Implications of zero party data on user decision-making in digital advertising: Implications of behavioral economics on decision-making

Abstract

Today’s digital advertising is predominantly founded on third party data such as cookies, which track the browsing behavior history. However, the data collected by cookies is incomplete, it merely reflects past browsing behavior instead of providing information on current interests and specific consumption desires.

Due to an increased need of privacy, Google announced the disappearance of third party cookies. This means that websites will not be allowed to collect user data through cookies anymore in order to share it with third parties. As a result, companies will not be able to rely on user data gathered through external websites.

On the other hand, zero party data allows companies to collect direct information from its users. Through the means of intentionally provided data by users (such as user profiles, forms and surveys), digital advertisers could create more pertinent advertising content without relying on third party cookies.

When subject to digital advertising, several biases play a role in the decision making process. This work intends to assess the impact of digital advertising using zero party data, by analyzing the potential decrease in discrepancy between rational consumption intent and actual consumption considering behavioral biases. 

Browsing is defined as the “act of looking through a set of information quickly, without a specific sense of purpose”[1]. In Thinking Fast and Slow, Kahneman, D & Tvesky, A (2011) explain how the thinking system 1 uses past decision-making experience to generate a fast response, which is often influenced by a variety of behaviour biases. Therefore, browsing information collected by third party cookies results from system 1. 

Zero party data primarily relies on system 2. This thinking system works in a slower manner as it requires effort to lead to logical conclusions. It is used for instance to resolve hard problems and evaluate pros and cons. When answering a complex survey on personal goals, or completing a form requiring conscious attention, then, system 2 is used. As zero party data consists of more meaningful and intentionally provided information compared to third party data, digital advertisement based on zero party data has a higher likelihood that rational consumption intent and actual consumption are in line.

The methodology conducted consists of research through two surveys (which served as A/B test) and interviews to suggest an alternative approach to third party cookies. Through the surveys and interviews, eight biases and heuristics present in the user journey were identified; the paradox of choice, the availability bias, the confirmation bias, the consistency bias, the bandwagon effect, the anchoring bias, the Ikea effect, and the affect heuristic. Each section aims to analyze how these biases affect the online consumption process of a user in both scenarios of third party data and zero party data. Each outcome revolves around how to use the identified bias in the benefit of the user using zero party data.

Digital advertisement based on zero party data is a win-win solution for the user and the advertisement company.