A/B Testing in marketing channels

Optimise your marketing campaigns on-site and off-site with A/B/n split testing, understand customer behaviour and boost conversions

A/B Testing in Marketing Automation

Meet the tool

A/B testing (or split testing) enables you to refine your engagement campaigns and/or product recommendations by systematically evaluating different alternatives to understand what appeals the most to your audience at what situation. 

This data-driven method helps optimising cross-channel journeys, including email, push notifications, SMS, and WhatsApp, or on-site and off-site product recomendations. 

By continuously testing and adapting based on behaviour, A/B testing not only improves engagement and conversion rates but also offers deeper insights into customer preferences. This allows you to tailor your marketing efforts more effectively and build stronger, more personalised customer relationships.

How does it work?

The A/B/n testing framework is designed to convey experiments with the messaging or content provided to your audience to understand what genuinely engages your audience. 

1. Define Your Variables: Initiate tests by choosing elements to evaluate, from algorithms or UIs of Product Recommendations to campaign elements such as subject lines, call-to-action buttons, images, or dynamic filters.

2. Split Your Audience: Use the platform’s segmentation to divide your audience, setting test percentages and variable numbers to ensure test reliability.

3. Launch and Learn: Deploy your tests and gather insights. The platform offers real-time metrics to quickly identify top-performing variations.

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Precision Targeting

A/B testing enables precise targeting, both on-site and off-site, allowing you to optimise user experiences wherever they interact with your brand. 

On-site, test different layouts, content, and features to see what drives engagement and keeps users on your platform longer. 

Off-site, evaluate the effectiveness of email campaigns, social media adverts, and other digital marketing efforts to ensure your audience receives the most compelling messages, no matter where they are.

Enhanced User Experience

Creating tailored experiences for users both on your site and through external communications is key to building engagement and loyalty. 

A/B testing facilitates this by letting you refine every touchpoint based on user behaviour and preferences. 

This process ensures that whether users are browsing your site or interacting with your brand via external platforms, they receive a personalised and cohesive experience that resonates with their needs and interests.

Advanced Testing Flexibility

The ability to conduct multi-variant tests opens up a world of possibilities for optimising your marketing strategies. 

Beyond simple A/B tests, multi-variant testing allows for the examination of several variables simultaneously, providing a deeper understanding of how different elements interact and affect user behaviour. 

This advanced approach enables you to make more nuanced adjustments to your campaigns, leading to significantly improved outcomes across all channels.

Cross-Channel Engagement

Image Testing

Visuals play a crucial role in grabbing attention across all platforms. Experiment with different images in your web push notifications, emails, SMS, and WhatsApp messages to identify which visuals drive the highest engagement.

A/B Testing on emailsA/B Testing on web pushMulti-variate testing

Messaging

The wording of your messages can significantly impact their effectiveness. Test variations in your messaging across channels to discover the tone, style, and call-to-actions that resonate best with your audience.

A/B Testing on emailsA/B Testing on web pushMulti-variate testing

Dynamic Filters

Utilise dynamic filters to personalise your communications further. By testing these filters in your cross-channel strategies, you can fine-tune who receives your message based on their behaviour or preferences, enhancing relevance and engagement.

 

A/B Testing dashboardA/B Testing on web pushMulti-variate testing

Higher engagement rates

They also have higher engagement rates than other forms of communication, making them an effective way to reach customers. Additionally, push notifications can be used to increase website traffic and conversions with an opt-in of at least 16% in Spain and 18% in the U.S.A

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Product Recommendations

Algorithms

The backbone of effective product recommendations lies in the algorithms that determine which products to suggest. A/B testing different algorithms helps you understand which method is most effective at predicting and matching user preferences.

 

Multi-variate testingA/B Testing on-site

UX/UI Design

The user experience and interface design of your recommendation sections can influence how users interact with the suggested products. Test different layouts, styles, and navigation options to enhance user engagement and click-through rates.

 

Multi-variate testingA/B Testing on-site

On-site and Off-site

Extend the personalisation beyond your website by testing product recommendation strategies in your email marketing and web push notifications. This allows you to see how different approaches perform in driving traffic back to your site and converting interest into sales.

 

Product Recommendation in EmailA/B Testing AlgorithmsA/B Testing on-siteA/B Testing on web push

Higher engagement rates

They also have higher engagement rates than other forms of communication, making them an effective way to reach customers. Additionally, push notifications can be used to increase website traffic and conversions with an opt-in of at least 16% in Spain and 18% in the U.S.A

A/B Testing Algorithms Product RecommendationsInterface A/B Testing Product RecommendationsOff-site and On-site A/B Testing Product Recommendations