Ligne-en-ligne.com & Keley Consulting Leverage Google Analytics to Maximize Marketing Budgets
Company Size
11-200
Region
- Europe
Country
- France
Product
- Google Analytics’ Multi-Channel reports
Tech Stack
- Google Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Revenue Growth
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Sales & Marketing
Use Cases
- Demand Planning & Forecasting
Services
- Data Science Services
About The Customer
Ligne-en-ligne.com is a leader in the French diet and well-being market. Its community gathers more than 800,000 free members and many thousands of premium members. Through a unique highly-interactive diet and fitness program, a team of nutritionists guides each member to achieve their diet goals. For the past couple of years, Ligne-en-Ligne has strongly relied on its affiliates network to draw in new, free and premium members. As a large part of the subscriptions streamed from affiliates, thus accounting for the largest part of marketing expenses, the team identified a potentially threatening dependence.
The Challenge
Ligne-en-ligne.com, a leader in the French diet and well-being market, relied heavily on its affiliates network to attract new members. However, the team identified a potentially threatening dependence as a large part of the subscriptions came from affiliates, accounting for the largest part of marketing expenses. The team wanted to understand the behavior of customers coming from affiliates, the primary sales driver, and how consumers who choose the highest value offers behave. They also aimed to diversify and optimize their digital marketing budget. To address these issues, they partnered with Keley Consulting, a Google Analytics Certified Partner, to analyze their traffic acquisition strategy.
The Solution
Keley Consulting used Google Analytics’ Multi-Channel reports to create personalized conversion segments to better identify and understand how each channel interferes in the conversions of the different offers. They created new conversion segments to isolate affiliate from the other channels and to split the welcome offers from other, higher value ones. The Model Comparison Tool was used to measure each channel’s influence on the conversion rate according to different schemes. The results of the study led to the development of a new growth strategy. They started by working on SEO and launched an action plan that included a radio campaign in a popular station and a new SEM campaign. They also worked to improve the ergonomic experience of the website’s most viewed pages to ensure that people coming through the affiliate channel would be efficiently caught.
Operational Impact
Quantitative Benefit
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