in detailed pages

Business impact: a better user experience. Before the optimization there were issues with crashes on databases, indexes were jamming during high traffic. After the database was cleared, these incidents stopped. Also, excessive traffic of crawlers overloaded the website and database, after appropriate SEO changes the problem stopped.

The decrease in MySQL times is especially visible, – related to the cleaning and unloading of the database. The increase in the Apdex score for the App user also looks good.

Apdex score – after optimization

Apdex Score

As you can see optimizing an online store improves website speed, leading to better user experiences and increased conversions. Additionally, an efficient backend helps handle more traffic, significantly impacting revenue growth. And this is something we can help you with.