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One of the best ways to start thinking of a personalization strategy is to view your whole website as one form. Every time a visitor is doing anything on your site, they are giving you the data to make personalization on-site just as they would when filling out a form on a landing page or on a demo registration page.
When a visitor goes and reads an article on your blog titled “7 marketing hacks to boost conversion rates,” you know that the visitor is likely a marketer.
Then a week later when the same person returns and digests a case study of how Bonobos used your software — you’re given a key indicator that an individual customer is an e-commerce customer. When that same person returns and visit your pricing page, and then click the tab for a 50,000+ visitor count plan, you’re filled in with even more information. And you’re shown they are one step closer to converting.
Most marketers don’t think of this user behavior as a person filling out a form. They’d rather push you towards a signup page and have you fill out a long, obtrusive form to get started with your brand. Why?
Let’s consider the example above from Salesforce. I’m the buyer here — why am I being required to do the leg work for a Sales team and provide 8 form fields before seeing pricing or a demo?
And it’s not just Salesforce doing this, it’s commonplace across the industry. You’ll hear marketers say “how am I supposed to get accurate information without asking for it?”
Well, that’s a neat quality about personalization! It can help you collect data from your visitors, and then you can use that to make the on-site customer experience frictionless and more delightful.
Many marketers, including Guillaume Cabane, former VP of Growth at Drift, suggests using data from personalization and enrichment as a way to confirm information from a visitor — creating a frictionless signup for the visitor.
In the example video above, once a visitor types an email and hits tab, Javascript is fired, and email based data enrichment via a 3rd party is executed. That process is used to fill out other fields in the form. The visitor can then confirm that the info is correct, but they don’t have to take action and fill out any fields. It takes the burden off their shoulders, yet provides the same amount of information.
Since data isn’t always 100% accurate — even when it’s accurately tied to an IP or email — you can use this method to confirm that pre-filled info is correct.
In the last chapter, we talked about the 4 types of data types — demographic, firmographic, behavioral, and contextual. And sticking with that data for personalization framework, we’ll cover how you can collect data points from each type.
You collect demographic and firmographic data during any form field completion on your site: a signup flow submission, a demo registration, a live chat interaction, or a lead magnet download. Most of the data you’ll receive at those points is first-party data (sourced from your own site).
But during the funnel, when you collect an IP address or email — either at the point of engagement or signup — you are grabbing a touchpoint that will help you source third-party data via API from a vendor such as Clearbit or Datanyze.
To be successful with personalizing, you do need to have spots where you can collect these gateway demographic data points ( such as emails and IPs). Collecting these fields opens the doors to more data — and better data. If you don’t collect these two things already, short and simple, add them now.
And if you already do collect emails and IPs, kudos to you! With these collected items, you can start unlocking the potential keys to plethora of other information. You can hit an API call with an email or IP, and pull data into your personalization platform to create audiences buckets and start deploying personalization experiments.
Behavioral and contextual data is usually collected from a pixel installed on your website. When you use Segment, you install their pixel on your site’s pages and it’s able to sync a user’s contextual data (browser, device type, etc) to your data warehouse.
If you’re not currently using Segment or you haven’t established a protocol for storing visitor data yet — you need to send it to a place where it’s usable. Proof Experiences can initiate an Identify call that will allow to create audiences from behavioral and contextual data — then you can use it to personalize and send to your data integration tool.
To get started with personalization, you need to realize that you can’t go at this process alone. Even the best types of personalization software on the market require the utilization of data from a variety of other sources and companies.
Here are the tools you absolutely need to know and utilize as you begin your journey into making the Internet more human and personal for your visitors.
Segment provides data infrastructure that allows you to clean, collect, and control your customer data all in one place. It’s an essential tool for marketers wanting to personalize because it provides a single location to route all your data into and out of.
What exactly does that entail?
Let’s say a customer receives an email from Hubspot, then visits your site to sign up, and finally installs your tracking pixel on their website. These are all different events that get associated with a customer’s unique ID. Segment makes sure all of that data from those events lives in one central repository that is clean — giving your personalization software the data it needs to update a customer’s experience quickly and accurately.
While Segment is incredible at integrating your data, it isn’t a single source of truth — meaning it isn’t immediately up to date when you make a change in one of your data sources. Hull.io is the solution you need for this data clarity.
Their data platform allows you to react when a lead take an action (and subsequently changes a data point) and empower your sales & marketing teams to react to customers in real-time. This is how sales teams are able to quickly send you a personalized message in Drift when you take an action on some other channel or how a prospect’s lead score increases and fires an event in real-time.
Clearbit is a marketing data engine that you can call via API to find out more information about a prospect solely from an IP or email. It’s our go-to solution for enriching firmographic data on our visitors at Proof — and it’s quite powerful.
We send off to Clearbit an IP or an email, and they will send back 80 to 100 fields all about the person and their associated company. These include properties such as URL, Description, Industry, and more. It’s our most utilized 3rd party data tool.
FullContact is a data enrichment tool that we turn to whenever we need data around an individual (think demographic data). We send over an email address to the FullContact API, and they return information to us all about an individual. This helps populate data for personalizing titles, greetings, and other individual-specific properties on a page.
Many of the personalized experiences that we publish on our site require us to know about the tech stack of a business (i.e. what software they currently utilize) in order to recommend a product or position an offer in terms of what software they currently are using. Datanyze solves this issue by providing a look up of a company's tech stack. It’s also useful for enabling a sales team to directly cater outreach to a specific visitor.
For instance, on Drift’s site, they use this data to personalize their ChatBot to identify my company (Proof) while on-site. Plus, they call out the fact that we’re using a competitor — Intercom to make their messaging seem even more hyper-relevant.
Even more importantly for personalization, if we see that a prospect isn’t using a software tool, we can hide a module or replace it with something more relevant for a visitor.
More relevant content = more engagement, happier customers, and more revenue.
While utilizing external data (aka third-party data) is a great way to supplement your data collection on-site, there’s also the opportunity to directly ask users to provide data to you (first-party data) while they are reading your pages. Hotjar and the Proof Experiences surveying tool are two great tools to collect first-party data while visitors are on-site.
And if a visitor doesn’t want to give you info — there’s no harm! They can simply exit the popup and keep surfing your site.
Hotjar provides several products and services (such as heat mapping, visitor recordings, and surveying) to help websites understand their visitors. The tool most directly important for personalization is their Feedback poll — a feature that lets you target simple questions to specific visitors on your site. This feature can be used to collect 1st party data, and deploy more relevant & personal experiences.
The beauty of using Segment or other data integration tools is that you can use the platforms to send data nearly anywhere — from a CRM to your own servers. And when choosing a place to store your personalization data, this decision is imperative.
Most times, we see personalization data most successfully stored in a CRM (Salesforce, Hubspot, Marketo). By storing data in a CRM, you’re able to empower your sales team with data that you’ve collected through the personalization process. When an SDR logs into Salesforce to look at a Prospect’s account, they’ll also have access to the data you’ve populated in via your personalization campaigns.
They’ll have more data points to include in their outreach (such as Industry, Tech Stack, Location, and more). That enriched profile of a prospect improves the open rates for your rep, and increases the likelihood of closing an account. Not only are you providing your team with more leads — you’re also giving high quality leads.
Another value of storing personalization data in a CRM is that you can create automated campaigns to fire based on certain criteria. For instance, if a visitor was identified as a SaaS marketer in your personalization efforts — you’re able to automate a follow up tailored for that exact audience.
For instance, we could shoot a 3 part email drip focusing on:
A tracking plan is something that is integral to any successful implementation of personalization. Without a roadmap of what to record and where to record it, you can get lost.
It’s just like taking a road trip. Sure, you can drive with a destination in mind and figure out your route on the way. But you’re likely to get lost, make mistakes, and be a whole lot less efficient than if you followed a map.
With a tracking plan, you’re able to track and monitor (in a living and breathing format) every event that you deem necessary. A centralized plan can align marketing, product, and engineering — and makes it easy to summarize what events need to be added, why they are tracked, and where they go. It also gives a status update on the deployment of each event.
While we could go super in-depth in to this section of the guide, we think it’s easier to understand this concept by looking at an actual tracking plan. We’ve included an example of the tracking plan that we use internally to track our personalization experiments using Proof Experiences.
And if you’re in B2B SaaS, this article from Segment on tracking plans is definitely worth a read.
When building a company or investing in a new initiative at your business, there are two ways to approach the situation:
While for many tasks we do in B2B software such as deploying new features or putting up a landing page, route 1 is ideal. When it comes to data naming conventions, the opposite plays true.
You’ll thank us greatly later if you follow route 2 from the get-go. Why?
A company isn’t static and your data certainly isn’t static. Your data warehouse is only going to grow larger and larger as time goes by, and inconsistently named data will be a headache that will slow your team to a standstill. You’ll have fewer insights, and you’ll waste time trying to fix what would have been an easy accomplishment to standardize from the get-go.
While establishing a naming protocol might seem like overkill at the stage you’re at — please trust us and take a few hours to do this. It’ll provide the framework to grow over the near and far term. Plus, it’ll open the door to easy personalization in the future.
While for many tasks we do in B2B software such as deploying new features or putting up a landing page, route 1 is ideal. When it comes to data naming conventions, the opposite plays true.
You’ll thank us greatly later if you follow route 2 from the get-go. Why?
A company isn’t static and your data certainly isn’t static. Your data warehouse is only going to grow larger and larger as time goes by, and inconsistently named data will be a headache that will slow your team to a standstill. You’ll have fewer insights, and you’ll waste time trying to fix what would have been an easy accomplishment to standardize from the get-go.
While establishing a naming protocol might seem like overkill at the stage you’re at — please trust us and take a few hours to do this. It’ll provide the framework to grow over the near and far term. Plus, it’ll open the door to easy personalization in the future.
If you’re still not convinced, here are a few of the many other reasons you should establish a data naming convention before launching personalization on your site:
To establish a naming convention, you need to understand the 2 most common types of calls (Identify and Track) you’ll have your personalization platform make via API when personalizing your site.
Don’t get stressed with the Engineering lingo — we’ll make this data dive quick and easy.
The first type of call is an Identify call. This is the API call you’ll make immediately after a user registers, logs in, or updates information. It lets you record an identifier about a user (a user ID) and traits about the user.
The second type of call is a Track call. This is the API call you’ll make to track an Event a user takes on a site — Signing, Creating an Account, Starting a Trial, etc. Under an Event, you’ll track properties about a person.
When it comes to what naming convention to follow, you’ve got several choices. If this is all new to you — we recommend following Segment’s Object Action Framework. In the next section, we’ll talk about how to use this framework when referring to your on-site events.
Why is it important to name your data with a system? Because when you don’t properly name, things can get confusing really quickly.
The Object Action Framework is made up of two things. Can you guess?
That’s right! An object and an action.
An object is a piece of your website or application that your customers interact with frequently. If you’re an E-commerce company, some common objects you’d want to track include:
If you’re SaaS, some common objects you’d want to track include:
The object is essentially what is being manipulated by an action.
And an action is what your customer or visitor can do with the aforementioned object. So in our example using the object Account — the actions a visitor can take include Create or Update.
When you pull an object and an action together, you create an event.
It’s a two-part term that specifically identifies an action that a user does on some part of your site. And it’s a key item you’ll define your audience for personalization.
When it comes to capitalization, you need to approach the subject with the mindset of a high-school English teacher. Proper capitalization is key, and by not being consistent, it’ll be incredibly hard to track events in your data pipeline as your company grows.
Why does this matter?
To a database, casing is unique and naming is essential. For the event “account created” — you could refer to the same action with a wide array of event names that all essentially mean the same thing:
While all the terms above indicate the same action, searching through the data and remembering the intricacies in naming will surely slow you down.
So by using the Action Object framework, you control for order and proper word choice in your data naming. And by deciding on a consistent casing, you add another layer of order. It doesn’t matter what casing type you use, but you should decide on one that you’ll use globally (for events, properties, & traits).
Here are the 5 types of casing:
At Proof, we use Proper Case for events, and snake_case for properties & traits.
The method of casing you choose for your data is up to you — the important thing to take away from this guide is that consistency is key. We've already covered what is personalization, personalization trends, and the basics of personalization data.
In the next chapter, we’ll focus on the when and where of personalization — explaining actionable examples you can use to personalize your own site.
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