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EXPERIMENTATION | A/B TESTING

Optimize your site with an A/B testing agency

Optimize your conversions with Welyft, an A/B testing expert. Benefit from tailored support at every stage of your optimization strategy for tangible and lasting results.

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  • Fursac
  • Jardiland
  • Renault Group
  • L'Oréal
  • Sephora
  • Yves Rocher
  • Cegid
  • Bricomarché
  • Gamm vert
  • Hiscox
  • Byredo
  • TAG Heuer
  • Shiseido
  • agnès b.
  • A.P.C.
  • Etam
  • Monte-Carlo Société des Bains de Mer
  • RAJA
  • Mouratoglou Academy
  • Chaumet
  • Salomon
  • Alptis
  • OGF
  • Youdge
  • Domitys
  • Maison 123
  • Undiz
  • Bricorama
  • Rustica
  • Aroma-Zone
  • Air Caraïbes
  • Frenchbee
  • Air Austral
  • Compagnie des Alpes
  • Le Coq Sportif
  • Tediber
  • Brico Dépôt
  • Intermarché
  • OVHcloud
  • Brevo
  • Crédit Agricole
  • La Poste
  • Engie
  • GRDF
  • FDJ
  • Midas
  • ADEME
  • Oh My Cream
  • IKKS
  • CWF
  • Groupe Beaumanoir
  • Histoire d'Or
  • Mobalpa
  • Buffalo Grill
  • Hippopotamus
  • Fitness Park
  • Sunêlia
  • Tootbus
  • Virbac
  • Sector Alarm
  • Linxea
  • Eurécia
  • FullEnrich
  • Chronodrive
  • Meilleurs Agents
  • Canal+

  • Test your hypotheses

    Without taking the risk of investing in costly UX and IT projects

  • Optimize every click

    through A/B testing and maximize your conversion rates

  • Turn your visitors

    into loyal customers by testing personalization strategies

WHAT IS A/B testing?

Boost your performance with an A/B testing agency

Did you know that small changes can have a big impact on your conversions? That's exactly what A/B testing makes possible, and at Welyft, it's our specialty!

What is an A/B test?

Imagine you have two versions of a web page, a button or an ad message:

• Version A: your current design or text • Version B: a slightly modified version

We test these variations in real conditions on your audiences. Then, we precisely analyze which one generates the most clicks, purchases or engagement.

SERVICES

A/B testing agency offers

Our teams of consultants support you across all your A/B testing needs

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SOLUTIONS

Setting up an A/B test campaign

An A/B test follows a five-step process: building the hypothesis, validating the test plan and mockups, development, implementing and monitoring the test, then analyzing results and making decisions.

  1. STEP 1

    Building the hypothesis

    Every A/B test starts with a clear and measurable hypothesis: - What problem are we trying to solve? (e.g., "Does a more visible CTA increase the click-through rate?") - What improvement should be tested? (e.g., changing a button's color, text, or position) - Which KPIs should be measured? (click-through rate, conversion rate, time spent on page…) Example: "If we [change made], then we will observe an improvement in [main KPI] of __%."

  2. STEP 2

    Validating the test plan and mockups

    Before launching the experiment, we validate: - The test plan, detailing the variants to be tested and the methodology - The mockups, to ensure that the new versions comply with the user experience and technical constraints - The traffic allocation rules, defining how traffic will be distributed between versions A and B Rigorous validation ensures that the test will be reliable, actionable, and aligned with business objectives.

  3. STEP 3

    Development and integration

    Once the mockups are validated, we move on to the technical implementation of the test: - Development of variants on the chosen testing tool (AB Tasty, Google Optimize, Kameleoon…) - Integration of tracking scripts and verification that they work properly - Testing and QA to ensure no bugs will skew the results This phase ensures that the user experience remains smooth and consistent, regardless of the variant displayed.

  4. STEP 4

    Launch and monitoring of the test

    The test is live! 🚀 We activate the experiment and monitor in real time: ✔ The proper distribution of traffic between versions A and B ✔ The tracking of the KPIs defined beforehand ✔ The absence of bias that could skew the results Rigorous monitoring allows the test to be quickly adjusted if necessary and ensures a reliable and representative experiment.

  5. STEP 5

    Analyzing results and making decisions

    Once the A/B test is complete, we analyze the performance of each variant: - Which version achieved the best results? - Are the differences statistically significant? - Should the winning variant be permanently deployed? If an improvement is proven, it is rolled out in production across the entire site. Otherwise, a new iteration can be considered to deepen learning and refine optimization.

METHODOLOGY

Which KPIs can an A/B test impact?

Through A/B testing, we run experiments to help you achieve your business goals.

  • Conversion rate

    Increase the share of your users who land on your sites and complete a transaction.

  • Engagement rate

    Increase the average visit duration as well as the average number of screens or pages viewed per session.

  • Bounce rate

    Reduce the share of users who land on your site without performing any meaningful interaction.

  • Customer lifetime value

    Increase the duration and frequency of customer interactions with your brand to maximize their long-term value.

  • Opt-in rate

    Increase the number of users who sign up or give their consent to your communications.

  • Talk to a Welyft expert

    Book an appointment

SOLUTIONS

How do our A/B tests work?

Our CRO missions upstream of A/B testing are structured to maximize the impact of A/B test results. We start with an audit phase to assess your UX strengths and weaknesses. Then, we identify optimization opportunities through an in-depth analysis of user behavior, customer journeys and current performance.

A/B testing within the CRO method

Goal

A CRO audit is a key step to ensure the effectiveness of an A/B testing strategy. It's not just about randomly identifying areas for improvement, but rather structuring tests on solid foundations, relying on reliable data and objective analyses.

  1. Kick off & Scoping

    During this step, we clarify the method, gather teams' expectations, identify constraints, understand strategic challenges, define objectives and key performance indicators (KPIs), and align the vision of success.

  2. Analytics Audit

    After scoping, we begin the analytics audit, focused on quantitative data from your website. The goal is to analyze user journeys and understand "how" they interact with your templates. This allows us to identify your key audiences and determine where to focus your efforts.

  3. UX Audit

    The UX audit aims to understand the "why" behind the potential friction points identified during the analytics audit. Thanks to a CRO analysis matrix, we easily spot the elements on your templates that positively or negatively influence conversion.

  4. User testing (Option)

    By observing user interactions in real-life situations, we identify conversion obstacles and validate the hypotheses formulated during the analytics and UX audits. This allows us to propose concrete, tailored improvements.

  5. Roadmap prioritization

    Based on data from the audits and tests, we identify the initiatives with the greatest potential impact on conversion, while taking into account available resources and project constraints.

  6. Activation (A/B testing!)

    We implement the A/B tests prioritized in the roadmap resulting from the audit, in order to test the different solutions to the identified hypotheses.

Our A/B Testing Glossary

  • 🎰 Multi-Armed Bandit Testing

    The Multi-Armed Bandit (MAB) is an adaptive experimentation approach used to test multiple variants of a page or element while maximizing results in real time.

    A/B testing+ Details

  • Flickering effect A/B testing

    The flickering effect (or flicker effect) refers to a visual issue perceptible by the user when loading an A/B test:

    + Details

  • UPT (Unit per transaction)

    E-commerce indicator that measures the average number of items purchased per order.

    KPI+ Details

  • Session Replay

    Behavioral analysis technique that consists of recording and replaying users' browsing sessions on a website or application.

    + Details
View the glossary

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FAQ

Frequently asked questions

  • A/B Testing is a method that allows you to test different versions of a web page, graphic element or marketing message to determine which performs best. By displaying two variants (A and B) to distinct user groups, it is possible to analyze behaviors and optimize conversions based on real data.