Digital Marketing - Study Notes:
Common data types
When working with data, it’s important to note the different types of data that exist. In essence, you need to understand which types of data are important for your organization, and secondly, you need to consider how you are going to capture the information you need. As well as storing it, and of course using it.
Some of the more common data types that digital marketers typically use are:
- Zero-party data
- First-party data
- Second-party data
- Third-party data
Zero-party data
Zero-party data is data that individual customers proactively share with an organization via feedback forms, surveys, email responses, phone calls, and online chats, for example. In other words, you don’t have to search for this data because customers provide it themselves. This type of data is powerful because it may directly indicate a customer’s preferences or purchase habits, or how a person wants a brand to interact and engage with them.
That being said, zero-party data poses some challenges too. The amount of data you collect may actually be too small to be statistically significant. As a result, it can be hard to know how best to use it.
First-party data
First-party data involves collecting specific data about your website visitors or customers, through lead forms, ecommerce purchases, and other transactions.
While similar to zero-party data, first-party data isn’t as proactively shared by the customer. With zero-party data, the customer decides to reach out and tell you something. With first-party data, on the other hand, you collect data on a customer as they are browsing or engaging with your business. In other words, with zero-party data, customers give you the data, whereas with first-party data, you collect the data from the customers.
Second-party data
Second-party data is essentially one organization’s first-party data that is sold directly to another organization. Google and Facebook, for example, allow you to access their user data in relation to any campaigns you run on their advertising platforms.
Other types of second party data you can purchase may include data from activity on their websites, apps, social media, email lists, followers, in-store purchase history, and survey responses. It’s important to do your due diligence when purchasing any second party data sources to ensure it has been collected legally and there is consent from the original user that allows for sharing of their data.
Third-party data
Third-party data is data from multiple sources that is then compiled and made available to you as a single data set. An example of this is, , when people add a Meta or Google Ads tracking codes or pixels to their website. When shared back to you via the ad platforms, the data that is collected is called third-party data.
This may sound like second-party data, but there is a distinct difference. A user may start their browsing or interactions on Google or Facebook, but the moment they click an ad or link that brings them to a new platform or website, the data becomes third-party data. This data is then fed back to Google or Facebook, and subsequently organized and compiled before making it accessible to you.
Reliability of data
Digital marketers need to be cautious about the reliability of second- and third-party data sources. So, for example, Facebook gathers information on websites and app users and allows you to access it. Facebook here is the middleman, providing you with their second-party data. However, the data that it retrieves, in your case, is third-party data. As a result, the data collected and used by you won’t be as vetted and may be somewhat skewed.
Nevertheless, each data type can be useful in different ways in terms of the insights it provides and the impact it can have on making strategic decisions. It is also worth noting who is collecting each data type as this will have implications in relation to data privacy, which we’ll explore at a later stage
Back to TopCathal Melinn
Cathal Melinn is a well-known Digital Marketing Director, commercial analyst, and eommerce specialist with over 15 years’ experience.
Cathal is a respected international conference speaker, course lecturer, and digital trainer. He specializes in driving complete understanding from students across a number of digital marketing disciplines including: paid and organic search (PPC and SEO), analytics, strategy and planning, social media, reporting, and optimization. Cathal works with digital professionals in over 80 countries and teaches at all levels of experience from beginner to advanced.
Alongside his training and course work, Cathal runs his own digital marketing agency and is considered an analytics and revenue-generating guru - at enterprise level. He has extensive local and international experience working with top B2B and B2C brands across multiple industries.
Over his career, Cathal has worked client-side too, with digital marketing agencies and media owners, for brands including HSBC, Amazon, Apple, Red Bull, Dell, Vodafone, Compare the Market, Aer Lingus, and Expedia.
He can be reached on LinkedIn here.

Kevin Reid
Kevin is a Senior Training Consultant and the Owner of Personal Skills Training and the Owner and Lead Coach of Kevin J Reid Communications Coaching and the Communications Director of The Counsel.
With over twenty years of experience in Irish and International business with an emphasis on business communications training and coaching, he is a much in demand trainer and clients include CEO’s, general managers, sales teams, individuals and entire organisations.
With deep expertise in interpersonal communication through training and coaching and in a nurturing yet challenging environment, Kevin supports teams and individuals through facilitation and theory instruction to empower themselves to achieve their communication objectives. This empowerment results in creativity, confidence building and the generation of a learning culture of continuous self-improvement.

By the end of this topic, you should be able to:
- Critically analyse the process of using analytics tools to create insights
- Critically evaluate the role of Artificial Intelligence (AI) and Machine Learning (ML) tools in enhancing marketing strategy
- Evaluate Customer Relationship Management (CRM) data and its use in informing business decisions