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If there was a common theme that resonated with marketing leaders in our annual survey and State of the Website report, it was opportunity. With AI setting a lightning pace of innovation, marketing leaders agree that the opportunity for growth is huge, while acknowledging that there’s a need for flexibility and adaptability as they set strategies for the future. 

So we invited three marketing leaders—Ashley Kemper of Pandadoc, Emily Singer of Drift, and Neda Stoll of HubSpot—to share their personal takes on the future of the web. How should leaders be thinking about new sanctions and laws around privacy? How can they improve existing processes and test out new ideas? And of course, we talked about AI. 

Read on for advice that your web team can use today, to prepare for whatever opportunities come our way tomorrow. To watch the discussion in full, check out our free webinar.

Forging new experiences with AI

In the coming years, we may see a shift in traffic away from organic sources and channels like search engines. “So the idea of a very static site, where everyone sees the same information when they come in, might not be the best experience for your customers,” Stoll said.  

Today, ABM (account-based marketing) is largely accepted as the gold standard of personalization. But it’s going to be more important in the future to be able to cater to individual accounts. “That gets a lot more complex, and that’s where AI can help drive efficiencies,” Singer explained. (Shameless plug: We recently acquired Intellimize, which helps marketing teams personalize their websites for different audiences at a one-to-one level.)

With marketing owning so much of the buyer experience and the web team, they have a chance to steer their company’s AI strategy and internal adoption. Scrappy marketing teams, in particular, can seize the moment. “Small companies have the opportunity to be AI-first and lean into some of these trends from a cultural standpoint, in a way that bigger companies will continue to face a challenge to do,” Singer said.

One more thing: As companies implement AI, there’s an opportunity for web teams to lean into what’s uniquely human, like creativity, humor, and relationships. “Incredible storytelling, high quality content that adds value to your customers and prospects—that continues to be core,” Stoll said.

Losing cookies without losing engagement

The future will be about finding new ways to balance being compliant with new privacy requirements, while still delivering the most relevant, engaging content to customers. Panelists stressed the importance of not giving up on personalization, and finding creative ways to deliver a great brand experience without cookies. 

Singer framed the shift this way: “It’s less about caring who they are—as in personal identifying information—and more about what they want, to be able to meet your buyer in the right place at the right time with the right message. If you’re able to do that successfully and drive a positive brand experience, then you can build that trust where they’ll voluntarily share who they are, and you can go from there.”

On a very practical level, it’s important for marketing leaders to start working with their legal teams early and often. “We’re learning a lot about different cookie access permission levels, and tools that our team has to make strong decisions,” Kemper said. “If you have a great legal department, pull them in for those conversations.”

Balancing ownership with collaboration

In our survey, marketing leaders named website ownership as a persistent challenge—one that resonated with our panelists. “If marketing doesn’t have ownership over your website, you end up spending a lot more time and budget on those ecosystems in the future,” Kemper said. (Our report found that marketing teams on average spend $1.6 million on their web team and software.)

But at most companies of sufficient size, it’s a balance, where ownership needs to be shared with engineers and satellite teams and regions to empower better processes.  

HubSpot has navigated this by investing in governance. “We try to provide marketers across the company with what they need to make sure they’re compliant, on brand, and set up for success, even from a measurement and tracking perspective,” Stoll said. 

“I’m excited to see the continued trend of engineers becoming less ‘technical-only,’” Kemper added. “I’m pushing for web engineers to own OKRs around SEO and performance and around website conversion rates, so that they can see the impact and the direct-line contribution to our customer experience.”

Testing and retesting to refine hypotheses

In our 2024 State of the Website report, marketing leaders listed “experimenting with new marketing strategies and tactics” as one of their top three priorities for the year. At first, this might seem surprising, because today’s leaders also report having smaller budgets and smaller teams. But marketing leaders understand that experimentation is a great way to accomplish more with less. 

“We have a culture of test and learn,” Stoll shared. “Just because a program or a test or an initiative didn’t work in the past, doesn’t mean it’s not going to work in the future.”

Kemper agreed. “Anytime you’re not testing on your website, it’s a lost opportunity. Every visitor is a potential data point to teach you something new. Being in the mindset of always-on testing, you are incrementally driving learnings over time.”

Wondering where to get started with testing? “Understand your goals,” Stoll said. “We usually start with a brief any time we want to test something. What are we trying to accomplish? Who’s our audience? Why do we think that testing is the way to achieve what we want?”

As marketing leaders look toward the future, one thing remains certain: the website will never be “done.” “It’s always evolving,” Stoll said. “It’s truly a journey, not a destination.”

Tree testing reveals how participants interact with your website’s navigation structure and provides valuable insights into browsing behaviors and thought processes. You can use this tactic to map out user paths and identify points of confusion or inefficiency.

Whether you’re launching a new product, redesigning your layout, or optimizing existing navigation, tree testing ensures your website feels as intuitive as possible and delivers a user experience (UX) in sync with user expectations.

What’s tree testing for websites?

Tree testing in UX design is a usability technique for checking a website structure’s clarity and findability, primarily for navigation. By presenting test groups with a simplified version of the site’s structural hierarchy, stripped of any design elements or content, tree testing focuses solely on the labels and organization of essential information, like section or item names.

It helps you gauge how user-friendly an interface is and how quickly first-time visitors can find what they need.

Here’s how a typical tree test works:

• Give participants tasks and ask them to find information or locate items within the website’s structure.
• They navigate through the hierarchy, or the tree, and choose routes they believe will lead them to the correct destination.
• The results reveal improvement areas — where participants take wrong turns, feel confused, or experience delays.

Tree testing is best for the early stages of website design. It allows you to identify and fix navigation issues before investing time and resources into full-scale development. Then, you can optimize the information architecture to create a user-friendly and engaging experience.

Tree testing vs. card sorting

Tree testing is also known as reverse card sorting. It’s a task-based activity where you ask participants to locate specific information on a website. Your primary goal is to identify their difficulties navigating the site’s layout and fix those areas to create better structures.

On the other hand, card sorting involves understanding how people naturally categorize information. You give participants cards that represent a piece of content or feature on your site, then ask them to arrange the cards in a way that makes sense to them.

There are two main types of card sorting:

• Open sorting: Participants create their own categories
• Closed sorting: Participants sort cards into predefined groups

With either approach, you’ll better understand the participants’ mental models, which helps you create more user-friendly and accessible site structures.

While tree testing measures a preexisting structure’s usability, card sorting helps you create or revamp a layout based on user input. Whether you opt for one or both, these techniques guide your design process to improve user experiences.

When to use tree testing

Tree testing is a versatile usability technique to use in various scenarios, including:

• Launching new products. When launching a new product, you must ensure a user-friendly navigation structure so people can quickly find key features and information like pricing and release dates. Tree testing validates the initial hierarchy and allows you to find and address issues before moving to the site’s final iteration.
• Redesigning or migrating websites. Your site’s existing layout undergoes a significant change during a redesign or migration. Tree testing checks whether the new structure meets user expectations and improves upon the previous version for a smoother transition.
• Following a card sorting study. After a card sorting study to understand how participants naturally organize information, tree testing is the next step to validate your architecture. This sequential approach allows you to create sites based on real feedback — card sorting reveals users’ mental models, while tree testing ensures the resulting structure is functional and navigable.
• Before creating content or layouts. Tree testing confirms that a site’s foundational structure is user-friendly, allowing you to work within a practical framework. Testing ahead of time reduces the need for significant changes later, saving time, resources, and energy.‍
• Optimizing existing structures. Even after your website goes live, you can tree test its layout to measure its suitability to current demands and identify areas for improvement. Incorporate this tactic into your regular workflow as an ongoing website optimization checkup to keep the navigation user-friendly and responsive to changing behaviors.

How to perform a tree test: 5 steps

Here’s how to conduct a tree test to gain reliable insights into your site’s navigation and usability.

1. Develop a user research plan

Establish a clear project scope so your team knows their roles and what the tree test aims to achieve. This includes defining your target audience, setting a timeline, allocating resources, and deciding how to recruit participants.

Your goal might be to ensure visitors can quickly find documentation, troubleshooting guides, and customer support. You can target existing customers or recruit participants by sending email invitations.

2. Prepare questions and tasks

Create practical tasks that mimic real-world goals, like “Find the user manual for the latest software update” or “Locate the customer support page.” These tasks guide participants through the tree and test their ability to find specific information.

Tips:

• Ensure the assignments are unambiguous (you don’t want confusion you could’ve avoided to muddle your data).
• Ask participants to fill out a survey for additional feedback.

3. Outline the tree structure

Create a stripped-down version of your site’s layout using wireframes and prototyping tools. Focus on a logical hierarchy with labels and exclude design elements.

For example, the tree structure for the customer support portal might look like this:

• Home
  • Documentation

• Troubleshooting
  • Common issues
  • Error codes
  • System status
  • FAQs

• Contact support
  • Email support
  • Mobile support
  • Live chat

When building a basic navigation structure, focus on the main categories and subcategories. Ensure each subcategory logically flows from its parent, and keep paths consistent across the layout. You can also conduct a competitive analysis to see how competitors structure their websites.

4. Test with users

Conduct the tree test with participants and ask them to perform the tasks. Observe their navigation paths and note difficulties they experience between the first action and final checkpoint.

Tip:

• Brief participants about the tasks but avoid any further information to ensure an authentic first-time navigation experience.

5. Review data

Analyze the insights from the test to find each participant’s success rate, time taken, and paths. Use this information to improve the navigation structure.

For example, the data might show that participants struggled to find FAQs and often looked for it under “Documentation” and “Contact support” instead of “Troubleshooting.” In this case, consider renaming or moving sections to improve clarity.

Tips:

• Identify common points of failure or confusion.
• Study participant feedback for additional insights.
• Reconduct the test with other participants for a larger sample size.

Optimize your website’s navigation with Webflow

No matter how high ranking or well performing your website is, you can always conduct tree tests to improve navigation. With changing trends and preferences, tree testing reveals where your site falls short and helps you create more intuitive experiences.

After performing a tree test and gathering results, you must translate those insights into a visually appealing, user-friendly website. With Webflow Enterprise, you can leverage a visual-first design platform with robust UI/UX tools. Plus, your whole team — developers, designers, marketers, and editors — can work on shifting and improving content with a comprehensive CMS.

Build, ship, and manage websites without relying on developers and scale your site today.

The purpose of data mapping is to combine insights from various sources and merge their related fields. Depending on your company’s needs, this can be an automatic or manual process. Either way, a proper data strategy will help you create a consistent, usable database, so we’ve documented a data mapping process to help you get started.

Understanding data mapping

Data mapping is the process of matching fields from multiple sources to create a consistent database. Data sources, like marketing metrics and customer relationship management (CRM) systems, often have slight differences in naming conventions that create conflicts when combining data. Hence, you need effective mapping when merging information from these various origins.

For example, your CRM might store a customer’s user ID as “USER_ID,” while Mailchimp could keep that same information under a field called “user-id.” If you attempt to create a report of all distinct user IDs in your system, this small difference might cause duplicate entries. Data mapping is the practice of applying specific techniques that correct these conflicts.

How data mapping works: 2 main techniques

The data mapping process might look very different for every business, but its primary goal is consistent. The first step is understanding your data — where it comes from, what it signifies, and how it all fits together. Then, you develop a series of transformations that carefully merge this information.

The data mapping technique that best suits your business depends on your team’s bandwidth, the collection scope, and the compatibility of your sources.

Here are two main techniques for data mapping, along with a brief description of how they differ.

Automated data mapping

In a fully automated process, companies use data mapping tools like those from Twilio Segment and Informatica to map information from hundreds or thousands of sources. The software typically leverages artificial intelligence (AI) or machine learning (ML) algorithms to create consistency, integrate common fields, and correct errors.

Let’s say you’re a regular Target shopper and have signed up for their rewards program, Target Circle. When you shop online, information from your shopping experience, such as your payment method and products purchased, goes to a data warehouse. Then, when you shop in the physical Target store, the information is sent to a similar warehouse, perhaps even the same one. These data points are the same across both purchase experiences but come from different sources using unique labels and fields.

Target could use an automatic data mapping tool to merge various source insights before adding the information to your customer profile in their CRM. Along the way, the tool combines similar fields, organizes them appropriately, and makes them compatible with the CRM.

Manual data mapping

A manual process involves directly translating data to its target destination rather than relying on a tool or automatic method. This often requires duplicated effort as customers or employees must enter data into one system for communicating information and another for storage.

For example, healthcare businesses increasingly rely on online forms for their intake process but also accept paper forms. The online and paper forms ask the same questions, but your paper forms must be transferred into the system manually. When the healthcare worker enters your information into their computer, they’re essentially filling out the online form for you. But they’re using software rather than a browser, which is a different source.

If the business uses a manual approach, a worker would code each field in their software to align with the online form’s back-end labels. That way, when they submit the information, it can go to the same place as the online forms.

Data mapping benefits

Data mapping establishes a cohesive database that prevents duplication and errors. Beyond the obvious advantage of improving consistency, mapping also brings the following benefits.

Diagnosis

When your data mapping process functions correctly, you can diagnose discrepancies, such as duplicate or conflicting customer profiles. As you detect such an issue, you can trace where the duplication occurred and then apply a new filter or other transformation to correct it. This procedure also helps you fix errors, find empty profiles, and refine device analytics.

Integration

Data mapping matches data fields, while integration involves merging databases. Successful data mapping leads to clean integration in which all fields combine coherently in one or many databases. To achieve that result, mapping identifies all the transformations each piece of data requires to become compatible with the target database.

Governance

Governance consists of the policies an organization adheres to regarding its data, and it’s become increasingly important. For instance, the European Union’s General Data Protection Regulation (GDPR) strictly regulates collecting and deleting data. They also require that businesses keep a comprehensive Record of Processing Activities (RoPA), which describes how data flows through their organization.

These strict regulations demand an equally rigorous process for maintaining your data. A sound mapping strategy ensures your data is well preserved within your database. This helps you avoid the expensive fines and time-consuming investigations brought on when a customer accuses your business of failing to meet regulatory expectations.

Data mapping features

Mapping quickly becomes challenging to navigate without the proper usability features, but tools like Informatica and DataGrail can simplify the process. Even if you aren’t using an automated tool, you can find ways to emulate some of these solutions’ features in your data mapping strategy.

Capabilities of data mapping tools include:

• Simplified GUI. A quality graphical user interface (GUI), typically a digital whiteboard, allows users to drag and drop nodes and draw connections between points on the map.
• Format/type indicators. Customizable labels, colors, and shapes differentiate nodes on the map.
• Templates. Users can leverage reusable templates to set up new mappings quickly.
• Transformation options. Easy filter, action, and sorting options enable users to transform mappings quickly.
• Automation. Automated actions create or alter maps according to predetermined guidelines, usually with the help of AI or ML algorithms.

The data mapping process: 5 steps

Implementing a systematic approach to data mapping requires a keen eye for detail and deliberate decision-making. To better understand your collected data, adhere to strict usage regulations, and avoid errors, follow this five-step process.

1. Define scope

Collect all sources you need to combine and identify the target destination for their merged data. Pay close attention to the data formats and organize them accordingly. For example, if you have customer profiles that you need to add to your CRM, assemble all the spreadsheets and forms that capture that information. Then, note all the fields you must fill in, such as “Name,” “Join date,” or “Purchase history.”

2. Characterize data

Clearly define all the various data points you need to map. Arrange them on a digital whiteboard into categorized groups that place similar sources together. Then, label every field in all the sources to make it easier to match them.

Remember, capitalization is important! If one source specifies “user-name” and another does “USER-NAME,” label them accordingly. This will be important in the next step.

3. Match related fields

Indicate which fields match with one another. Typically, this involves drawing lines between the sources to connect related fields, but feel free to create a system that works for you, such as color coding or differently shaped labels. Regardless of your method, your goal is to match fields like “user-name” and “USER-NAME” that must merge on their way to the CRM.

4. Apply transformations

Redefine necessary fields and labels to merge corresponding data points under a name the CRM expects. When using an automated tool, leverage its features to create consistent rules you can apply to future sources. If you’re doing this manually, keep track of the original field names and their merged equivalent. This will make it easier to apply to new sources.

For example, if you’re merging data sources that use different labels for “user-name,” check what the CRM expects and rename the field labels to match the CRM’s expectation. Take note of the original names to simplify mapping these sources next time.

When your transformations are complete, send the data to its target. Keep an eye out for errors and adjust accordingly.

5. Automate

Even with a manual method, try to leverage any features to automate parts of the mapping process. This helps prevent user errors and decreases process time. If you’re using a spreadsheet, activate sorting functions to keep the sheet organized as you add new entries. And if you’re using a digital whiteboard, save templates that let you drag and drop new entries faster.

Leverage the potential of data mapping seamlessly with Webflow

Data errors often occur because sources use wildly disparate labels for their fields. This can make data mapping challenging — but it doesn’t have to be. With Webflow, the Forms element lets you customize each field’s name, creating consistency with other sources in your data ecosystem.

With Webflow, you can transform complex data structures into visually engaging and interactive web elements. Our visual web development platform helps you elevate your data storytelling, enhance collaboration, and make your information accessible to a wider audience. Choose Webflow Enterprise for a dynamic and intuitive web experience that aligns perfectly with your data mapping goals.

When you first start creating content, it might seem like the content ideas never stop flowing. But eventually, the creative river dries up, the content calendar is empty, and you need help generating quality ideas that effectively engage your audience. Thankfully, there are many tried-and-true techniques for coming up with content ideas. Some involve researching topics in new ways, while others draw inspiration from other content creators’ ideas. 

Whichever technique you use, remember to take notes as you go. Write down even the smallest ideas to ensure nothing is lost. You never know what concepts might be useful.

18 strategies to generate high-quality content ideas

Sometimes, when you’re out of ideas, it’s best to take a break and try again later. Once you’re back from your break, try these 18 strategies to send your brainstorming in new directions.

1. Conduct keyword research

Research keywords associated with your brand, services, or products into a keyword research tool like Semrush, Google Trends, or Ahrefs. They’ll surface keywords and content topics that align with the ones you already have. This practice creates a cohesive content portfolio. 

2. Include user-generated content (UGC)

If your product includes a digital marketplace or even a forum, you have an endless supply of content from your audience. Check out UGC like reviews, memes, and assets, and then write articles featuring the best ones. To encourage users to create more content, try starting a giveaway or contest to incentivize them.

3. Social media feeds and tags

Social media algorithms excel at aggregating content followers might find interesting. They use hashtags and topics to detect what content is about and engagement metrics to determine what followers want to see. Leverage this system by creating a new account on a social media platform. Engage with hashtags, memes, and posts related to your topics. Then, take note of any content in your feed that you haven’t explored yet or seen on your other account.

4. Explore search engine suggestions

Enter a few of your existing topic ideas into the Google Search bar and see what comes up to discover new angles for articles. 

You can also enter the beginning of a question related to your topics to see what suggestions for full search terms appear. For example:

• “In Figma, how do you…”some text
  • Undo
  • Add captions
  • Make infographics
• “In social media marketing, how do you…”some text
  • Get followers
  • Advertise giveaways
  • Use Instagram

Any of these searches could be a new topic for a post.

5. Analyze competitor content

Review your competitors’ social media content, blog posts, and testimonials for inspiration. Look for instances where they cover something you don’t or where you find yourself asking a question their content doesn’t answer. For example, if you’re reading a competitor’s social media post about UX design, you might discover that they neglected to discuss color theory. Perhaps you did, too, and now you can correct that oversight with a blog post on the topic.

You can always borrow ideas from your competitors, but to overtake them in search results, you need to offer a unique, engaging perspective. Summarizing someone’s article is plagiarism and won’t help you climb the search ranks. Reflect on what you have to share with the audience that the competitor article doesn’t. 

6. Conduct a content gap analysis

A content gap analysis involves using SEO tools like Semrush or Ahrefs to research your competitors’ content and find gaps in your content portfolio. Look for keywords or topics they cover that you don’t or where they get more traffic than you. 

For example, if you share web development content, you could discover that competitors see more search traffic from articles about front-end development. Examine their article topics and keywords to determine what you’re missing, then generate content ideas that address those gaps.

7. Identify what customers struggle with

Users typically seek out content when they have a question to answer or a challenge to overcome. Reach out to your sales or customer support teams for insights on your customers’ top pain points, and brainstorm topics related to those areas.

8. Check out the “People also ask” section

In their results pages, Google and Bing offer additional answer boxes labeled “People also ask” or “People also search for” that suggest adjacent search queries. Use these suggestions to discover new topic ideas.

9. Expand on your successful content

Review your most successful content to identify subtopics and essential concepts you can cover or expand on. For example, if your top-performing articles are “Best of…” lists, brainstorm other categories you can cover in new lists. It’s a bonus if they’re related to a top-performing list since you’ll be able to cross-link to the new piece.

10. Interview thought leaders

Identify a prominent person in your industry and interview them for their perspective on important topics. Do some research to come up with questions to ask them, then write an article dedicated to the interview.

If your content focuses on writing and publishing, you could interview novelists like LeVar Burton or Elif Shafak. You could transcribe the interview into a blog post, and the authors’ thoughts could inspire other content ideas you can use on social media or in memes and videos.

11. Surveys

If you use platforms that enable real-time marketing, like LinkedIn, Instagram, or Reddit, send out a poll to ask your readers for direction. They might have ideas for content that would be helpful or interesting. Or, if you’d rather use email, send out a campaign inviting subscribers to complete a Google Forms survey.

In your survey, ask what categories readers want to see more of, which formats they enjoy most, and if they have suggestions. If you’re writing for a company that develops project management software, for instance, your survey might look like this:

• Which of these categories do you want us to keep covering?some text
  • Time management
  • Leadership
  • Agile methodology
• Which content formats do you enjoy most?some text
  • Social media posts
  • Polls
  • Tips & tricks
  • Interviews
• Are there any topics you want us to cover?

12. Leverage content idea generators

Use a tool like Hootsuite to generate ideas from a few keywords. Just input a content type, noun, and keyword to see many potential titles. Most of the titles follow a similar formula, such as:

• The ultimate guide to [verb] a [noun]
• The importance of [noun] to [other noun]
• How to make a [noun] [adjective]

13. Use AI tools

AI tools like StoryLab take idea generation a step further: They can create whole content campaigns with a few prompts and a general content type. The more detailed your prompts are, the more potential topics the AI will uncover. Even if you plan to write the content yourself, what the AI writes serves as inspiration. 

14. Subscribe to industry newsletters

Sign up for regular newsletters from industry-similar content creators to learn what they cover. You could find their newsletter raises a question you can answer.

15. Refresh or improve existing content

Although you should try to keep most of your content evergreen, some articles will require occasional updates. Audit your existing content to revise outdated information, repurpose content, or add new headings. For example, you might check that any software or hardware you mention is still available, and if not, update these articles with new products.

16. Get insights from conferences

Conferences and conventions are often a hub of cutting-edge information, so they’re a great place to learn about new products and techniques. Attend or find recordings for industry-relevant professional gatherings to research topic ideas.

17. Check out forums and FAQs

Explore forums like Reddit or lists of frequently asked questions about your product or industry to discover what people generally ask about. Nearly every question can become an article title. For instance, the query “How do you fix error 110?” becomes “Troubleshooting guide: How to fix error 110.”

18. Share behind-the-scenes content

Try a more personal approach with a content series that gives your audience a peek behind the scenes of your business. Show them how the team makes the product, publish interviews with coworkers, or create a list of fun facts about your team.

Build out your content strategy

Creating a quality and engaging content offering is effort-intensive, so you’ll want to start on the right platform. Webflow CMS brings everyone involved in the content creation process together. It includes professional features like custom fields, rich content embedding, and content migration. And it supports integrations with analytics apps like Nocodealytics to track your content’s engagement.

Track — and improve upon — your content’s performance with Webflow.

You know, cracking open an editor and creating a new page like this:

<html>
  <head>
    <title>Hello, World!title>
  head>
  <body>
    <h1>Hello, World!h1>
  body>
html>

More realistically, you’re using a UI library like React, and creating a reusable component. Something like this:

import * as React from "react";

export const HelloWorld = () => {
  return <h1>Hello, World!h1>;
};

Having the skills to express your ideas in code is a superpower and you’ve worked hard to unlock it. However, text-based coding isn’t the only way to bring these ideas to life. 

Our mission at Webflow is to bring these development superpowers to everyone, but not everyone wants to type arcane symbols into a keyboard and bang their head against the wall until they find that missing “;”. Some people want to realize their ideas visually by directly making changes to the result with a rapid feedback loop.

Text-based development requires you to edit your code in one tool and then build and run it separately to see how your changes look. It’s indirect manipulation and the feedback loop is long. Even with state-of-the-art hot reloading, if there’s an error in your program, you won’t see anything but an exception!

Here’s what an error looks like with hot module replacement:

And this is where visual development steps in. You edit the results directly and the feedback loop is immediate, offering a more intuitive way to bring ideas to life. Even if your program is incomplete you’ll always have a result to work with. Here’s what editing visually looks like:

To edit a program from its result, you need some guarantees. For starters, there’s always got to be a result, even if the program isn’t complete or has errors. If the program crashes or can’t run there’d be no way to fix it! You also need to be able to evaluate independent pieces of the UI (subtrees) efficiently or the latency of running “the whole program” creates too much lag for visual editing. You can’t have untracked side-effects like memory mutation either, otherwise re-evaluating those subtrees loses their state and causes unexpected behavior. This is what makes hot module replacement so tenuous when it comes to JavaScript. Beyond that, JavaScript has all sorts of “syntax sugar” for text-based developers that make it a difficult target for projectional editing.

This is a problem. When your mission is to unlock visual development for the web — as it is for our team at Webflow — it’s an imperative to solve problems like these. And on top of that, we don’t want to sacrifice the power and flexibility of the web platform in the process. We’re asking the question — how can we give our customers the same superpowers that traditional developers have.

To solve for all of this we created a programming language that is authored visually. We call it Webflow Design Language (WFDL) and this is our first time sharing it with the world.

Here’s a deeper dive into what it is, and how it works. 

Webflow Design Language (WFDL) is a programming language designed to be used visually. It is a projectionally edited, purely functional programming language that powers the Webflow Designer with a visual-first authoring experience. In even more computer science-y terms, it maps closest to a structurally edited, simply typed lambda calculus with a row polymorphic Hindley-Milner type system.

We take sites built with this language, interpret them and produce websites. Like the one you’re reading this on right now. Here’s a diagram of the high level evaluation and rendering flow:

‍

To break it down, I’ll introduce you to WFDL using the age-old programming tradition, “Hello World!”

Hello World!

Let’s dive in and look at some of the features our Webflow Designer offers and the WFDL that our customers (visual developers) are creating. Here’s how a user creates a “Hello world” text block:

When a user drags an element onto the Webflow Designer Canvas like this we create the following WFDL to represent the element:

A note: I’m showing you WFDL projected to its human-readable syntax, however, our tools work with the Abstract Syntax Tree (AST) structure directly. WFDL has some additional information such as scope-unique identifiers for each syntax node which are used for generating “source maps” that power visual editing. I’ve omitted them for brevity.

Here we are creating two elements.

1. Basic::Block element to represent the wrapping div with Basic::String provided as children
2. Basic::String with “Hello world!” as its value

Basic::Block and Basic::String here are fully qualified names. This is a fancy way of describing a unique ID we can use to look up the backing implementation of whatever is being referenced. Qualified names are how we implement name spacing throughout WFDL.

Basic::Block and Basic::String are also element types. They tell us what components these elements are instances of. So here we have an instance of Block and an instance of String provided by the Basic module.

This is how our visual visual developers add new elements to their site — with each element representing an instance of a component. To ground this in something that’s more familiar, if we were to do the same thing in React as code it’d look something like this:

import { Block } from "./basic";

export const page = () => <Block>Hello world!Block>;

Components

Now that we’ve covered elements we have the foundation for something far more interesting, components. Visual developers want to package up reusable parts of their UI and use them throughout their site. Let’s explore how this is done in the Webflow Designer.

In this video, we turn our “Hello world!” element into a component named “Hello World.” Then we create another instance of that component right below it using copy-paste:

When the visual developer changes the component, all the instances are updated. Notice how when we change the component from “Hello world!” to “Hello reader!” both instances are updated on the Webflow Designer Canvas.

Editing a component updates it everywhere.

When a component is created two things happen to the underlying WFDL:

1. We extract the parts of the UI that are meant to be reused into a new component and export that component from a WFDL module.
2. We replace the element with a new component instance element that points to the new component we extracted in step 1.

What’s happening to the WFDL under the hood in this video is an extraction of our Basic::Block to a new “Hello World” component, which we then exported from our Site WFDL module:

// Extract component to a module named Site
// Qualified name Site::HelloWorld is used to access this component
export HelloWorld = {
  name: "Hello World",
  render:  {
    children: [
      
        "Hello world!"
      
    ],
  } 
}

Second, we replaced the element we just extracted to a component with an instance that points to our new component, then we added another instance below it:

-  {
-    children: [
-      
-        "Hello world!"
-      
-    ],
-  } 
+  { } 
+  { } 

When we are rendering an element and encounter the type Site::HelloWorld, we retrieve its backing component from the Site module and then locate its HelloWorld export, retrieve its render expression, and render that. In this case our initial Basic::Block -> Basic::String -> "Hello world!" tree.

If we did this in React we would extract our component to a new module:

// Extract component to a new module, site.js
import { Block } from "./basic";

export const HelloWorld = () => <Block>Hello world!Block>;

And update the page to import and use that component.

import { HelloWorld } from './site';

<HelloWorld />
<HelloWorld />

Properties

One of the key aspects that distinguishes a component from an include or a symbol is the ability to provide props or options. Properties describe the settings interface for the component allowing each instance to provide different values.

Creating properties in components

In this video, the visual developer edits the underlying component to add a property named Children:

This property creation process involves two main actions:

1. Updating the render expression: The render expression is updated to include a variable bound to the new property. This allows the component to dynamically render content based on the provided property value.

2. Creating a configurable default value: A default value is established by extracting the prior content and storing it on the type. This default value ensures that a value is always rendered whenever the property isn’t provided.

The underlying WFDL changes to our component look like this:

// Site::HelloWorld
{
  name: "Hello World",
  render:  {
+    children: data.Children // Now a variable binding!
-    
-      "Hello world!"
-    
  } ,

+  // We'll talk about this later, this is a data type.
+  dataType: {
+    Children: {
+      name: 'Children',
+      type: List
+      defaultValue: [
+        
+          "Hello world!"
+        
+      ]
+    }
+  }
}

Notice that the “Hello world!” element was extracted and replaced by a variable binding to data.Children and prior content is stored as a default value.

A note: One challenge for direct manipulation is that the program must always succeed, or else there is no result to edit! So in cases of missing values we still need to produce something. To deal with missing values we either provide a default value or leverage typed holes as placeholders.

Providing property values in a component instance

Now that a developer has created a property for the component, they can provide values to customize the behavior and appearance of a specific instance. This allows the component to be tailored to specific use cases, making it more dynamic and versatile.

Providing a property’s value visually looks like this:

Here, we are editing the instances of the component to provide different property values for each instance. You’ll notice that the settings panel on the right shows the property value thatwe can also edit directly on the Webflow Designer. 

The underlying WFDL changes look like this:

 {
+  Children: [
+    "Hello friend!" ,
+  ]
} 
 {
+  Children: [
+    "Hello reader!" ,
+  ]
} 

If this were React code, it would involve updating our component to include a new typed prop, providing a default argument, and replacing the content with a children identifier:

import { Block } from "./basic";

export const HelloWorld = ({
  children = "Hello world!",
}: {
  children: React.ReactNode, // Specifying the type of the children prop
}) => <Block>{children}Block>;

Types

When we create a new property, we have to know its type so we can provide a consistent visual editing experience for this data throughout the Webflow Designer.

When we created and bound the Children property above, our component got a new dataType field associated with it that describes the property:

// I told you we'd talk about it later. Later is now!
dataType: {
  Children: {
     name: 'Children',
     type: List,
     defaultValue: [
       
         "Hello world!"
       
     ]
  }
}

When you create a property in the Webflow Designer, it automatically determines the property’s type based on the context in which it was created. For example, if you create a binding using the “Text” field of the Basic::Block component, the Webflow Designer infers the type from that field. In this case, the Basic::Block component has a data type for the “Text” property defined as List, so the new property will also be List.

Visual developers can create properties of different types to enhance their components. For example:

• Visibility (List): Allows developers to control whether specific elements are rendered based on a property.
• Image (Record): which allows developers to upload and provide references to images that are hosted on a CDN and made responsive automatically through our Assets panel.

In this video, the visual developer has created three properties of different types:

Which produces a component data type that looks like this:

{
  Header: {
    name: 'Header Text',
    type: List
  },
  Image: {
    name: 'Image',
    type: Image // (aliasing Record)
  },
  Visibility: {
    name: 'Show Header',
    type: Visibility // (aliasing List)
  }
}

A note: Types are qualified and extensible using WFDL modules as well, however, I’ve omitted the namespaces for brevity.

Notice how when we see a field of type List we provide a text box and allow Webflow Designer Canvas editing. When we see an Image, we provide an image editing experience. Our engineers can provide any number of types with different interfaces like this and WFDL glues them all together. With Webflow’s entire settings interface being driven by types, our dynamic variable binding experience is driven by the same typing system as well.

For example, if we put our Site::HelloWorld component inside this new component which offers a List Header Text property we can connect it to our Site::HelloWorld Children field because its type is also List property:

We provide this experience by running type inference on the current scope along with a typed hole, and if the type matches up, we present it as an option for filling in the hole using a binding. Holes are a type of expression that allow evaluating incomplete programs,which is vital for live editing. If the word “hole” came out of nowhere and you’re still curious I’d recommend reading this paper. It’s requirements like this that led us to create WFDL as a pure functional language, rather than using a JavaScript AST subset.

This binding approach is conceptually similar to how a text editor provides intellisense, only a step beyond that. Imagine being able to put an "_" anywhere in your code and your editor provides a dropdown with all the values in scope that could validly go there. The values don’t have to exclusively come from component properties either, they can come from many sources! Here you can see the power of type unification presenting “Blog Posts” options provided by our CMS:

In this image, you’ll also notice that you can bind to date fields provided by the CMS. This hints at other WFDL features around function calling, implicits & type aliases. WFDL has many such features that bridge the gap between code and no code, to name a few:

• Foreign function interfacing to interoperate with JavaScript. This lets Webflow provide code that our customers can visually consume. For example, date formatting functions or other JavaScript values.
• Host extensible type system with typed holes and inference that enables our team to provide unique custom visual editing interfaces that offer bindings out of the box with full support for type aliases that provide tailored editing experiences for the same underlying type. A good way to visualize this is a phone number editing experience being different than that of an email, but they’re both ultimately strings.
• Pure evaluation which enables many of our interactive live evaluation and debugging experiences. 
• Holes which enable us to support live editing, even if values are missing or corrupt.
• Replaying without executing effects again and so much more.

We’ve focused on how WFDL unlocks visual front-end development and shown how it produces HTML, CSS & JavaScript but that’s not all we use it for. WFDL evaluates to an intermediate representation that we turn into other outputs as well, for example, a JSON representation of the site for use in site-search indexing. We also compile WFDL to React components which powers a feature we call DevLink:

We also use it to power Site Search indexing:

An overview of what we’ve covered:

We decided to create a new visual-first programming language because editing JavaScript & React Abstract Syntax Trees (ASTs) directly didn’t offer the properties needed for a first-class visual experience. On the other hand, editing a haphazard JSON data structure didn’t offer the power of code. We didn’t make this decision lightly because we knew it was no small undertaking.

• We needed a small AST to target for projectional editing. The JavaScript AST is massive and contains a lot of redundancy from syntax sugar and years of cruft with lots of different types of syntax nodes.
• Efficient subtree evaluation requires controlled side effects without mutation. Unlike JavaScript, WFDL is pure which allows us to provide efficient incremental reevaluation.
• JavaScript has no solution for partial program states to support projectional editing. WFDL uses a combination of default values and typed holes to ensure you always have a result to edit. Projectional editing ensures you never have an error you can’t recover from.
• By targeting our abstraction we can do more than just render and edit React. We can compile to other frameworks or even platforms. Everything is statically analyzable which creates rich build time optimization opportunities we wouldn’t have with the dynamic flexibility of JavaScript.
• TypeScript’s type system doesn’t guarantee “complete” type inference. We needed complete type inference to determine which values could be presented as an option to specific parts of the program.
• Editing a simple JSON tree structure without programming language principles didn’t bring the full power of text-based programming to our visual developers.
• We server render all our sites and the security risk surface area for JavaScript is massive. We needed a solution that allowed us to constrain our user-provided risk while still enabling us to bridge the power of code with FFI. This enables Webflow engineers to add new value to visual developers in the form of plugins which I didn’t get to cover here.

At Webflow, we’re on a mission to bring development superpowers to everyone. It takes a lot of code to No Code. If you’re interested in learning more about WFDL let us know, or who knows, come build with us!

Website personalization is the act of tailoring a website to attract and convert prospective customers. With it, marketers can customize web pages, tailor web content, and present an experience to their site visitors that matches their consumer behavior. 

Also popular amongB2C and ecommerce brands, B2B businesses can benefit from applying website personalization tactics to their websites to entice and engage visitors. The only difference between the end goals for the two business types is the definition of conversion. For a B2B business, a conversion might be a lead form fill or a content download. For B2C brands, conversions are typically actions like adding products to a shopping cart or making a purchase. 

Below, we’ll dig into why website personalization is critical to B2B businesses, as well as a few examples of how your marketing team can tailor web content for your core audience.

Why is website personalization important for B2B companies?

Here are a few key reasons your B2B brand should be leveraging website personalization tactics in their marketing strategies:

1. To differentiate from competitors: B2B brands need to set themselves apart from competitors, and most do this through their website — the primary channel where prospects learn about your products. ‍
2. To improve the customer experience: Once you have a prospect’s attention, your marketing team needs to make sure that the content on your website speaks directly to that individual visitor and is appropriate for the buying stage they’re in. A positivecustomer experience reduces friction when optimizing for conversions.‍
3. To increase engagement: By personalizing your website for buyers based on their stage in the journey, your visitors are more likely to interact with your site pages. A first time visitor might be more inclined to register for an informational webinar, whereas a repeat visitor might be interested in a free trial or custom demo.

What are examples of B2B website personalization?

While the list of ways B2B brands can personalize their sites is endless, here are a few ways to get started.

Customize your website in real-time with zero-party data

One great strategy to personalize your B2B website is by collecting zero-party data early on in the customer journey. Zero-party data is information that visitors proactively share with your brand. For many businesses, zero-party data usually consists of valuable details like email addresses or phone numbers. While this type of data is integral to building a strong relationship with prospective buyers, we recommend thinking beyond standard Personal Identifiable Information (PII) when collecting zero-party data.

Take project management tool Monday.com’s zero-party data collection strategy, for example. On the homepage, the brand prompts visitors to pick how they intend to use Monday’s product. When a visitor picks an option, the “Get Started” button lights up in the corresponding color to their selection. In addition to this fun aesthetic choice, Monday can also use the zero-party data collected through this interactive element to customize the rest of the website for that particular visitor.

Use intent data to inform personalization

If your brand is executing against any sort of account based marketing (ABM) program, using buyer intent data to personalize the website experience for those visitors is non-negotiable. 

Before you start your ABM program, divide the contacts you are trying to reach into two categories: engaged and unengaged. Whether you choose to send these folks to your base website or alanding page, you’ll want to adjust the content they see based on their level of interest. Visitors who have engaged with you previously and have shown intent should see messaging around the value of your solution and how it addresses their pain points. Content for non-engaged visitors should stay higher-level, focusing on education and helpful resources to guide them further down the funnel.

Make the homepage unique using firmographic data

In addition to the other types of data mentioned in this article, firmographic data — data that provides information about a company’s characteristics and attributes — can also be helpful when personalizing your B2B website. Firmographic data can help answer the following questions:

• What company does the visitor work for?
• What industry is the company part of? 
• How much revenue does the company generate?
• How many people does the company employ?

Using this data, you can customize your homepage to cater to different types of visitors. Even within a certain industry, you may want to customize what visitors see based on the size of their businesses to better speak to their particular needs.

Small changes yield big results

Knowing where to start withwebsite personalization may seem daunting, but it’s achievable on even a small scale. These examples are just the tip of the iceberg and demonstrate the endless possibilities that exist for B2B brands looking to provide a more personalized experience for buyers. 

Remember: a more personalized experience is a more powerful and engaging customer experience — which means more leads and more conversions for your business. To learn more about creating a highly personalized website experience for your customers and prospects, get in touch with our team today.

And as a web development agency building for rapidly growing companies and organizations in Europe — we see this first hand. From an emerging Swiss brokerage firm, to a  Parisian media agency — and everything in between — our client base prioritizes localization because it’s vital to reaching new markets and customers. 

But as an agency, it’s up to you to deliver that value. Even though localization is a key part of your client’s strategy — they’re depending on you to offer strategic guidance through the design and development of a site. Your goal should be to hand off a localized site that seamlessly allows your client to go off and execute. 

And that takes careful planning and project management. 

Here’s our story on how our small but mighty team built a strategic, localized site for Flomodia, a media site dedicated to helping aspiring entrepreneurs across the world turn their dreams into reality. 

A small, award-winning agency

Even though our award-winning team has worked for over 100 clients — we’re actually just a small team of seven people. 

This makes the organization of our team extremely important. The work of each team member has an outsized impact, so it’s even more important that we get team structure right. 

At Digidop, we’ve built our team full of folks who exemplify the T-shaped model. A T-shaped team member possesses deep knowledge and skills in a specific area (the vertical bar of the T) but also has the ability to collaborate across different disciplines (the horizontal bar of the T).

When you make up a team in this way, your overall team as a whole is able to: 

1. Focus on specific goals and allocate the right resources to each project, according to the customer’s needs and the expertise of each team member.
2. Delve deeply into their expertise (UX, UI, Development) and truly become an expert in their field.
3. Challenge themselves and the project with their vision and skills.

Additionally, we always work collaboratively, with developers being on board from the very first workshops to facilitate easy information exchange throughout the project.

Who is Flomodia? 

So, when Flomodia came on board, and explained their needs, we knew our team was set up to tackle the job. As we mentioned earlier, Flomodia is a Paris-based media and content company that’s dedicated to inspiring, educating, and  entertaining entrepreneurs and aspiring entrepreneurs. 

Their primary medium is video — and they post all kinds of video content such as,in-depth interviews with prominent entrepreneurs, as well as different tips for entrepreneurs looking to start or grow their own business — among other things/ 

On top of this, they also host live events and talks to build and empower the entrepreneur community in France and have sponsorships with companies like Fiverr, Ahrefs, Shine, and Monster. 

Flomodia’s found great success in France, but when they came to us, they were looking to take their brand and content even further, and reach new audiences in the rest of Europe. 

For their site, Flomodia prioritized SEO above all else. They wanted to make sure that their site was strategically optimized, so that they could effectively reach their target audiences through organic search. 

They also wanted to have a CMS-first approach to the site. As content creators and event organizers, they need a lot of flexibility to scale their content quickly. They also wanted  to launch new services independently in the future, so having a CMS-first approach with pre-built components would allow them to be fully autonomous. 

Here’s how we approached the build.

How we built Flomodia’s localized site 

All of our projects start with workshops to thoroughly understand the company and their goals. We conducted several workshops with Flomodia, involving both designers and developers, to propose a strategy and web architecture that best suited their needs. In this case, it was  a highly optimized site for SEO and a CMS-first and components-first approach. 

Then, we took those learnings and used Figma to sketch out the architecture. Once that was squared away we then went on Webflow to build. 

When building we had these three considerations in mind: 

1. Wording: As a media company, the way they communicate and the words they use are crucial. They wanted to have 100% control over the content in both languages, and also have it optimized for SEO in both languages. 
2. Design: With several YouTube channels, some in English and some in French, the website needed conditional visibility ensure we were displaying the most relevant content to the target audience (or something more specific)
3. An all-in-one platform: Flomodia wanted a streamlined solution that wouldn’t require them to rely heavily on third-party tools.  With Webflow, everything was in one place, which made it the perfect platform to build their site. 

Here’s the step-by-step on how we built Flomodia’s site. 

1. Initial setup on Webflow First, we began by importing the validated mockups into Webflow and created the site’s design. This step laid a solid foundation for further development.
2. CMS integration Next, we set up the CMS collections to enable Flomodia’s team to manage content autonomously. We configured dynamic page templates for different content types such as articles, videos, and events, making updates and organization easier.
3. Managing multilingual content To meet localization needs, we integrated content in both English and French. We implemented conditional visibility systems in the CMS to display relevant content based on the user’s language and region. Language options via a drop-down selector and localization settings – like automatic routing – were also added for smooth navigation.
4. SEO optimization Because SEO optimization was a priority, involving the configuration of meta tags, page titles, and descriptions for each language. We applied best SEO practices to enhance the site’s visibility on search engines, thereby increasing its potential for organic traffic. Because Webflow’s platform offered a fully localized, best-in-class SEO right out of the box, it saved our team a lot of time for this step, while still giving peace-of-mind that we were delivering the most optimized site possible to the Flomodia team. 
5. Training and Documentation To ensure Flomodia’s autonomy, we conducted training sessions and provided documentation for their team, covering the use of Webflow Localization and daily content management, ensuring a smooth transition.

One thing that we adjusted for during the build was that Flomodia’s business was evolving during the project. To mitigate this, we helped them focus on their short, mid, and long-term goals and defined a release roadmap to achieve quick wins by releasing parts of the website incrementally. This approach allowed them to start reaping the benefits of their site, including improvements in brand image, SEO, and conversion rate as soon as possible. 

An award-winning site

When the site was fully delivered — the Flomodia team almost immediately saw results with their localized site. Their organic traffic tripled. and despite having even more content — with 17 collections, and 800 items — to manage with a localized site, they were able to launch new landing pages 50 percent faster — something that they couldn’t do with their previously unlocalized site. 

And that’s not all, the Flomodia site received two Honorable Mentions on Awwwards, and our team is already hard at work again to now elevate Flomodia’s site with an exclusive “members area” that provides exclusive content for paying members. 

Lessons learned 

Even though our team was the ones delivering, we’re always learning, growing and iterating from each new project, and we learned a ton when it comes to building a localized site. 

First, localization needs to be maintained, so always optimize your build and the platform you build from for your client’s future usability. Webflow Localization was particularly great for this because it allows you to manage everything from a single interface — versus using plug-ins or third parties. 

At Digidop we always deliver every Webflow website with a component library — and for localized builds in particular, we found it especially helpful for the client because it allows the client to easily manage and personalize their localized content using the properties settings in Webflow. For us, this is a must-have for anyone building a localized site for a client. 

The other thing that we also took away from this build was to make sure to create documentation and information for your client for a seamless handoff. It can be easy for your client to assume that everything — including translations — will be instantly localized, but if they want to add more content on their own, it’s important for them to understand what to do, so that they’re able to be fully autonomous.

Because Flomodia is so content heavy, and they’re creating new content every day — it was really making sure they understood how to localize and translate net-new content on their site using Webflow. 

Building on Webflow and using Webflow Localization both for us and the client was awesome because it was very easy to implement, and very clear to use — which isn’t always the case when it comes to localizing sites. We loved how integrated the feature was and we can’t wait to get started on building even more localized sites and delivering value to our clients. 

Historically, websites have served as the virtual storefront of most businesses, a place to learn more about a company or directly purchase products and services. Most websites today, however, are static, meaning they show the same information to every visitor. While consumer applications have started to personalize the experience for end users, websites have yet to catch up to the trend. Thanks to recent advances in technology website personalization is now possible, and a key tool to use in differentiating from the competition.

The concept of website personalization is simple: custom web experiences are served by leveraging data pertaining to the visitor such as demographic, firmographic, or other known information to provide them with a relevant experience. Personalizing a website has been proven to increase engagement and the likelihood of conversion from visitors.

The importance of website personalization

Most marketers know that website personalization drives higher conversion rates and more revenue. McKinsey analysts estimate that personalization could create between $1.7 and $3 trillion in new value for companies. It stands to reason that companies that don’t personalize their websites will fall behind competitors in their respective industries and ultimately lose market share to those who embrace website personalization.

While the importance of website personalization may be perfectly clear, there are misconceptions around how difficult it is to plan and implement a personalization program. In reality, it’s best to keep it simple when starting out. Here are a few things to consider when exploring website personalization as an option for your brand:

1. It doesn’t have to take a long time to get started: Look at identifying three elements of a webpage to personalize and testing three different versions of each element at the same time. This allows you to get started quickly and helps you identify which personalization efforts are having the greatest impact on performance.
2. You don’t need first-party data: First-party data can almost always help improve performance, but it’s not required. Contextual data such as geography, time of day, first visit/repeat visit, day of the week, and device type are available on every visit to your site. It’s easy to overlook the value of this contextual data; however, it’s common for these attributes to enable double-digit lift for marketers.‍
3. Website personalization won’t create inconsistent messages: Personalizing your site experience enables you to engage each of your website visitors in ways that are uniquely relevant to them. Each potential customer has different questions and considerations before moving to the next phase of their buyer journey. Website personalization enables you to have a consistent message for each visitor, every time.

There are some fundamental differences between traditional personalization, where marketers create segment-specific definitions, and AI-driven personalization, which leverages the power of machine learning to deliver unique experiences. It’s important to understand each method, and teams should keep these considerations in mind when determining the best method for their programs:

1. With AI, audience segments don’t have to be predefined: Personalization with machine learning doesn’t require you to predefine segments. Instead, AI-driven personalization automatically discovers segments by observing how messages perform for different audiences.
2. ‍Technical and engineering expertise isn’t required to start website personalization: Building your own personalization engine from scratch is resource intensive and requires specialized expertise. Instead, explore partnering with an external solution provider to help you with your personalization initiatives.

Previously, because of the high technical bar in creating AI-driven personalization systems, this approach has only been possible for some of the largest technology companies in the world. Today, marketers can implement an AI-driven personalization solution by adding just a single line of code to their website. With this approach, getting started with personalization is more accessible for companies of all sizes looking to deliver better user experiences.

With this in mind, it’s time to actually get started with website personalization — and that means exploring data.

Getting started with website personalization

How do marketers really use data in their personalization efforts? Here are five best practices for using data to build successful website personalization:

1. Leverage the data you can see on every impression: It’s easiest to start with data that is commonly available on every impression. This includes data such as device type, time of day, day of week, geography, and more. High performing segments are often found via this routinely available data. When you’re considering personalization, make sure the tools you are using can efficiently make use of this data.
2. Take advantage of UTM data: Use UTM parameters on links driving traffic to your site to further personalize based on the channel the visitor came from. Creative content, platform, and keywords can be useful in creating a seamless experience across your paid campaigns and your website.
3. Use first-party customer data to personalize the customer lifecycle: Your most valuable customers expect to be treated differently than a first-time visitor to your site. Recognizing these customers with tailored offers reinforces the relationship and can increase conversions and loyalty. Conversely, tailored offers for first-time visitors might look like free trial incentives or other messages around trying the product before they purchase.
4. Leverage third-party data for better relevancy: Third-party data can be particularly valuable to create relevant experiences for your site visitors. Some of this data can be demographic, such as age and gender, behavioral, such as past purchases and interests, and firmographic, such as reverse IP lookups.‍
5. Lean into AI: Given the rich set of data and number of potential segments available, using an AI based tool is particularly valuable for automating segment discovery and simultaneously learning which variations perform best for each segment.

AI and machine learning for website personalization

Website personalization doesn’t have to be a daunting ordeal. With AI and machine learning technologies now available, scalable website personalization is more accessible than ever.

Much of the work of conversion rate optimization is in managing experiments — design, setup, implementation, and analysis. This work is important, but also sometimes tedious and repetitive. AI automates the rote tasks involved in website testing, automatically applying learnings and freeing up marketers to focus more energy on strategic initiatives and projects that require human creativity.

Using AI in your website personalization program can also help you validate your assumptions about what resonates with your audience. Rather than pre-determining the messages that will resonate with each audience group, you can set up multiple options for each audience. This helps you learn what resonates with each audience and can inform the strategy for additional marketing campaigns.

To learn more about using AI to create a highly personalized website experience for your customers and prospects, get in touch with our team today.

And, oftentimes, managing these tests and interpreting their results takes away from the things that actually move the needle — like brainstorming and strategizing so that you can better understand and connect with your target audience. 

While this is a reality for many marketing teams, it doesn’t have to be.

What if you could dedicate more of your time to creating meaningful content for your audience that resonates with their needs? What if you could have the space to develop strategic initiatives that drive revenue, instead of executing on something half-baked? What if instead of doing things manually, automation could take care of tedious, time-consuming tasks? 

The good news? This is all possible with the help of AI. AI can do all of that and more while helping you accelerate personalization results and drive conversions and revenue. 

Now let’s take a closer look at how AI in website personalization works and how it can benefit your team.

What is AI?

To set the groundwork, AI is generally defined as machines simulating human intelligence. Further, machine learning is a type of AI that helps software applications more accurately predict outcomes. It works by taking data, training an algorithm, creating a prediction, and then running it in the real world. This process runs in a continuous loop, constantly taking in and learning from new data.

We see many examples of AI in our everyday lives, whether we realize it or not. A few common examples include social media algorithms, predictive searches, and recommendations on streaming services. There are many different ways we use AI in marketing as well, ranging from email automation to real-time personalization. AI empowers marketers by reducing manual work and automating processes — and most importantly — it enables marketers to spend more time doing what they do best — understanding their target audience, developing strategy and hypotheses, and generating creative ideas to appeal to their audience to incorporate into their campaigns and programs.

3 common myths about AI in website personalization

Now that you have a better understanding of what AI is, let’s take a look at how it works in your website personalization program. But first, let’s separate fact from fiction and debunk somecommon myths about AI.

Myth #1: AI is too complicated to use in your personalization program

People tend to think of AI as a complicated concept that will be too difficult to implement and use in their everyday work. This is false, running an AI-based personalization program actually makes your job easier, because the solution automates much of your work and can do things at scale. Rather than running one personalization campaign at a time and waiting weeks or months for results, AI can run countless variations at once and give you results in days or even hours. Plus, these solutions are no more difficult to implement than other website personalization solutions – you typically just need to add a line of code to your website.

Myth #2: AI can completely run your personalization program

While AI is a great way to manage your personalization program, it still needs your creative ideas in order to deliver personalized experiences to website visitors. The combination of AI technology and human creativity is what makes a website personalization strategy the most effective, leading to better customer experiences and higher conversion rates.

Myth #3: Everyone talking AI is telling you the truth

Many companies use AI as a buzzword but often overpromise on what their solution can do in terms of machine learning. Some companies promising AI actually don’t use any at all, while others may provide a data scientist as a service to build some kind of AI model manually. The latter option does create real AI but, since the model is built manually, it is likely not regularly updated or optimized. This doesn’t mean AI is untrustworthy, but it’s important to carefully vet any AI-based solution before making a purchase decision.

Questions you should ask when assessing AI-based solutions include:

• What does the system focus on? Is it optimizing directly for the key metrics you’ve indicated? Or, is it simply providing data or automation that fill a specific task in your overall process?
• How does the system learn? Does it require a lot of data upfront before the system can start making predictions and take action? Or does it start learning in real time as visitors engage with your site?‍
• Is the system transparent? Can you see the personalization decisions it’s making, and can you access the data–your data–reflecting these decisions?

Benefits of AI in website personalization

Now that you know what AI is and what it’s not, let’s dive into the benefits of using artificial intelligence in your personalization program.

• Reduced campaign management: With traditional A/B testing, the majority of your time is spent checking your campaigns to see whether they’ve reached statistical significance. But with an AI-based personalization program, all of that tedious campaign management is done for you. This means your team has more time to analyze results and brainstorm more creative ideas for future tests.  
• Accelerated learning: Since AI allows you to do things at scale, you can dramatically accelerate your learnings from your website personalization program. By running more campaigns at once, you’ll gain a greater understanding of how different messages resonate with your audience. AI-based personalization also yields faster results than traditional solutions, with some tests declaring winners in hours or days.‍
• Increased conversions and revenue: With an AI-based personalization program, you’re able to deliver a more tailored experience to each unique website visitor. By providing your website visitors with messaging and content that makes sense for them, you’ll improve the customer experience and therefore drive more conversions and revenue.

Two common approaches to personalization with AI

The benefits of AI in website personalization are clear, and there are multiple approaches you can choose from to personalize your website and drive more conversions. Here are two common approaches you might consider:

1. Rules-based personalization is where you create “if this, then that” statements for various segments of your target audience. With rules-based personalization, there are often three main components: defining the audience the rules apply to, creating the experience this specific audience will see on your site, and determining which pages the rules will apply to. While AI does help to automate your personalization program with this approach, there is quite a bit of manual work involved in coming up with personalization ideas and then creating the rules.‍
2. Predictive personalization goes a step beyond rules-based personalization by using machine learning to predict what will be the best experience to show each website visitor. Rather than having to manually set up rules, machine learning automatically predicts which is the best combination of your personalization ideas to show each visitor to deliver the optimal experience for them. The machine is constantly learning as it runs your campaigns, and can even update the experience as a visitor’s behavior changes.

With AI-based predictive personalization, your team can vastly improve the customer experience and drive better results. Just see how other marketers have succeeded using a predictive personalization tool:

Using AI to personalize your website

Incorporating AI into your website personalization program is one of the best ways to fast-track success. Harnessing the power of machine learning to serve the most personalized experience to each unique website visitor will ensure an increase in conversions and revenue.

Leveraging an AI tool amplifies not only your marketing team’s bandwidth, but also the impact that their unique campaign ideas can make. As visitor behavior changes, AI automatically adapts to meet these changes to continuously deliver the best personalized experience for each unique website visitor.

To learn more about using AI to create a highly personalized website experience for your customers and prospects, get in touch with our team today.