First-party

This is the most powerful data of all, because it’s the stuff you collect directly from your customers and it’s therefore the most relevant and accurate. 

Think of it like this: if I ask one of my actual customers about themselves directly, I’m likely to get a much more accurate picture of my target audience than if I bought some data that was ‘representative’ of that audience but taken from people who largely aren’t my customers at all.

Not only that, but I am the only one to own that unique data set (unless I choose to sell it), which makes it all the more valuable. 

In a recent Econsultancy report titled The Promise of First-Party Data, almost three-quarters of marketers we surveyed said first-party data provides the greatest insight into their customers. 

Of those surveyed who manage to produce strong return on investment (ROI) from data, 81% say they use first-party data regularly, compared to 77% who use second-party data regularly and only 61% for third-party. 

Q: Which categories of data does your organisation use regularly?

types of data brands use

The above chart illustrates not only the power of first-party data when it comes to achieving actual business results, but also the fact that those brands who’ve struggled to produce data ROI are perhaps putting too much focus on third-party over second or first-party data.  

Where it comes from

In our survey, the most frequently cited source for collecting first-party data was a brand’s website (70% for those with strong data ROI), while 63% collect it at the point of sale and 61% via email or SMS.

Q: What sources does your organisation use for collecting first-party data?

first-party data collection sources

Pros 

  • Belongs to your brand.
  • Unique.
  • Less regulated. 

Cons

  • May be limitations in terms of depth and scale. 

Second-party 

This is a relatively new form of data collection, and it is essentially another company’s first-party data that is collected and sold to you by that brand. 

In theory it enables brands to exchange data with each other in situations where it benefits both parties. 

One example might be a hotel chain working with an airline to mutually benefit from each other’s data sets. 


In a recent post about creativity in programmatic, TUI’s Head of Media, Sammy Austin, said of second-party data:

Being able to access another data set directly from another source is extremely valuable, and where there is no competition between brands I think these types of relationships will bring huge benefits.

Where it comes from

Most often from other brands whose data sets might compliment yours and vice versa, as mentioned above, and usually under a pre-determined and defined agreement.  

Pros

  • Can add depth and further meaning to existing first-party data.


Cons

  • Potential integration issues. 
  • Can be limited in availability compared to first-party data. 
  • Data partnerships can sometimes bring complications with them.

Third-party

This is your bog-standard, bargain basement data. The stuff you can buy pre-collected from an external source. 

If you receive an email from some company you’ve never heard of, it’s very likely your data has been sold to them. Perhaps that email is relevant to you, but compared to first and second-party data the likelihood is lower. 

Because these data sets are sold ‘off the shelf’, they are by definition not unique, which of course diminishes their value and means competitors could easily access the same insight. 

Where it comes from

This type of data can be purchased either from a company specialising in data collection or any other business that has valuable data sets. 

If you are going to use third-party data to target people, I strongly recommend you read up on the new EU data regulation laws first to avoid getting into trouble.  

Pros 

  • Readily available.
  • Wide-reaching

Cons

  • Quality can vary wildly. 
  • Not unique.
  • Can be costly. 
  • Higher risk of breaching data regulations.  

Download The Promise of First-Party Data today for lots more insight around different types of data.