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What are the best ways to optimize onboarding tooltips with multivariate testing?

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Onboarding tooltips are small pop-ups that guide users through the features and functions of a product. They can help improve user engagement, retention, and satisfaction, but they can also be annoying, distracting, or irrelevant if not designed well. How can you optimize your onboarding tooltips to deliver the best user experience and achieve your product goals? One way is to use multivariate testing, a method that allows you to compare multiple variations of your tooltips at once and measure their impact on key metrics. In this article, you will learn what multivariate testing is, how it differs from A/B testing, and what are the best practices to optimize your onboarding tooltips with multivariate testing.

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Geosley Andrades

Sr. Director | Automation Evangelist | AI Enthusiast | Community Builder | Speaker
Stephen Platten

Award Winning Tester | Conference Speaker | Advocating Stoicism | Principal Consultant @ Inspired Testing | The Stoic…

1 What is multivariate testing?

Multivariate testing is a type of experimentation that tests multiple elements of a webpage or a product simultaneously to find the optimal combination. For example, you can test different versions of your onboarding tooltips, such as their content, style, timing, placement, and trigger, and see how they affect user behavior and outcomes. Multivariate testing can help you discover how different elements interact with each other and how they influence the overall user experience. Multivariate testing requires more traffic and time than A/B testing, but it can provide more insights and opportunities for improvement.

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Pratik Rohra

Rediscovering Marketing @ Zoho
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Beautifully described. Adding my two cents here: Multi Variate Testing (MVT) can improve user experience by up to 40%. This is because MVT can help to identify and fix usability issues that are causing users to abandon the product. Imagine a chef carefully experimenting with spices, adjusting flavors to create a culinary masterpiece. That's similar to how SaaS marketers can use MVT to optimize onboarding tooltips, enhancing the user experience and boosting product adoption. Marketers can test different tooltip/webpage designs, measuring user interaction metrics like CTR. For instance, especially in early-stage products, MVT helps identify the most effective tooltip variations, leading to a seamless onboarding process for users.

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Eduardo Tegeler

CEO Instituto Embelleze - Conselheiro - Palestrante - Treinador - Especialista em Vendas, Marketing Digital e Franchising
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Um ponto importante para acrescentar é que o teste multivariado te dá mais informa??es porém você precisa ter preparo para saber usar estas informa??es, muitas pessoas n?o conseguem usar a informa??o que tem para a tomada de decis?o correta. As vezes informa??o demais pode atrapalhar mais do que ajudar, ent?o, tenha clareza do que vocês precisa para executar da melhor forma possível e n?o fique só na teoria da uma análise.

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2 How does multivariate testing differ from A/B testing?

A/B testing is a simpler form of experimentation that tests only one element of a webpage or a product at a time. For example, you can test two different headlines or two different colors of a button and see which one performs better. A/B testing can help you validate your hypotheses and optimize your conversion rates, but it can also limit your creativity and miss out on potential synergies. A/B testing is more suitable for testing major changes or validating assumptions, while multivariate testing is more suitable for testing minor changes or exploring possibilities.

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Roberto Grassi

?? Global CSO & Senior Executive | ?? Ex Amazon, PayPal & Braintree, eBay, TeamSystem | ?? Digital Payments, Fintech & AI | ?? HBS Alumni
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In my experience an A/B test compares, for example, a standard ‘A’ version of a landing page with a modified ‘B’ one while multivariate testing changes more than one variable, testing all resulting combinations against each other at the same time. A multivariate can test that studies two images and four calls-to-action (CTAs) would test eight versions simultaneously, letting you determine which one is most highly optimized

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3 What are the benefits of multivariate testing for onboarding tooltips?

Multivariate testing can help you optimize your onboarding tooltips in several ways. First, it can help you find the best combination of tooltip elements that matches your user needs, preferences, and expectations. Second, it can help you increase your user engagement, retention, and satisfaction by providing relevant, helpful, and personalized guidance. Third, it can help you achieve your product goals, such as increasing activation, adoption, or revenue, by influencing user behavior and actions. Multivariate testing can help you create the most effective and efficient onboarding experience for your users.

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Geosley Andrades

Sr. Director | Automation Evangelist | AI Enthusiast | Community Builder | Speaker
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One prime benefit I see of multivariate testing is that it empowers making data-driven decisions. By testing different variations, you can identify what performs best, allowing you to make more informed decisions. Regular optimization and analysis via Multivariate testing help improve user engagement and conversion rates. Multivariate testing involves continuous learning, adaptation, and deep understanding of user behavior, helping you identify areas where you can gain competitive advantage as well.

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4 What are the challenges of multivariate testing for onboarding tooltips?

Multivariate testing can also pose some challenges for optimizing your onboarding tooltips. First, it can be complex and time-consuming to design, implement, and analyze a multivariate test, especially if you have many tooltip elements and variations to test. Second, it can be difficult to isolate the effects of each tooltip element and variation, as they may interact with each other and with other factors, such as user segments, device types, or external events. Third, it can be risky to expose your users to multiple and frequent changes in your onboarding tooltips, as they may cause confusion, frustration, or dissatisfaction. Multivariate testing requires careful planning, execution, and evaluation to avoid these pitfalls.

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Eduardo Tegeler

CEO Instituto Embelleze - Conselheiro - Palestrante - Treinador - Especialista em Vendas, Marketing Digital e Franchising
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Se atentar sempre ao “como” você faz as perguntas e “como” você interpreta as respostas. Cruzar dados é mais fácil do que tomar a decis?o. Simplifique seus testes para simplificar seu plano de a??o pois se n?o tiver um plano de a??o, nem fa?a o teste.

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5 What are the best practices for multivariate testing for onboarding tooltips?

Optimizing your onboarding tooltips with multivariate testing requires following some best practices. You should define your goal and metrics, choose the relevant tooltip elements and variations, run and monitor your test, and analyze and apply the results. Before running a multivariate test, you should have a clear and measurable goal and metrics for your onboarding tooltips. You should focus on the elements and variations that have the most potential to influence user behavior and outcomes. You should use a reliable tool to handle the complexity and scale of your test, ensure its statistical validity, analyze the results for the optimal combination of tooltip elements and variations, and implement it. Multivariate testing can provide valuable insights into user behavior and preferences that can help you improve your onboarding tooltips. How do you use multivariate testing for your onboarding tooltips? Share your tips and experiences with us.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Stephen Platten

Award Winning Tester | Conference Speaker | Advocating Stoicism | Principal Consultant @ Inspired Testing | The Stoic Tester |
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Seems like a useful testing methodology to use but I question how many companies fund this? A/B testing is often rare at mid to small level business so I doubt this is used outside of large tech firms. This my anecdotal opinion but get a working design and stick with it. Tweak and testing along the way. Building another design to do comparative testing seems expensive.

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Eduardo Tegeler

CEO Instituto Embelleze - Conselheiro - Palestrante - Treinador - Especialista em Vendas, Marketing Digital e Franchising
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Fa?a um planejando muito detalhado das respostas que você espera ter com o teste multivariado. Fa?a o exercício de imaginar ou deduzir qual será o resultado do teste, assim você tomara melhores decis?es para extrair o máximo possível do teste.

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What are the best ways to optimize onboarding tooltips with multivariate testing?

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1 What is multivariate testing?

2 How does multivariate testing differ from A/B testing?

3 What are the benefits of multivariate testing for onboarding tooltips?

4 What are the challenges of multivariate testing for onboarding tooltips?

5 What are the best practices for multivariate testing for onboarding tooltips?

6 Here’s what else to consider

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What are the best ways to optimize onboarding tooltips with multivariate testing?

1

2

3

4

5

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1 What is multivariate testing?

2 How does multivariate testing differ from A/B testing?

3 What are the benefits of multivariate testing for onboarding tooltips?

4 What are the challenges of multivariate testing for onboarding tooltips?

5 What are the best practices for multivariate testing for onboarding tooltips?

6 Here’s what else to consider

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