Customer Data Platforms: Everything You Need to Know

Customer Data Platforms: Everything You Need to Know

As marketers and salespeople, we often drool over data. The more we can learn about our customers, the better.

With in-depth data, we can personalize interactions with customers, market to them at the right times, create a more enjoyable experience, and overall, close more sales.

That’s no secret. However, capturing all of this data, organizing it in one place, and making use of that data has been a struggle using traditional tools such as web analytics, CRMs, and marketing automation.

You typically have to spend a lot of time somehow combining all of this data in order to get a complete picture of your customer. Even then, this process is limited and you can’t fully take advantage of this data to completely personalize your marketing campaigns.

This is where Customer Data Platforms come in and aim to fix this problem.

In this article, we’ll define Customer Data Platforms, the difference between them and traditional marketing tools, their benefits, and even a list a few Customer Data Platform options. Follow along:


What is a Customer Data Platform?

The Customer Data Platform Institute defines a Customer Data Platform (CDP) as the following:

“A Customer Data Platform is a marketer-managed system that creates a persistent, unified customer database that is accessible to other systems”.

But what does that really mean?

In layman’s terms, a CDP is basically a system that pulls together all the data you have on a customer in one place. This way, you can create a unified view of that customer and you can see every action they’ve taken since first interacting with your company.

Ideally, you would be able to discover:

  • When that person first visited your website
  • How many times they’ve visited a specific page on your website
  • When they opened one of your emails
  • When they clicked a link inside that email
  • How many times they opened your emails
  • Even information on mobile app sessions, social media comments, purchase orders, and chat history would be accessible

In essence, a Customer Data Platform aims to pull together data that once existed in multiple platforms (such as email marketing platforms, CRM, analytics, etc.) and makes all of that data available in one place.


Customer Data Platforms vs. CRM vs. Marketing Automation: How Are They Different?

You may be thinking, “Don’t CRM or email marketing platforms such as Hubspot and MailChimp already do this?”. Not exactly. Customer Data Platforms differ from these two traditional tools in a few ways:

1. CDPs Provide More Data & Deeper Insight

The data that CRMs and email marketing platforms offer is limited. CRMs typically offer basic information and allow you to store customer information such as addresses, emails, etc. Some may even track interactions such as email opens and live chat or email conversations.

The same goes for email marketing platforms such as MailChimp. These platforms will store a customer’s email and track email activity but they miss other key areas such as web activity, mobile app activity, and so on.

However, CDPs aim to combine all of this data into one place and try to capture a customer’s entire interaction with a company. A true CDP would have data on a customer’s chat history, email history, website visits, mobile app sessions, purchases, social media interactions, and anything else that would involve an interaction between them and your company.


2. A CDP Combines All of These Platforms into One System

Ideally, a true CDP will have all of these capabilities in one platform. From your CDP, you’ll be able to track web analytics, store customer data, send emails, run marketing automation, etc.


What Are the Benefits of Using a Customer Data Platform?

Having all of this data under one house can be huge. Instead of having data in a host of different places (such as email activity from MailChimp, chat interactions from Zendesk, web activity from Google Analytics, and purchase activity from say, Shopify), all of this data in stored in one place.

Benefits of using a CDP include:

1. Having a Single View of Your Customers

The most obvious reason to use a CDP is that you can get a “single view” of the customer. You can see their entire interaction with your company in one place, rather than trying to somehow manage and collect this data from multiple tools.


2. Being Able to Personalize Customer Interactions

Having all of this information in one place can allow you to personalize a customer’s entire experience with your company.

You can personalize names in emails, send out a coupon directly after a customer has visited a specific page on your website, enter them into a marketing automation process when they’ve had a chat with your company or send them an email when they logged onto your app.

The possibilities are really endless as to the type of personalized experiences you can craft for your customers. This all goes into to creating a stronger connection between you and them.


3. Being Able to Create Insanely Targeted Campaigns

With all of this information at your disposal, you can now create insanely-specific targeted campaigns.

Do you want to target customers who have visited your pricing page within the past month, have opened up and clicked in your last three emails, downloaded your mobile app and have been actively using it for the past two weeks, and have also contacted your company via email or your live chat widget?


You can do that.

Using a CDP gives you an immense number of options as to how you can segment your customers.


Customer Data Platform Options

Since CDPs are relatively new, there aren’t a ton of providers out there. However, we’ve listed a few of the top players in this list of Customer Data Platforms:



We’ll start this list of CDPs off with an introduction to ourselves so you know who we are and what LeadBoxer does. LeadBoxer collects information about your customer throughout their entire customer journey.

We collect and give you information such as:

  • When a customer visited your website, what pages they visited, and how long they spent on that page
  • What emails a customer has opened from you, when they opened it, and what links they clicked
  • Contact information such as the person’s name, email, what company they work for, where they’re located, etc.

All of this information is then organized into your “LeadBoard” and each of your different customers or leads are given a score to gauge how engaged they are with your company:

Each of these customers or leads can be viewed on a micro level to see every bit of that person’s activity:
Note: LeadBoxer can be demoed as free-trial for 14 days with full-access to all of its paid features.

Start your free-trial here.



Boxever is CDP that collects data on web visits, mobile activity, email activity, calls, ads, and more. It combines all of this data into one place and allows you to personalize your marketing and deliver predictive offers. Pricing is crafted on a per business basis.



Evergage allows you to personalize content on your website, app, and emails. It’s been used by companies such as Intuit and Walmart. Again, pricing is offered on a per business basis and you will need to contact a salesperson for a quote.



AgilOne is CDP specifically for B2C companies. The platform offers a “360 profile” where you can view customer interaction. Pricing is offered on a per business basis and you will need to contact the company for a quote.


Using a CDP is really the next level of marketing automation.

Providing an entire customer’s interaction with your company all in one place, rather than trying to make do with a suite of separate tools, really gives marketers and salespeople an immense amount of opportunity. It also saves time as you’ll no longer have to dig through data from multiple sources.

Instead, you can see a unified view of your customer all in one place and create insanely targeted and personalized marketing campaigns for your customers. Something that will not only create a stronger connection between you and your customers, but it will also help to close more sales.

Getting started is super easy. We will provide a tracking pixel for your site and emails and we will help you getting connected to as many touch-points as possible.

If you want to get started using a Customer Data Platform today, try LeadBoxer’s free 14-day full access trial.


Data-driven Lead Qualification

Why LeadBoxer Is The Best Choice For Automating Lead Generation


happy sales team


Q: As briefly as possible, what has LeadBoxer done that is so valuable for business websites?
A: Developed a way of applying Search Engine technology to qualify leads.

We started with visitor website tracking a number of years ago, and have evolved into a system which uses big data technology to identify interesting leads. Currently we’re working towards full automation of the process of lead identification.

Calling it AI or artificial intelligence would be wishful thinking, but we’ve definitely made enormous strides in the process of automating lead qualification and audience segmentation.

How have we done this? Basically, moving on from MYSQL to NOSQL using Elastic and Cassandra, we’ve built a system that can filter, in real-time, through website traffic, and create notifications based on a lead score. Click here to read how (technically) LeadBoxer’s lead score formula converts clicks into prospects via an algorithm.

What does this actually mean?
It means that now, as of December 2017, we provide the framework to organize Marketing and Sales data on the following traffic values:

  • Company
  • Country / Region
  • State / Province
  • City
  • Industry
  • Company Size
  • Utm Tags (PPC-traffic, Adwords, LinkedIn, Facebook campaigns)
  • URL
  • Exit Link
  • Referrer
  • Lead Tags (competitor, customer, partner, prospect)
  • Identity Fields (Email
  • First Name
  • Last Name)
  • Visits
  • Page Views


Letting smart algorithms do the heavy lifting

In conclusion, in order to succeed, a software product needs to add value. The value we are adding is machine learning. You tell our machine what a valuable lead looks like, and we use algorithms to find these leads for you. Our goal is to automate the process, so that letting LeadBoxer loose on a website will provide a list of all activity, prioritized by lead score. To increase the efficiency of the system, and reduce the burden of logging in to (another) software product, we push email Notifications to your team’s mailboxes.


List of Filter Notifications in LeadBoxer

When Big Data goes Wrong

When Big Data goes Wrong

Because Web Analytics is part of our core solution we have spent a lot of time pondering over and perfecting our use of Big Data. LeadBoxer has been in the industry for more than 15 years (both directly and indirectly) and we can say with fair certainty that we have learnt several things during our cumulative “service”. But we will be lying to ourselves if we don’t admit that sometimes Big Data can fail you. With that in mind, we wanted to write this piece on how to make sure that your company is using it the right way and it doesn’t lose touch with the individuals that make-up the data sets. In the spirit of honesty, I have to give credit to Martin Lindstrom’s book “Small Data”, because it is what gave me the inspiration for this article. In it, he makes a point that nowadays the corporate world has become blinded by Big Data and this happens because it is incredibly hard to describe emotions using data.

Data does not reflect emotions.

Martin starts his book with the famous example of LEGO. In 2002-2003 the company was going bankrupt so they used Big Data to determine that Millennials have short attention spans and get easily bored. This led LEGO to make their small, iconic bricks into huge, simplistic building blocks. This change only accelerated their decline so out of desperation, the company decided to go into consumers’ homes to try and reconnect with their once loyal customers. I am not going to reveal much from the book, but in a few words, after meeting with an 11-year-old German boy, they discovered that for children, playing and showing mastery in something was more valuable than receiving instant gratification. This made LEGO pivot again and after their successful movie in 2014 they surpassed Mattel to become the world’s largest toy maker. Now, of course there is much more to the story that is hidden in the background, but the bottom line is that patterns and trends can sometimes be misleading.

Correlation is not causation.

Big Data is all about finding correlation and patterns in human behaviour, but that is not always the whole truth. Take as an example Google; back in 2008 they believed they could use Big Data to predict flu outbreaks and launched a program called Google Flu Trends (GFT). The algorithm analysed search queries with the word “flu” to follow patterns but it did not take into account unrelated searches. And then in 2013 it failed dramatically by missing the flu season peak of 140 percent. This is not necessarily a failure of Big Data as much as it is a failure of people using it. Call it hubris or simple error of judgement. But the fact of the matter is that correlation is not always causation and sometimes Big Data is simply just too big and not all relevant.

Not all data is useful.

The problem with Big Data is that you are looking at the data you have collected and not necessarily the data that you need. Sometimes the numbers you have are not interesting or insightful. Or even worse, they are just a vanity metric. Like thinking that a lot of Twitter followers translates into actual real-life influence or that a lot of website traffic leads to high conversion. You only need to take a look at the Big Data Industry Report for 2016 by Prompt Cloud to see that the biggest issue for companies is how to get value out of the data they have collected. leadboxer-big-data

What is the take-home?

Data has become so rooted in our work that we sometimes use it almost exclusively. But the examples that I mentioned and all of the others that didn’t make the cut to be included in the article, show that it takes something more than data. Organisations need to keep in mind that data does not reflect emotions. Correlation does not always equate causation. And just because you have a lot of information it does not mean that it is useful or actionable.