Web personalization is the practice of customizing users’ online experiences to their specific preferences and demographic profiles to improve engagement and conversion rates.
Web personalization is a powerful differentiation tactic for brands swimming in a sea of online competition. But changing consumer preferences means it’s also becoming more critical for success. In 2023, personalized product recommendations were the second most-desired ecommerce innovation by consumers of all ages, behind only frictionless payment options.
Personalization improves the overall user experience and drives conversions. Read on to learn how to use web personalization to engage and delight potential customers.
- Web personalization involves using relevant customer information to tailor website experiences to individual visitors and increase user engagement.
- Best-in-class personalization relies on user data and behavioral insights to provide the best end-to-end experience.
- Most consumers agree that a lack of personalization would cause them to lose loyalty to a brand.
The power of web personalization
Web personalization enables you to turn your standard website interface into a reflection of your visitors, empowering you to appeal to potential customers in a targeted and relevant way—saving them time and energy.
So, how does it work?
Personalization is informed by a user’s preferences, online behaviors, and demographic or firmographic information. It takes many forms, including custom designs or images, content, and UI elements like personalized modal windows or slide-outs.
Some examples of web personalization that brands across industries use include:
- Dynamic content: Dynamic content entails tailoring the content on your page to match the preferences or behavior of your visitor. Examples include serving new visitors with a discount code or using an exit-intent modal to prompt blog readers to enter their email addresses before closing out of your webpage.
- Recommendations: Personalized recommendations are suggestions directed at users based on their past interactions with your website. For example, an ecommerce brand might use a customer’s purchase or cart history to suggest products relevant to them. Or if you have marketing assets like educational blogs or white papers, you could recommend related content to your users based on their interests.
- Personalized messaging: Personalized messages on your website harness first-party data to craft tailored messages for visitors. For example, you could use information about a customer’s subscription level to upsell an advanced feature from a different plan.
Context and relevance play a huge role in driving user engagement. Well-timed, helpful personalization builds trust and loyalty—but a poor experience does the opposite.
In 2022, 62% of consumers worldwide said interacting with a non-personalized experience would cause them to “lose their loyalty” to a brand—up from 45% the year before. As the prevalence of personalization grows, users increasingly expect it. And irrelevant experiences provide little improvement over the spray-and-pray approach of more traditional marketing channels.
Enabling effective web personalization with data analytics
Data is the lifeblood of modern marketing and plays a critical role in implementing website personalization. Without the ability to source, analyze, and act on customer data, delivering personalization at scale that improves your user experience and drives desired actions is impossible.
That’s where website analytics comes into play. Marketing analytics platforms enable you to track campaign data, like ad spend, impressions, and clicks, across various acquisition channels. This makes it easy to gauge the effectiveness of your campaigns, test design, and improve content decisions to optimize your conversion rate and unpack audience interests at a granular level.
But marketing analytics can only take you so far. Organic traffic and ad impressions are just vanity metrics if you don’t have a mechanism to understand their impact on conversions and in-product actions further down the funnel.
That’s why platforms that combine website metrics with behavioral analytics are crucial to effective personalization. By sourcing in-product behavioral insights, your marketing and product teams can get a complete picture of the customer journey, from acquisition to conversion and activation. For example, you can use a data analytics platform to identify behavioral cohorts based on in-product user actions. Then you can create a view to cross-reference these with user acquisition channels.
Once you have a complete picture, your teams can use the data to deliver personalized experiences on your website at scale. Products like Amplitude’s Behavioral Graph even unearth emergent behaviors to create automated personalization in real time.
For example, let’s say there’s a strong correlation between users arriving on your website via social ads and the completion of a specific product action. You can use this information to create contextual content that’s personalized for their use case and serve it to them directly. Combining behavioral insights with user data enables your marketing teams to create impactful personalization from the first point of contact.
How to implement web personalization: Five practical steps
Bringing website personalization to life involves stakeholders across product and marketing and can feel daunting. But we’ve broken the process into smaller steps you can follow to kickstart your personalization efforts. Let’s dive in.
1. Data collection
Data collection can be complicated. With the deprecation of third-party tracking cookies, teams are increasingly reliant on first-party information that customers provide. To make matters worse, data is usually spread across numerous platforms, including customer relationship management (CRM) tools, analytics solutions, and product platforms.
Diving into data collection begins with clearly understanding your team’s goals. What are you going to do with the data? What questions will the data help you solve? And how will you get it?
Tools like Amplitude and Google Analytics can help you understand user behavior on your website, such as session length and bounce rate. Using tracking pixels can give you insight into acquisition and attribution patterns. Finally, implementing a product analytics platform enables you to track the actions users take once they’ve moved from a website to your app.
More than anything else, your teams are obligated to source user data ethically and securely. This is especially crucial for teams handling sensitive or protected information, like user health data.
Once you collect data, segment users into different groups based on behavior and other characteristics.
Categorizing users is crucial. It helps your team to identify the type of experience to serve and to whom as you map out your web personalization plan.
Some of the main segmentation types come from:
- Behaviors: Behavioral insights come from website-level analytics, such as session length and conversions, and product-level actions, like activation and engagement.
- Demographics: What are the shared characteristics of your users and customers? This can include everything from age and geographic location to their employer and job title.
- Preferences: Preferences can include user interests in your products and services. For example, if you’re an ecommerce clothing store, it’s helpful to know whether your users are interested in casual or formal wear.
3. Content adaptation
With the information gleaned from your data and segmentation efforts, you can begin creating and serving personalized content, messaging, and product recommendations to your different users.
Website content adaptation works best when you channel it to the right user at the right time. For example, if a potential customer on your ecommerce store previously looked at an item, you could use that info to recommend the same or similar product while they browse your page. For SaaS companies, a popup directing readers to a product demo might work best when you present it to readers on a bottom-of-funnel, high-intent comparison page rather than on a top-of-funnel, informative blog post.
4. Testing and optimization
Iteratively refine personalization strategies and tactics with your team to achieve the best results.
Conducting A/B tests for personalized content is critical here. For example, if your ecommerce store offers a code for 10% off to first-time visitors, you could compare success against different versions of the offer based on:
- Content copy
- Timing and page placement
We recommend testing one version at a time to ensure you’re not confounding variables and then incorporating your findings into future versions.
Deliver better web personalization with Amplitude
Your website is an opportunity to leave a great first impression on potential customers. By combining the power of data analytics and behavioral insights, you can stay ahead of the pack and create enticing experiences for your visitors at scale, regardless of your industry.
Ready to see how Amplitude Audiences can help you build personalization at scale? Check out our on-demand webinar for more practical tips and tricks on your journey to robust personalization.