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How B2B Marketers Can Use Data for Deeper Personalization

What we B2B marketers lack for in volume, we make up in our depth of data. Here’s how to use your data to its full potential.

This is a guest post by Ed Hull, Growth @ Hull.

When it comes to web personalization, I’m incredibly jealous of my B2C peers.

From e-Commerce, marketplaces, and even politics, B2C has the volume to run with incredible test velocity and web personalization.

But us B2B marketers don’t have that volume and velocity. Few of us have millions & bajillions of users to experiment with. But what we lack for in volume of users, we make up in our depth of data. A typical Salesforce instance might have:

  • Job roles, titles & seniority
  • Industry & sector
  • Company size & revenue
  • Technologies
  • Location
  • Language
  • Social bios & followers
  • Websites

… and so on. How can we leverage this data for web personalization?

There is juicy data for B2B personalization beyond the browser

Web is the highest volume channel for most teams and has much higher engagement than other channels. All this creates a ton of behavioral data that can be tracked and traced. Most web personalization tools work by profiling your website visitors for this data, then assigning them into audiences and variations of the content.

But it isn’t the only data. In fact, it just scratches the surface.

With your other channels — email, live chat, sales — you are able to use far more lead and customer profile data to build segments and change content dynamically. With more and better data comes more and better possibilities for personalization.

But with B2B — where we have person & company level data — there is far more profile data to understand and personalize with. Not just the website visitors browser behavior (like visiting your blog or pricing page), but other data too like:

  • Visitors other known profile data (are they a subscriber? An existing lead?)
  • Visitors other behavior (are they opening & responding to email? Any live chat? Have they tried your product?)
  • The company’s profile data (Are they a good fit? Are they a lead? Customer? Competitor? Partner?)
  • Everyone one else’s profile & behavioral data who works at that company


Data TypeDataVariations Browser only

  • Visited many documentation pages this session
  • Time of day/day of week
  • Device type
  • Geography
  • UTM parameters
  • Show testimonial for developers
  • Special deals each week
  • Headline and UI variations focused on device
  • Regional headline, image and copy variations
  • CTAs and offers related to paid media campaigns

Browser + Profile data

  • Visited many documentation pages this session
  • Another person at the same company has visited the pricing page 3 times in the past 2 days
  • Existing opportunity in Salesforce
  • Five contacts from company engaged with email and live chat in the last 30 days
  • Has seen a demo
  • Healthcare industry
  • 200+ employees
  • Special offers for highly engaged visitors
  • Push high value prospects to engage directly with the sales team
  • Expedited order processes and and preferred offers for existing opportunities
  • Include copy and ideas covered in prior email and live chat in body copy.
  • Highlight case studies from healthcare industry
  • Highlight plans and messaging for SMBs

There’s a chasm between web and every other channel. Web has unmatched volume and behavioral data. Email, chat, sales, and everything else has the depth to the profiles. How can you break down these silo, unify these two sets of data, then power up your personalization everywhere? And why can’t we do this already?

Fear the flicker!

The first constraint is speed. Whilst you can sync data between tools in other channels over seconds or minutes, web personalization needs the data in almost real-time. None of the normal methods seem plausible unless you wire together APIs yourself. The team at Intellimize suggest you need the data back into the page and change the content in under 200 milliseconds from the initial HTTP request to avoid the dreaded page flicker

face screaming in fear

That’s slightly faster than a blink of the eye…

How B2B Marketers Can Use Data for Deeper Personalization

Ugh, flicker

So how do you integrate customer data in real-time?

First, understand customer data flows in loops.

There’s a loop between customer profiles and page variations with the customer.

If you signup to a product (creating a profile), I can use this profile and the signup event to trigger a welcome email. “Hello there! ”

I can then track the reactions (opens, clicks, unsubscribes…) back into a profile.

Same story for other channels. Your live chat tool and trigger messages and track reactions. You can add people to ad audiences and track their reactions with web analytics. And the same loop of customer data happens with web personalization too. It has just got to be really, really fast.

The challenge is how many loops are involved in getting your rich B2B data back into the page.

Browser behavior is the 1st degree data loop

Here’s what the data loop looks with just browser behavior. The “default” data that can be used.

You can see how it’s a simple request and your personalization tool can turn around the recommended variations immediately. But it’s separated from the rest of your customer data which sits in profiles in other tools.

Add an identifier (2nd degree data loop)

Identifiers are used to associate data with a person or a company. For instance, an email address for a person has a name, job title, location, and so on.

With B2C, it’s hard to identify someone accurately without their email address. There are few other stable identifiers.

But with B2B, you’re not limited to identifying people. You can identify companies too. Since IP addresses can be associated with office locations, you can identify companies that are visiting your website with reverse IP lookup tools. Now you can identify the companies that are on your website and engaging with your brand.

Whilst there are many reverse IP lookup providers, just a company name isn’t the most useful data for meaningful personalization. Similar to “Hi {firstname}!” email personalization, using your name within an otherwise generic message doesn’t add meaningful personalization.

A company name is also not a stable company-level identifier — most other sales and marketing tools use a domain for the main website.

This is why Clearbit Reveal is a popular reverse IP lookup tool. With extensive coverage, they return a company domain name together with 30+ data points about that company. This can be used pushed back into the browser to be used for web personalization right away.

This is good! But it’s still not your profile data.

Identifiers mean you can associate website visitors with profile data (3rd degree data loop)

By revealing the company domain name behind an IP address, you can now associate everything else you know about that company and your interactions so far:

  • Are they a customer? Competitor? Partner?
  • Are they already engaged in a sales cycle?
  • What data is in your CRM? Marketing automation? Email? Live chat? Backend database?
  • Have people from this company visited before? Any significant pages?

When you combine this data with your browser data you can deliver deeper 1:1 personalization.

But all this data lies siloed in different tools. Your CRM, marketing automation, backend, web analytics, and so on. With only 200ms to return all this data into the page (including reverse IP lookup), it isn’t possible to ping all these tools and get all the data back in time.

Customer data platforms unify your profile data and give you one source to request

Instead of requesting data from dozens of different tools, you can minimize the number of loops with a customer data platform. Customer data platforms create a unified customer profile from all your tools — you only need to query one place.

Reverse IP lookup can associate a website visitor with an company profile, fetch all existing company profile data, then push it into the browser to use for personalization all at once. Once you’ve identified your website visitor and you have an identifier to match profile data with (company domain name), you need only one data source to query for all your company profile data, so you can run data loops fast enough to leverage all your customer profile data.

Hull is a customer data platform for B2B SaaS startups. With a unified customer profile and unified account profile, you can capture all this data from your sales and marketing tools and databases, and push it into the webpage using Hull Browser and Fastlane for real-time processing.

You can and should use all your customer data for personalization

Especially in B2B. We don’t have the volume of B2C, but each customer we do have has such comparatively high value. Personalization across every channel is powerful.

The idea of personalization with tools and data is to replicate a 1:1 personal experience and relationship. But as B2B marketers, we have such a depth of data that we can drown in it.

It is near-impossible to manually test variations and decide experiments at scale. It’s not immediately clear or obvious what data points are key to maximizing conversions with our unique audiences.

This is why we notice more B2B teams investigating predictive personalization tools like Intellimize. Instead of choosing variations & traffic allocation manually in a tool like Optimizely, they create all the variations they want to test and let algorithms train themselves to maximize conversions by matching the right variations with the right website visitor.

For B2B, this is what enables rapid test velocity across a vast array of test ideas. Intellimize has enabled B2B teams to implement successful web personalization. One of their clients ran 105 test ideas over 4.5 billion page combinations in 3 months.

Web remains the biggest channel and marketing asset for most B2B SaaS companies. With reverse IP lookup services like Clearbit Reveal, customer data platforms like Hull, and predictive personalization tools like Intellimize, web personalization becomes a reality.

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