Case Studies


LamaLoLi is a European online children’s retailer and wholesaler, welcoming 100’s of thousands of visitors to its site each month. The e-commerce site offers over 1,500 products from 50 brands across 30 categories, such as clothing, shoes and accessories. Customers can visit LamaLoLi.com via their desktop retail website and a mobile retail website. A third platform, the wholesale site, operates separately to the retail sites, but is managed under the same Google Analytics account. Their website can be accessed in 8 languages and transactions can be processed in 4 currencies.


After the initial investigation of LamaLoLi’s Google analytics setup, we discovered that their account was presenting some unreliable data. In order to overcome these discrepancies, Seperia reconstructed LamaLoLi’s Google Analytics account from the ground up. This was a complex task, requiring a thorough mapping of their original analytics account configuration.


The following case analysis presents LamaLoLi’s core analytics goals, the challenges we overcame whilst implementing GA, followed by the overall results of our service.


Goals of the Google Analytics Re-structure


Following successful reconfiguration of LamaLoLi’s Google Analytics properties and validation of all data, the following goals were addressed:

  •  To migrate LamaLoLi’s web properties to Universal Google Analytics, in order to take advantage of advanced features such as Enhanced E-commerce and User ID that are only available in UA.
  • To migrate all marketing pixels from the site’s source code to being managed through Google Tag Manager.
  • To help executives better understand core website performance indicators, including granular data from the cart and checkout process, and monitoring users’ behaviors using thorough data analysis.

Challenge 1: Implementing Google Analytics across 3 web properties


The Google Analytics implementation was carried out across three web properties:

1. Web (Retail)

2. Mobile Website (Retail)

3. Wholesale

Each property required separate configuration treatments such as goals, funnels, filters etc…


The Solution


From the GTM Perspective

We used the variable type ‘Lookup Table’ to match approximately 10 different domains and subdomains to a certain environment (including development environments).  

GTM Environment


From the GA Perspective

We used multiple trackers in order to send data to 4 different web properties. That is, 2 simultaneous hits- one for the currently viewed property and one for the “All” property:

  • All
  • Web
  • Mobile
  • Wholesale

This enables both a property- specific analysis and an overall analysis of more than one web property, such as the ‘end-user’ view that combines web and mobile environments.


The Result


LamaLoLi’s Google Analytics properties were upgraded to Universal Analytics with the addition of three more web properties- one for each property with dedicated views per country.


Lamaloli web properties


Web Property


Challenge 2: Managing all marketing pixels in 8 different languages on 3 properties from 1 Google Tag Manager container


Managing the marketing pixels of three different web properties within one Google Tag Manager container required more thorough implementation than simply placing a code snippet within the source code of a specific page.


Regardless of the difficulty of copying currently implemented pixels properly from the site’s source code to GTM (some included dynamic values like cart and transaction data), managing all of the pixels from one container required very strict rules and organization to make sure no pixels would be fired in the wrong case. For example LamaLoLi requested the implementation of some language oriented pixels, such as a Facebook remarketing list pixel for French speakers only.


The Solution


We created a {{language}} variable that takes the language value from the GTM dataLayer (provided by the developer) returns the current individual language, across all 3 web properties. This way, we were able to manage each tag in its respective language. 

 GTM Language



The Result


LamaLoLi now sets and publishes all marketing pixels via GTM. Their developers do not need to be too heavily involved in the implementation of new pixels.
Their container currently includes:

  • 50 tags
  • 100 rules
  • 50 macros

The following is a visualization of Lamaloli’s GTM container, demonstrating the relationship between tags, triggers and rules. A complexity the developer does not have to worry about thanks to GTM.


GTM Visualization

Visualization Tool: http://v2.gtmtools.com ; JS Library: http://d3js.org/


Challenge 3: Tracking Users in a One Page Application Angular JS Framework


The mobile platform is a one page application, based on an Angular JS javascript Framework, essentially meaning that as the user lands in the mobile site, the site loads once, no matter how many pages are viewed. The only requests the browser does beyond ‘loading once’ is to take data from the server such as product image, product ID etc…


The Solution


We used Google Tag Manager to track page views (in javascript: History Object pushStates). Further to this, we formulated specific methodologies to achieve even better results.


Final Results


Following the migration to Universal Analytics and optimization of LamaLoLi’s Google Tag Manager account, LamaLoLi’s executives now possess a better understanding of their consumers’ behaviors through access to more accurate data: geographical views, behavioral metrics, internal search, cart and checkout performance, overview of all properties together and more.


The proper collection of data as well as its arrangement are crucial to the maintenance of a Google Analytics account. Our services now focus on reporting, dashboards and implementing the new Universal Analytics Enhanced Ecommerce feature.


The following are examples of two dashboards Seperia has created for LamaLoLi, showing a combined overview of core metrics from all properties (figures have been hidden for privacy purposes). Another advantage the dashboards provide is the “Site Average” data display, reporting the proportion of each metric per property in relation to the site’s total.


Properties’ E-commerce Dashboard:


ga conversions dashboard


Properties’ Goals Dashboard:


ga goals dashboard


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