The Value of Zero: Accuracy and Trust

Data-driven marketing has always focused on getting as much information on your customers as possible through various channels. As privacy grows increasingly important and tracking becomes increasingly limited, zero-party data (ZPD) is on the rise.

Conventional marketing wisdom has always been that the more you know about your customer, the more effectively you can target them. For that reason, marketers have always been trying to get their hand on as much data as possible, relying not just on their own first-party data but even paying for second-party and third-party data. 

To clarify terms, here’s a rundown on the differences in data sources.
First-party data

First-party data is what a business receives directly from a customer typically as a result of purchases, subscriptions, or points of contact. It can be the result of what a customer actively fills in on a form or passively shares as a result of cookies that the customer accepts by using the brand’s site or the tracking that comes through use of an app.

While a complete record of information given by a customer is valuable, for businesses that haven’t had much time to gain a complete history, it may not suffice to inform truly tailored experiences. That’s why businesses will pay for access to additional information through second and even third parties.
Second-party data

Second-party data is first-party data acquired by another company that is then sold to a business that wants more information about its customer base. Drawing on the more thorough information can fill in more of the customer picture, but it’s still limited to what a single business has been able to gather on the customers, which is why some will pay a broker for data.


Third-party data

Third-party data is different from first and second party in that it draws on multiple sources of data that a separate company puts together into a single dataset to be sold to those in the market for that kind of customer information. Typically, the company in the business of delivering data will purchase first party data from a number of companies to create these data packages for others to buy through the data exchange marketplace.
Data drawbacks

While going from one to three increases your data resources, it’s not without its drawbacks. As anyone can buy third party data, what a business buys is not unique to it. As a result, it is very likely that all businesses competing for the same customers are working off the same data set.

Also since the establishment of GDPR in Europe and CCPA in California, marketers have had to respect consumer-set boundaries for the collection, use, and sale of their data.

The rise of such legislation has shed more light on privacy issues that has created pressure for platforms to stop enabling data collection without users’ knowledge. That is the story behind Google’s resolution to phase out third-party cookies and Apple’s new iOS setup for informed consent on apps.

The new frameworks don’t only curtail marketers from using data obtained from outside sources. They can even limit some first-party data that businesses have obtained without informed consent by tracking consumer behavior with cookies, pixels, or cross-device identification (XDID).

That is why a couple of years ago, we started hearing about zero-party data or ZPD. The term has been credited to Forrester, which presented it in Predictions 2019: B2C Marketing Report.

This approach has gained momentum over the past couple of years. AW360 predicts that a quarter of CMOs will be looking to implement ZPD in 2021.
The zero-party solution

As both zero-party data and first-party data take in information directly from the customer, there is some overlap between the two. The crucial difference between them is that zero-party data only includes what a customer knowingly and willingly shares.

That means that customers are in full control of the information they share with the business. They are willing to give their data if they feel they can trust the brand and are getting something of value in return.

Read more in  Zero to Hero: Providing Personalization & Privacy

Today's targeted marketing is powered by data and automation

 Marketing is always more effective when it is more targeted. As a result of integrating data and algorithms, marketers are able to now deliver a personalized customer experience at scale. 

There are various ways to target specific customers, and approaches range from lumping customers into very broadly defined categories to getting a lot more fine-tuned about the segments and responsive to individual customer behavior .In collaboration with Google, Deloitte put out a Digital transformation through data: a guide for retailers to drive value with data that took a closer look at these gradations. 

It ranked them as follows:

• Limited segmentation: All users are analyzed in broad segments. 

• Basic segmentation: Uses standard characteristics (e.g., gender, geography) for segmentation.

• Detailed segmentation: Segments are based on personal and behavior

• Dynamic segmentation: The UX / UI can respond to a customer’s in-session behavior as he or she exhibits different segment characteristics.

Achieving the detailed level depends on much more data than the static kind that is used for basic segmentation, and advancing to the dynamic level requires a level of automation that will enable recommendations and responses to go out in real-time. 

 The coming AI revolution in retail and consumer products invoked the women’s clothing store,  Avenue Stores LLC as an example of dynamic segmentation. It explained that  it brings together “data across multiple touchpoints, including in-store activities and market trend analysis, to learn and reason about what customers want and when they want it.” On that basis it can reach out to customers with communication tailored to their situation in real-time, which makes it possible to capture their attention while in “‘shopping mode.” 

Marketing for loyalty

Being in touch with your customers to let them know you’re there for them without pressuring them to buy can pay off in winning their loyalty and business later. In this case, your automated messaging doesn’t have to respond to segment your audience, as you would be working off a general form of communication.

When you don’t have history

But what if you do need to sell your products now? Marketing recommendations can work even on the more basic level, not just for new customers for whom you have no history to flesh out a profile but for the type of marketing communication that depends on general trends. For example, a very broad segment of all people in the United States can work for promotions tied to events shared by all due to the calendar, whether it’s Mother’s Day, Memorial Day, July 4th, etc. 

You don’t need to know much about your customer other than that they’ll know what these days are because they are on their calendars due to living in the United States for the trending algorithm to work well. That makes using this approach ideal for customers for whom you don’t have first-party data.

It doesn’t matter so much what they are normally interested in or what they’ve bought before when you’re sending out a marketing message about buying their mother something before May 10. However, if you do have information about the customer, say you know they’ve ordered flowers for their mother last year, then you can combine the trending recommendation with what you know about their behavior.

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Advanced Segmentation and Automation Are Changing the Marketing Game