What Is Web Content Personalization?

Web content personalization is the process of creating and delivering customized content and experiences for website visitors and it’s a must in today’s world. 

Based on their experiences with the likes of Amazon and Netflix, even business prospects and customers expect all their digital experiences to be tailored to their preferences, geography, interests, and more. Simply put, they want the most relevant experience possible to streamline their purchase process. 

In fact, prospective buyers decide whether to trust a company based on their web experience. If that site (i.e., company) is not delivering a relevant experience for a potential buyer at that point in their journey, it is falling short on its value promise. In frustration and disappointment, the visitor is quite likely to leave the site, and quite possibly never return. As a result, the company never gets a chance to explain the value of its offering and convert a potential buyer into a customer. 

Marketers spend billions to get prospects to the website, only to provide a low-conversion, one-size-fits-all experience. This is the biggest squandered opportunity in all of marketing. 

To drive conversion rates up, marketers need websites that perform differently, ones that deliver highly responsive, highly personalized website experiences in the moment. These are websites optimized for every single visitor, not lowest common denominator sites set in concrete. 


Two Key Web Content Personalization Options

Marketers typically call upon one of two methods to personalize web content and experiences: rules-based personalization and predictive personalization.

Rules-based personalization

Rules-based personalization avoids the winner-take-all approaches of A/B testing and multivariate testing to show a different experience to each site visitor. 

With rules-based personalization, marketers set up a series of rules to determine what each site visitor sees and experiences on their websites. The personalization in this case is prescriptive: the marketer chooses in advance what each segment sees. Some refer to rules-based personalization as real-time personalization because what each visitor sees is determined in real time as the page is rendered. The important distinction is that marketers must set the rules up far in advance.

Marketers need to know in advance which segments are going to come to their site, and must be able to identify each visitor by their segment when they first touch the site. This often means enriching what is known about each visitor, perhaps using third-party data from advertising efforts, or registered data for people who are visiting the site again.

Rules for rules-based personalization often include three components:

  1. The audience the rule applies to. 
  2. The content or experience they’re going to see on the site. 
  3. The page or pages and context the rule applies to. 

Marketers can think about these logically as ‘Show this content to these people at these times under these conditions.’ 

Upside of rules-based personalization

  • Marketers can drive meaningfully higher conversion rates by showing each audience segment the right content and experiences. 

Potential downsides to rules-based personalization

  • Marketers can fall down a rabbit hole with rules, creating a practically endless number for each individual sub-segment or account. 
  • Rules won’t accommodate changes in audience segments and behaviors until the marketer updates them.
  • Lack of testing behind the rules makes it unclear if the optimal rules have been created.
  • Marketing usually calls upon engineering to help implement the tests, and requires design time to create the creative. As such, marketers become the bottleneck, needing the time to create, test, monitor and update a host of rules. 


Predictive personalization

Predictive personalization is a more advanced approach than rules-based personalization. This form of personalization uses some system – often machine learning – to automatically decide what to show each site visitor as they show up on mobile and desktop websites. 

Rather than use fixed rules like rules-based personalization, predictive personalization watches visitor behaviors and decides which variation to show each visitor. The system automatically figures out which creative to show to whom, and gives more traffic to the creative that performs well while “starving” traffic from the ones that perform poorly. 

Like A/B testing, multivariate testing, and rules-based personalization, predictive personalization begins with marketers understanding site visitors, thinking through strategy, and coming up with ideas. Then marketers launch creative they think will help convert site visitors. 

However, unlike rules-based personalization, predictive personalization frees marketers to focus more time on strategy ideation and creative development. Marketers can think of it as system-learned, rules-based personalization because they don’t need to come up with all the rules in advance. The system automatically allocates and reallocates traffic based on what actually works best, effectively putting marketers’ ideas on autopilot. 

With predictive personalization, marketers can

  • Specify segments in advance with a set of rules, or have the system do it
  • Set the system to look at all possible combinations of data to describe an individual visitor 
  • Run many, if not all, ideas at once. It’s akin to a massive multivariate test or running numerous A/B tests simultaneously

In addition, a predictive personalization system should keep learning. Because it’s deciding the traffic allocation, it should be able to adjust to changes in audience, the market, products, promotions, and visitor behavior over time. By learning and adapting, predictive personalization helps ensure marketers harness every opportunity to drive meaningful, valuable experiences for each site visitor – increasing the likelihood of conversion.

Upsides to predictive personalization 

  • Rather than spend time managing large sets of rules, marketers can easily personalize their sites for each visitor, showing whatever is most likely to get them to convert. 
  • Even with many rules, marketers can usually only address a handful of segments through rules-based personalization, while predictive personalization unlocks the ability to personalize for individual site visitors. 
  • Marketers can react to (inevitable) changes in visitor behavior automatically. 

Potential downsides to predictive personalization

  • Marketers must spend time understanding their prospects, and developing creative ideas to engage them. The machine needs more personalization ideas available to discover combinations that deliver the largest gains.  
  • Several versions of the website are active at one time. For those in regulated industries where marketing and marketing pitches are regulated, this may not be accepted. This can be allayed by ensuring legal approves all possible combinations developed by marketing.


The Essential Building Blocks of Web Content Personalization

 No matter which approach marketers take to enable personalization, the following steps are foundational:

  1. Know the audience and segments (such as by industry, geography, age cohorts, gender, company size, existing technologies)
  2. Understand pain points by audience/segment
  3. Map audiences to solutions by identifying the intersection between pain points and value prop
  4. Determine how to differentiate for each segment/cohort to develop messages and offers that resonate and drive action
  5. Build web pages for each audience and determine rules for serving content
  6. Deliver relevant content to the right audience at the right time by identifying the site visitor (e.g., by sending emails to contacts within a certain industry, by deducing on website through reverse IP lookup, using third-party data enrichment, based on behavioral data)
  7. Monitor and analyze performance of personalized content compared to global web experience
  8. Combine personalization with A/B testing to fine-tune the approach and impact


Predictive Personalization Delivers Better, Faster Results

Intellimize uses predictive personalization to replace static, low-converting websites with high-conversion pages. The Intellimize platform delivers a new kind of experience, where visitors get a bespoke, optimized page in the moment driven by a marketer’s best, most creative ideas and almost always without the need to code.

Calling upon machine learning, Intellimize delivers a uniquely crafted web page to each and every visitor, assembled from the dozens or hundreds of variations envisioned by insightful marketers. Using powerful algorithms, Intellimize’s predictive personalization selects each specific element of content based on all of the available known data – including the user’s behavior. 

Then Intellimize beautifully presents the best version of the website to each visitor, delivering a world-class experience for them – and game-changing results for the marketer and their company in the form of high conversion rates.


Predictive Personalization in Action

With Intellimize’s predictive personalization, you can transform your website into a conversion machine that drives results 25x faster than traditional A/B testing. Check out these case studies explaining how Intellimize has worked for other marketers:

“Intellimize massively accelerated our website conversion optimization, enabling my team to optimize across 15M+ versions of our website in parallel. Through a joint continuous testing approach, we drove 24% more marketing qualified leads across our site and 87% more pricing page leads in two months. It would’ve taken my team decades to run these tests using traditional methods. Intellimize enabled us to optimize our website experience for each unique prospect at the moment.” 

Udi Ledergor, CMO of B2B technology leader Gong

“Intellimize married the best of marketing’s creative thinking with machine learning to deliver 1,500 more leads in the last 90 days, and the pace of improvement is accelerating. Their Continuous Conversion platform also delivered machine learned insights about user behavior, leading to more creative ideas to test. By turning a static website into a Learning Website, Intellimize has been a great partner and enabler to the marketing team.” 

Ryan Carlson, former CMO at Okta now working on a new special project at Okta

To see Intellimize for yourself, request a demo here.

Website Personalization

For much of the internet’s existence, a website was simply an online marketing and sales brochure designed to relay generic information about a company and what it sells. Thanks to technology advances such as reverse-IP data enrichment and firmographic enhancements, website personalization is now possible, and in fact a staple in differentiation against competition.

Website personalization means serving content specific to the visitor. The website experience becomes an experience that is defined by the visitor’s demographic, location, or profile that is built over a period of time and interaction.


The Importance of Website Personalization 

There is general consensus among marketers that website personalization drives higher conversion rates and more revenue. If these two benefits aren’t compelling enough, McKinsey analysts estimate that personalization stands to create $1.7 to $3 trillion in new value for companies. It stands to reason that companies that do not personalize their website experience will lag behind the leaders 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, the misconceptions on getting started suggest a difficult planning and implementation effort. In reality, it’s best to keep it simple out of the gates. Here are a few things to consider as you examine website personalization as an option.

  1. It doesn’t have to take a long time to get started. We recommend you start by identifying three elements of a landing page or homepage to personalize (ones that you believe will have an impact) and test three different versions of each element at the same time. This allows you to get up and running quickly and helps you identify which personalizations are having the biggest impact on performance. 
  2. You do not need first-party data to start website personalization. First party data can almost always help improve performance, but it’s not required. Contextual data such as geography, device type, time of day, first visit/repeat visit, day of week, and device type is available on every visit to your site. It’s easy to overlook the value of this contextual data because it seems so basic on the surface; however it’s common for these attributes to enable double digit lift for marketers.
  3. Website personalization will not create messaging inconsistency. Personalizing your site experience enables you to engage each of your customers in ways that are relevant to them individually. Each potential customer has different questions and considerations in their mind before making a conversion decision. Website personalization enables you to take a consistent message and focus on the aspects of that message that are more impactful to each individual visitor. 

Importantly, there are some fundamental differences between rules-based personalization, which relies on marketers to create segment-specific definitions for each personalization, and machine-learning based personalization that leverages the power of AI to deliver unique experiences personalized to every single visitor. These are two important considerations for any marketer that is evaluating a machine-learning based approach:

  1. Your audience segments do not have to be predefined. Personalization through machine learning does not require you to predefine segments, unless you want to. Unlike rules-based personalization, AI-driven personalization automatically discovers segments by observing how your ideas perform for different audiences. 
  2. You do not need technical and engineering expertise to start website personalization. Building your own personalization engine in-house is resource intensive and requires specialized expertise. Integrating your internal systems and programming machine learning algorithms can be time consuming.

Because of the incredibly high technical bar in creating AI-driven personalization systems, until now, this approach has only been possible for some of the largest and most familiar technology companies in the world, like Google, Amazon, Microsoft and others. The good news is that Intellimize is now bringing the power of advanced personalization technology to marketers at scale.  Today, conversion obsessed 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 can be as simple as providing the creative ideas that will be unique to each audience or segment..

With these aspects of website personalization in mind it’s time to get started and that means exploring data. Data is the fuel that powers personalization.


Getting Started with Website Personalization

With some of the misconceptions of website personalization behind us, it’s time to start thinking about implementation and that starts with data. How do marketers use data in their efforts? We’ve culled some best practices thanks to working relationships with a host of organizations across a number of industries. Here are 5 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. To most marketers’ surprise, high performing segments are often there to be found in 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 paid media data. If you are using paid media campaigns to drive traffic to your site, you can use UTM parameters to pass the targeting information to further enhance personalization. Data such as the creative content, keywords, and the referring site can be quite useful in creating a seamless experience across your paid media and your web site.
  3. Use first party customer data to personalize on lifecycle. Your most valuable customers expect to be treated differently than a first-time visitor to your site. Recognizing these customers with special, limited offers and unique offerings reinforces their special relationship and can increase conversions and loyalty. For first-time customers, providing incentives for a trial makes sense, and testing several versions makes sense as well. Additionally, first party data can be used beyond the lifecycle as well.
  4. Leverage third party data for better relevancy. Third party data can be particularly valuable when used to create relevancy for visitors to your site. There are many data providers offering a wide variety of consumer and B2B data. 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. Predictive Personalization can deliver! Given the rich set of data and number of potential segments based on the data above, using an AI based tool is particularly valuable at automating segment discovery and simultaneously learning which variations perform best for each segment. And it will save you an immense amount of time!


AI and Machine Learning for Website Personalization

As we’ve pointed out above, website personalization doesn’t have to be a daunting ordeal. Gone are the long, arduous and lengthy A/B testing protocols that many marketers have relied on to date. With AI and machine learning technologies now available, website personalization can truly take hold.

Much of the work of conversion rate optimization is in managing experiments; design, setup, implementation, analysis, and application of learnings. This work is important, but also sometimes administrative and repetitive. Predictive personalization automates the rote tasks involved in website testing, automatically applying learnings and freeing up marketers to focus more energy on generating new ideas.

Automation does more than take the mechanical work off of marketers’ collective plates. In some cases, automation is able to do those jobs to a degree no marketer ever would. Where teams using A/B testing are typically able to test a few ideas at a time, predictive personalization allows teams to test dozens of ideas over a comparable period. In fact, in our first year, our average customer tested 25 times what they could have achieved using A/B testing. 


Website Personalization Resources (Blogs and Videos)

VentureBeat: Intellimize Raises $30M to Optimize Websites with AI

Kyle Wiggers shares highlights on the latest round of funding for Intellimize and speaks with Guy Yalif, CEO of Intellimize, in this article from VentureBeat.

“Our goal is to help more marketers deliver more revenue, more customers, and more leads to sales,” Yalif told VentureBeat. “We will help more conversion-obsessed marketers dynamically adjust their websites to each unique visitor’s changing behavior over time.”

“One-size-fits-all websites are the biggest squandered opportunity in all of marketing for all industries … Intelligent website optimization is essential tech to the modern marketing stack, and our investors share this sentiment,” he continued.

“[Over the past year,] we’ve been busy helping marketers create high converting websites by combining their ideas with our machine learning,” Yalif added. “We’ve become especially popular with business-to-business brands along with ecommerce. For example, we helped Snowflake generate 49% more leads with their website, while Sumo Logic accelerated decades of traditional testing and optimized across more than 1 billion versions of their site.”


What is A/B Testing?

A/B Testing


A/B testing is a statistical methodology of comparing different versions of something to see which version performs better. While A/B testing is a scientific approach to problem solving that has been in use for nearly a century, the technique was first adopted by marketers as early as the 1960’s in direct marketing campaigns. But with the rise of the digital era, A/B testing has surged in popularity, partly because launching and analyzing experiments in the online world is relatively easy.

In the context of digital marketing, conversion-obsessed marketers will test different versions of webpages, email headlines, landing pages, ad copy and other user-facing online content to determine which performs better. There are many webpage components that can be tested for performance, including page layout, menu location, headlines, CTAs, images, fonts, colors, image sizes… the list is nearly endless. Results and conversions can differ significantly depending on the combination of elements and the audience. 


Why A/B Test?


A/B testing provides a definitive, data-driven approach to determining which version of online content performs better, that is both statistically valid and scientifically sound. In short, A/B testing takes the guesswork out of marketing, replacing subjective decision making with an objective framework for determining winners and losers.

Because the guesswork has been reduced or eliminated, marketers and business managers can consistently improve the results and efficiency of their marketing efforts, or business operations, over time by employing a systematic approach to A/B testing. Often the result of ongoing A/B testing and experimentation is a dramatic improvement in marketing effectiveness and advertising ROI, and sometimes is the difference between the success and failure of a marketing campaign or even a business.

There are many A/B testing tools and software solutions today that can help with launching a successful program of experimentation. These testing tools can help marketers sift through the myriad of attributes, data, and options that can otherwise make A/B testing difficult or cumbersome. Their cost and complexity can vary tremendously depending on the size of your website and your firm’s needs.

In addition to learning and understanding the tools available for proper A/B testing, you’ll also need to have a solid understanding of the statistical principles that underpin all of A/B testing. Without a foundational understanding of how to statistically interpret results, you’ll likely encounter errors and make unreliable decisions. Let’s break down the three most important statistical terms you’ll become acquainted with along the way:

  • Mean – The mean (or average) is a measure for determining how each variable we test results in something. You’ll want to tabulate the mean click rate or conversion rate depending on what you’re testing.
  • Variance – The variance is used to determine the variability of the data being measured. If the variance is low, the more accurate the mean will be. Likewise, if there’s a large variance in what you’re testing, the confidence interval of the sample mean will be larger and less accurate as a measure.
  • Sampling – In order for the data to be statistically meaningful, there needs to be a large enough sample size. If we test only a handful of interactions with a particular website test, the sampling might not be large enough to have significance.

Determining the statistical significance of an A/B test is critical, because it is the statistical validity that gives A/B testing its prescriptive power. Without statistically significant results, marketers are at risk of making either Type I (false positive) or Type II (false negative) errors and misinterpreting the results of their tests. 


A/B Testing Challenges on Your Website


While A/B testing can play an integral and even essential role in driving marketing results, it is important to acknowledge the inherent challenges of A/B testing, especially for websites, that have led marketers to adopt more advanced ways of intelligently optimizing their website content.

  • A/B testing takes too long. With A/B testing, you test one variation at a time. Testing more than one at a time can confound the results of both experiments, undermining the statistical significance and defeating the point of the controlled experiment. And, depending on the amount of traffic your website gets, the results can take time – weeks, perhaps months, and far too often, a clear winner is never identified. In a business environment that often demands results this week, A/B testing can sometimes fall by the wayside.
  • A/B testing ignores smaller segments. A/B testing doesn’t take into consideration each unique visitor, but rather groups visitors into large randomly assigned segments. If one variation outperforms another 60% to 40% (as an example) the winning variation may be more effective for a majority of your website visitors, but there may still be a segment in your overall population that would respond better to the losing variation. In A/B testing, no allowance is made for serving different variations to different segments over time, instead a winning variation is chosen and served to all future web visitors.
  • A/B testing takes a lot of work. A/B testing requires marketers to closely monitor metrics, measure improvements, and update the website with new testing variations. This often requires the resources of web developers, programmers, graphic designers, possibly legal and regulatory approval groups within an organization to make site changes. 
  • A/B testing misses opportunities. An A/B test gathers data by serving one variation that will (hopefully) win and one version that will (presumably) lose to 50% of your selected website traffic users each. While the experiment is gathering data, your website is missing out on conversions from the half of your audience that is viewing the future losing variation.  Over time, these missed opportunities will add up. And while A/B testing is better than not testing, A/B testing lacks the efficiency that is delivered by today’s machine learning and artificial intelligence solutions.
  • Statistical Complexity. Without a deep understanding of statistical principles, marketers can often come to false conclusions by mis-interpreting the results of an A/B test. Ensuring experimental validity, reaching statistical significance and analyzing statistical confidence & power can be a high bar that trips up even the most experienced conversion optimizers.


Introducing Continuous Conversion™


Intellimize is pioneering new advancements in the industry by introducing Continuous Conversion™, a machine learning optimization approach that outperforms A/B testing. While A/B testing is cumbersome and slow, Continuous Conversion™ is fast and efficient, delivering head-turning results in days not weeks.

Intellimize uses machine learning to optimize the individual steps of each buyer’s unique journey in real time and automatically adjusts web content in response to changes in the buyer behavior over time, delivering better conversion results as much as 25x faster, empowering marketers to test more ideas, faster.


The Results of Continuous Conversion™


Intelligent website optimization can help improve lift and conversions for websites across a host of industries. Here are some use cases of how machine learning can power your website performance improvements.

  • B2B – See how Snowflake drove a 49% uplift in meetings booked using Continuous Conversion™ for their website. 
  • B2C eCommerce – See how Stella & Dot achieved a 52% increase in shopping cart conversions by testing 400 combinations of their checkout page in just a few months.


Recommended Resources – Intelligent Website Automation vs. AB Testing


Here are recommended resources on how and why Intelligent Website Automation outperforms A/B testing.


What is Conversion Rate Optimization (CRO)?

Conversion Rate Optimization (CRO)


In the context of digital marketing, conversion rate optimization – CRO – is the process of increasing the percentage of web site visitors that take a desired action or conversion goal. That desired action could be a purchase, a free trial sign up, a demo request, a content download, or even just spending more time on a specific page. Because online audiences (and marketing spending) can be so large, relatively small improvements in conversion rates can sometimes produce significant impacts on business performance and financial outcomes. In fact, CRO can be one of the highest ROI activities in a marketer’s toolkit and can dramatically impact successful customer acquisition through refinements in the conversion funnel.

While website conversion rate optimization relies heavily on analytics and statistical approaches to decision making, CRO is fundamentally about consumer insight and understanding prospective buyers – something that creative marketers are uniquely positioned and qualified to do. Conversion-obsessed marketers use an array of tools – web analytics, heatmaps, session recordings, surveys, user experience testing & customer interviews – to understand how and why consumers behave in the ways that they do.

Using this research, optimization experts develop a list of hypotheses on what may cause web users to change their behavior and complete the conversion goal more often. Then, borrowing from the tradition of scientific research, marketers test each hypothesis in a statistical A/B test using A/B testing software to randomly deliver different versions of a web page to individual users while measuring the results. Soon the level of complexity rose and marketers were embracing multivariate testing, which involved multiple iterations of several different content variations in a single experiment. Eventually marketers would also target specific content to unique, identifiable audience segments through a technique called “Personalization.” But all of these different approaches were focused on refining the conversion funnel and delivering more value for the traffic on a company’s website.

By methodically testing each hypothesis and incorporating winning iterations into the overall web design, a website’s conversion rate will rise over time, increasing the value of the website traffic for the business.

The Importance of Conversion Rate Optimization


Marketers today invest a tremendous amount of money and resources into driving traffic to their websites. By making sometimes minor changes to their landing page, marketers can improve conversion rates and the revenue that flows from those additional conversions, resulting in greater returns on the initial marketing investments.

Companies with high converting website conversion rates stand at a competitive advantage to their competitors with lower conversion rates. Because the firm is able to produce a more profitable return on their marketing investments, the company is then able to reinvest more of those profits back into customer acquisition, producing even more returns and a virtuous cycle of growth continues. This is especially true in cases where paid advertising is a main driver of website traffic and improving efficiency is an imperative.

One point to note, conversions are the lifeblood of any online business, though how they are defined and measured differ from industry to industry. An online ecommerce site might define a conversion as an order or sale. A B2B technology company might define a conversion as a form fill for a white paper download which generates a sales lead. While the process in each of these industries is different, the importance of generating conversions is the same.

The Building Blocks of Successful CRO – What to Test


In a recent research from Forrester and SiriusDecisions, they define three key patterns that digital marketers must follow for website and conversion rate optimization success in today’s online environment. 

  1. Attract – marketers must capture and direct the user’s attention. Evaluate the content on your own site by type:
      • Visuals – imagery, color, overall design, and emotional resonance. How these visual components are presented to the site visitor can determine whether they leave or convert.
      • Copy – headlines and body copy that connect the site visitor to your value proposition. Refining your story is critical to earning your next customer.
      • Calls to Action – a cta button, banners, links, and other similar calls to action move the user through the intended customer journey. How you choose and frame an offer can make all the difference between success and failure.
      • Usability and User Experience – unifying the previous elements in an experience that is pleasant for the site visitor helps improve the website.
  2. Engage – your website, as an important representation of your company or brand, must build trust with your audience. By aligning content to a user’s intent or goal for visiting a website, smart marketers build credibility. This helps facilitate future visits, purchase decisions, and long-term loyalty. The components that are put to work here include:
    • Navigation – site visitors can move throughout the site content smoothly with clear navigation that facilitates this process.
    • In-depth Content – site content should demonstrate expertise relative to the company’s value proposition.  It should also be consumable in different formats – such as text, video, etc. – and speak to visitors at various stages of the buying process.
    • Personalization – those sites that speak to the unique needs or pain points of the website visitor will resonate more with prospects and potential customers.

  3. Convert – While there’s a lot that goes into a quality conversion, building a deep understanding of consumers and what motivates them is critical. Psychological approaches, such as social proof, expertise & authority, also play an important role in the CRO strategy.
    • Offering Alignment – aligning the user experience with the site, product, or sales offering is critical. Content delivered along a “buyer’s journey” is an example of offering alignment.
    • Decision Justification – leverage confirmation bias and micro-conversions as steps toward a larger goal. 
    • Paths to Conversion – Some people convert faster than others and thus need a different route to conversion. Explore content formats and purchase paths customized to industry or persona.


Traditional A/B Testing – Is there Time to Manage the Complexity?


In the early days of digital marketing, A/B testing emerged as a winning solution to provide a definitive answer to a simple question – this one or that one? The statistical and scientific rigor of the process reinforced the credibility of data-driven decision making, and online content was forever changed for the better. Testing one landing page iteration against another landing page iteration was and is the foundation of conversion rate optimization today.

However, A/B testing software soon emerged to simplify the work of tracking experiments, measuring performance, and testing statistical significance, leading to a second revolution on the timeline of conversion rate optimization. For a new generation of digital marketers, it was now possible (and easy) to create variations, launch an experiment and report on the results.

But the complexity of managing an online optimization program has grown exponentially as the internet has grown and as the way we experience online content has evolved. Today, growth and experimentation-focused marketers must be cognizant not only of sample sizes and confidence intervals, but also multivariate experimentation, bayesian vs. frequentist approaches, cohort performance, test velocity, win rate, and experimental capacity. All while optimizing over dozens, if not hundreds, of pages & products, ensuring that no one experiment confounds the results of another and tracking the results of each one.

It is in part due to this complexity that A/B testing has struggled to reach widespread adoption in the industry, though A/B testing software is widely available and even free now. While some firms have embraced the mantra of experimentation, other conversion optimization managers note challenges like organizational alignment, conflicts with experimental mindset and time to impact.

Despite these challenges, industry titans, like Amazon, Google, Facebook, and others, highlight experimentation and optimization as foundational elements not only of their online experience but also of their competitive strategy.

With the rise of new technologies, like machine learning & AI, teams from the world’s leading companies have developed a new suite of tools to address the challenges of website optimization, leading to a third revolution in the timeline of website optimization – and turning skeptics into believers with some head turning results.


Intelligent Website Optimization Delivers Faster Results


The third revolution in conversion optimization is now available to the world’s most conversion-obsessed marketers. Intellimize has introduced artificial intelligence and machine learning into the conversion optimization dynamic, outperforming traditional A/B testing and personalization, and delivering better results, faster. 

Intellimize uses machine learning to deliver a uniquely crafted web page to each and every visitor, assembled from the dozens or hundreds of variations envisioned by insightful marketers. Using powerful algorithms, Intellimize selects each specific element of content based on all of the available known data – including the user’s behavior. 

Then Intellimize beautifully presents the best version of your website to each visitor, delivering a world-class experience for them – and game changing results for you.


Intellimize CRO in Action


Conversion rate optimization can make or break a website’s, and even a company’s, success. With Intellimize’s intelligent website optimization, you can transform your website into a conversion machine that drives results 25X faster than traditional A/B testing. Here are some case studies on how Intellimize has worked for other marketers:

  • B2B – See how Drift tried out 25,000 different variations of one of their landing pages, and ended up seeing a 322% improvement, driving higher-quality leads and more sales. 
  • B2C eCommerce – See how Dermalogica leveraged Intellimize to test over 450 variations on their website, increase revenue, and grow their business across 6 global markets.

Recommended Resources – Conversion Rate Optimization (CRO)


Here are some additional resources on how you can elevate your CRO efforts: