B2B Web Personalization Maturity Curve

Every B2B marketer in the world dreams of a state where every single touchpoint with a prospect or customer of your business is personalized.

But, what does it actually mean to be personalized?

My take on being personalized: content is relevant to the viewer. With that you, as the marketer, strives to provide value to that viewer about your business.

Value could take the form of education, a different perspective, or simply a spark of joy/emotion. You can measure the value you have delivered by means of engagement and action, such as a click and scroll.

In this post, let’s talk about the common phases or approaches that B2B companies are taking on the topic of web personalization.

B2B Web Personalization

If you have read my previous blog post, What is B2B Web Personalization, you may know that B2B web personalization centers on 3 elements:

  • Identification – the attributes to be used to identify that person
  • Content – the content that may be relevant to the person, including location of that content being shown
  • Algorithm – the logic behind the relationship between identification and content for the personalization

If you want to get an overview of B2B web personalization, read that blog post!

B2B Web Personalization Maturity

If that is B2B web personalization at a high-level, I would describe the B2B web personalization maturity journey as occurring in three phases.

1. Rules-Based Personalization with Reverse-IP Look-up

Personalization in this form is what most A/B testing platforms – Optimizely, Google Optimize and VWO – focus on.

These platforms act as a service layer between the three elements.

They take an identification attribute and read it via integration with a reverse-IP provider (e.g, Clearbit, Demandbase, 6sense) to surface the content.

The logic between the identification and content is rule-based and it’s often a 1-to-1 relationship.

For example, if site visitor is from the financial industry, show this image.

This type of personalization is table stakes at most mature marketing organizations, particular in B2B SaaS.

A/B testing (or experimental culture more generally) is something that every organization is driving for, especially where top-of-funnel volume and/or customer LTVs are high.

2. Dynamic or AI-Based Personalization

The core difference between the first and second phase is the personalization algorithm.

Instead of a if-this-then-that static rule, in the second phase there is a dynamic or AI-based algorithm (i.e, the personalization algorithm) that determines the content to optimize conversion based on the identification attributes.

With that, we see an increase in the number of inputs required in this second phase:

  1. Available identification attributes
    • [Individual] Behavioral – the activities that browser has done on your business web properties (e.g, page-view, IP-location)
    • [Account] Firmographic – the account information of that IP address (e.g, company industry, company revenue band)
  2. Available content

Both of these inputs are essential to determine which content is the best based on a single or multiple of identification attributes.

Having said that, the collection or aggregation of these two inputs could still be a rather manual effort into the personalization platform.

3. Full Scale Personalization – Customer 360 view

The last phase is built on top of phase 2, further leveraging the AI-based personalization algorithm with data.

The core differentiator in phase 3 is that the number and accuracy of inputs have exponentially increased, because of additional 1st party data (e.g, form fill provided by customers).

The available identification attributes now becomes:

  • [Individual] Behavioral – the activities that the browser has done on your business web properties plus activities within your products or free trial environments
  • NEW [Individual] Demographic – the static attributes of that individual once known (e.g, name, title)
  • [Account] Firmographic – the account information of that IP address plus what the individual provided.

With the massive amount of data becomes available, the business requires additional technology to organize the data.

Using the technology to blend and group the data attributes will be able to form identification segments.

If I use Amazon as an example: You (e.g., a 50 year old female in NYC) browsed product X, you are likely to put into a segment of “Interested in X”. And you can be in multiple segments at any given time.

On the other hand, the content algorithm organizes the available content and how they relate to other content.

Continuing the Amazon example, you will be shown product X in location B because you are in the segment of “Interested X”.

With the content algorithm, you might have a % of chances that you will be interested in product W and Y, in a similar lookalike audience.

To tie it all together, the personalization algorithm may also show product W and Y in location A and C.


Web personalization is a journey on which most B2B SaaS companies are currently embarked.

Although companies may be at a different points of the journey, the challenges and milestones are very similar depending on the volume of web traffic and relationships between website/product and go-to-market motions.

If you are interested to know more about my thoughts, add me on Linkedin!

What is B2B Web Personalization?

In addition to conversational marketing, personalization is part of my responsibilities at Okta, and I have thought about it quite a lot. This post gives you an overview of B2B personalization and some of my own thoughts.

What is Personalization?

Personalization is a marketing tactic to show relevant information to the site visitor with a goal to improve the conversion rate.

The technology behind it is based on cookies or sometimes the localStorage on the browser. (You can read more about the difference between the two here).

And the principle is largely the same – if the website knows you have attribute X, then the website will show you Y.

Origin of Personalization

Personalization began as a B2C use case in big technology companies like AOL and Yahoo, where the money-maker was their homepage which generated tens, if not hundreds of millions of views each day.

A very small percentage lift in engagement, or another page view, meant big money for them.

That is where personalization shows content that will be statistically more likely to generate interactions on the website.

More interactions mean more eyeballs; that means more opportunities for advertisers to show their ads to users, and more money for the website.

Amazon, for example, is able to predict what you want to buy based on your purchase and browsing history.

A webinar with VWO sharing my personalization journey at Okta (slides and recording)

General Requirement of Personalization

In general, there are three elements required in order to perform personalization

  • Identification, normally a browser cookie which is used to identify the individual site visitor.
    • For example, device type, or a common use case is you clicked from an email, the site can read which email you came from and personalize based on that.
    • The identification can also be based on IP address. And IP addresses could be attributed to a company with reverse-IP technologies. For example, 111.22.333.1 can be a company IP address of Apple.
  • Content that is relevant to the site visitor, based on the information identified. This includes the location of the content, for example, a block or an image container.
  • Algorithm or logic that decides what content to show, this could either be determined by a human or machine

B2B Web Personalization

Although there are many applications of personalization, let’s dive deeper into B2B Web Personalization.

To reiterate, the goal of B2B personalization is to generate statistical improvement in conversion rate.

Personalization is proven in A/B testing across industries, so the higher your site traffic volume, the higher impact.

In addition to the key difference in site traffic volume, B2B personalization is often based on IP address at a company level, rather than individual level. With that, you normally personalize based on location, industry, company size and revenue.

Therefore, it is not a tactic for an early-stage startup.

I would recommend it as a tactic worth investing in only once your website generates sessions in the 6-7 figure range each month.

Categories of Technologies

Instead of using engineering time to build the four elements of personalization, there are a number of technologies available in the market to make personalization easy to implement.


Software like Demandbase Engagement and Clearbit Reveal allows companies to uncover company attributes such as industry and company size with reverse IP lookup.

It is more complicated, but not impossible, to identify 1st party attributes (like values in your company Salesforce) or individual attributes because of

  1. Privacy concerns
  2. Complexity of data

Companies could achieve this either through dedicated engineering effort or leveraging a customer data platform such as Segment or LiveRamp.

This solves #1 Cookie element in the above requirement of B2B personalization.

Attributes that could be identified for personalization


The personalization platform solves #2 Location, #3 Content and #4 Algorithm elements of personalization, and it should integrate with the attribute identifier.

Examples are VWO, Google Optimize, Optimizely and many others.

Use Cases of B2B Personalization

The application of B2B personalization is not complicated, if the goal of the personalization is the CTR, you will need to measure that religiously.

Step-by-step Guide

  1. Identify the content that you want to personalize – normally it would be an image, text and/or links.
  2. Create the personalized content you will use to replace the default content.
  3. Configure the attributes in your personalization platform.
  4. Change the content from step 2 within the personalization platform.

Once you have the time and resources to cover basic personalization with if-this-then-that logic on your website, which are likely the homepage and product/solutions pages.

The next question then becomes what’s next?

Future of B2B Personalization

As the technologies improve, the biggest improvement are likely on #1 Cookie (or any way to identify really) and #4 the algorithm.

  • First being to identify more attributes more accurately, with a cookie or not.
  • Second, instead of if-this-then-that logic, it will be AI or machine learning-based, optimizing for the goal that you defined from any attributes.

Obviously, the technology set will become more accessible and become more like a commodity for B2B companies.

The leg work of importing content to a platform and identifying what personalized content is available for the business may not make that much of an improvement.

Final Thought

Personalization works.

I would recommend starting A/B testing first to prove results, before investing more resources in website personalization.

Personalization is a journey for any B2B marketing organization and it is never too late.