Marketing Forensics: How To Better Understand Your Customers

Claritix Services, Software Leave a Comment

Most companies nowadays gather and analyze data about their prospects and customers. Some companies collect vast amounts of data and some collect the bare minimum.

But regardless of how much customer data a company collects, the important question is:

  • How do companies use this data?
  • And, how  can they best leverage this data to create better customer experiences and in the process convert more customers?

While this sounds easy, the ever-increasing number of software solutions used by marketing today has resulted in a spaghetti of data that no one can easily unravel. Things have gotten so bad that most marketers need to get an additional degree in programming!

Here’s an actual ad we found on Facebook:


Now, while there are plenty of practical reasons for marketers to learn coding, the point we’re trying to make is that data complexity is a real problem!

But in order to be able to accurately identify a solution to the problem, we need to first take a step back and analyze the different kinds of customer data that companies collect.

For the most part, customer data can be split into 3 broad categories:

3 Types of Customer Data

1. Demographic

Demographic data as we all know is the foundation for customer segmentation. Companies try to collect demographic data with the least amount of friction possible during a customer’s interaction with their brand.

This data can be collected from different channels including (and most commonly during) a visit by the customer to their corporate website


Demographic data includes basic information like a customer’s first and last name, their company name, email address, phone number, location, IP address, etc.


While the data itself can seem fairly basic, it provides companies some preliminary information about a customer, which can be used to manage the initial engagement and communication with them.

2. Behavioral

Behavioral data is the next step in the metaphorical analytics chain. This information is collected progressively throughout multiple customer-brand interactions.

This data is also collected from various sources over a period of time, which when combined with demographic data can help deliver a more complete view of a customer.


Behavioral data includes asset downloads, webinars attended, pages viewed, event participation, demo requests and more.


Behavioral data is a handy part of the analytics chain because it helps companies tailor their messaging to match the customer’s behavior with their brand. Think progressive profiling.

This information can help companies better understand the motivations and interests that drive their customers.

3. Journey

If behavioral data looks at specific steps taken by a customer, then the customer journey looks at a composite view of all the steps that were taken.

This information is collected from multiple sources and laid out sequentially to determine the path traversed by customers as they engaged with a company.


This data includes different interactions between the customer and company, the type of interaction, the channel it took place on, the content that was consumed by the customer, and the outcome of the interaction.


The customer journey data provides a company with insights on the most current phase of the customer lifecycle. It can help brands tailor their offerings and nudge customers into the next stage of the buying lifecycle.

On a broader scale, information across multiple customers’ journeys can help the brand identify the most effective channels, campaigns, and content that helps successfully convert a prospect into a customer.

So why do we bring all this up? (Other than our innate love for data)

Challenges to Leveraging Customer Data

The above data is collected to varying degrees of detail based on the technology solutions used by each company. However, even the smallest company has a vastly diverse technology spread in place which results in multiple solutions, each holding only a part of the puzzle.

And more often than not, companies do not (or cannot) mine all this data and leverage it to improve the customer experience and drive conversions.

So, what’s the problem?

Complex Sales and Marketing Stack

The stack of technologies that most B2B companies have accumulated is very diverse and difficult to manage.

Most of these solutions address the needs of specific channels and are siloed. Collating and matching data across all these different solutions is often difficult and becomes the responsibility of the companies using these solutions (ironically to solve their complexity issues).

Brands find it very time consuming and expensive to get any meaningful insights in a timely manner. In fact, companies using tools like marketing automation platforms, which are designed to simplify the process and share insights, are finding it more difficult to get the insights they need:

So what can companies do to simplify their analytics?

Adopt a Marketing Forensics Approach

To overcome these challenges, we created the Marketing Forensics approach. (insert shameless plug here)

Marketing Forensics allows you to:

  • Get the data pieced together across all relevant source systems
  • Have the duplication and redundancy removed
  • And, meaningful insights delivered to you in a cost-effective and timely manner

Just watch this short 2-minute video to get a better understanding of it:

If you want to get more details on how companies are already benefiting from the Marketing Forensics approach, you can contact us here.