Location-based Advertising and Consumer Data

By Jun.-Prof. Dr. Irina Baye (Photo)

Location-based, mobile advertising is online advertising that is sent to the customer's mobile device (e.g. smartphone, lap-top, tablet etc.) by means of a GPS signal from the customer's device. This type of advertising is particularly interesting for retailers who want to attract customers near the store with personalized offers. In order to make attractive offers, advertisers try to combine the location data of customers with other customer data. For example, data on the age and income of customers can help to calculate optimal discounts. In our analysis, we assume that younger and less solvent customers are more likely to be attracted by discounts and therefore visit shops that offer a discount. Additional customer data on age and income therefore allow us to better assess the sensitivity of individual customers with regard to discounts. A customer who is highly sensitive to discounts is more likely to enter the advertising store than another customer in the same location who is less sensitive.

In our study, we look at two advertisers who have consumer location data and analyse their incentives to purchase or collect additional data that signal customer rebate sensitivity. The quality of this additional data is varied.

Effects of Customer Data on Competition

Using three scenarios, the study shows how corporate profits develop when two advertisers acquire additional customer data. In the first scenario, additional data on age and income weakens competition, so that the profits of both companies increase. In this scenario, consumers are relatively similar, they do not differ from each other particularly in their sensitivity to discounts. Even without access to data on age and income, competition is relatively intense because the companies compete intensively for all customers. Additional data cannot then further intensify the competition.

However, the companies benefit from the possibility of using more data to design more suitable customer offers and ultimately to push through higher prices with relatively small discounts. The second scenario represents a counter-case: Regardless of the quality of the additional data, corporate profits fall. In this scenario, consumers are very different, so that each company serves only certain customer groups (especially consumers near the store with low discount sensitivity), if the advertisers only have access to customer location data. This allows advertisers to avoid fierce competition. Additional customer data now causes the company to advertise for customers more intensively, which leads to tougher competition and correspondingly lower profits. The third scenario represents an incident: More customer data of relatively poor (good) quality reduces (increases) profits.

Our analysis shows that the incentives for companies to collect or acquire additional data can be very strong. Because the profit effect of the additional data can be in line with the three scenarios described above, companies may be worse off with data than without, for example in scenario two and in scenario three with low quality data. This is the dilemma: each company finds it individually profitable to acquire the data. Both companies, however, are ultimately worse off.

Conclusion and Implications For Competition Policy

Our analysis has shown that competition can become more intense and prices fall accordingly when companies engage in location-based advertising and collect customer data. This is the case when consumers are very diverse or when advertisers use low quality data while consumers are moderately heterogeneous. This result contradicts the conventional conclusion that more data on consumers is always profitable for companies. On the other hand, additional data can also lead to higher prices and thus harm consumers. These data-induced price increases offer another argument against the intensive use of consumer data, in addition to the possible violation of privacy. Price increases are more likely if the data are relatively precise.

This article is also published in the DICE Policy Brief.

DICE PUBLIKATION

Irina Baye & Geza Sapi (2019), Should Mobile Marketers Collect Other Data Than Geo-Location?, Scandinavian Journal of Economics, 121, 647 – 675.