Behavioral analysis as a basis for effective shopping mall strategy

Agnieszka Winkler, Associate Director, Retail Advisory Services, Colliers International
Agnieszka Winkler, Associate Director, Retail Advisory Services, Colliers International

Nowadays it is no longer enough to know who forms our client base – creating profiles based solely on the needs, expectations or values held by the consumers is no longer enough to remain competitive on the increasingly dynamic market. To make the right business decisions, one has to employ behavioral data analytics tools. The conclusions arising from behavioral analyses provide a far more precise quantitative and qualitative information on clients’ needs and lifestyles than client statements collected through traditional research methods. Data from said analyses can be combined with algorithms utilizing the advances in the AI technology, allowing to predict future needs.

Behavioral catchments

Crafting a good strategy for a shopping mall requires understanding consumer behaviors within the wider scope of the entire local market. In practical terms, this indicates a necessity of discovering not only shopping choices of the clients of a given mall, but also of those who have not yet become clients. It is particularly apt, if they live in the mall’s catchment zone. While collecting the data concerning the former is relatively easy, knowledge of the latter group tends to be limited, despite it possibly being key for raising footfall and strengthening the shopping mall’s performance.

Behavioral catchments indicate how the clients behave within the designated areas – not only their home zones, but also their work zones. For example, the research might show that the catchment of an analyzed shopping mall consists primarily of persons working (but not residing) nearby and highlight their potential. Said persons will, as a general rule, visit the facility between Monday and Friday, usually within particular time windows – in the morning (before work), during lunch hours and directly after leaving work. Another characteristic behavioral pattern would be nearby workers usually shopping alone, but being able to share lunch offers with colleagues.

Having such knowledge gives the basis for taking appropriately directed marketing action and making correct operational decisions, such as preparing varied lunch and services offers in response to high potential of the nearby office workers, or establishing the right communication strategy.

Choose technologies smartly

Shops which operate strictly online tend to precisely analyze their clients’ activities, while brick and mortar shops and shopping malls find other technologies useful for purposes of consumer behavior analysis.

There are several research methods, utilizing broadly defined mobile data, being used on the market. Most of them are based on the GPS technology and Internet signals coming primarily from various applications. Such an approach might yield unrepresentative data, leading to overrepresentation of smartphones and people using certain applications, which could narrow the subject group or skew the demographic profile towards younger people.

GSM-based technology proves to be more effective and trustworthy. It’s more precise, covers all telephone types, does not require an Internet connection or use of an app and thus has an increased range and leads to a wider, more representative sample. Thanks to such a methodology one can, among other things, precisely define behavioral catchments – that is, factual influence zones of a mall – allowing for learning factual mobility patterns within the urban space and thus research factual flow of clients in given shopping facilities and analyze its potential.

Responding to such needs, Colliers International, in cooperation with DataWise, has created a research tool using mobile operator’s data and microstatistical data sets of several million phone users from Poland, who had agreed to processing of behavioral information. The tool provides owners with key data for making investment decisions.

Such advanced methods, when combined with expert knowledge and systems owned by the client to merge various data sources and types, allow for constant monitoring of changes and therefore providing of an up-to-date support for business decisions. The owners of shopping malls have at their disposal tools for monitoring footfall, number of cars or loyalty programs, while tenants can reach such capabilities by merging GSM-based behavioral data with POS system data, RFID-enabled labels or loyalty programs.

Appropriately used data

Based on mobile data, one can monitor the frequency of client visits to a given mall and the circumstances behind their visits, appraise effectiveness of the conducted marketing activities and target the future ones more precisely, as well as answer the question of whether the marketing budget has been effectively allocated. Moreover, the tool allows for monitoring the behaviors of the entire local market and thus enables establishing the position held by a mall in its clients’ choices and who is its largest competitor.

The tool utilizing GSM data might constitute the starting point for crafting the mall’s strategy – but even more importantly, it allows for ongoing monitoring of changes and their effects. It provides an advantage over the traditional statistical research, which are usually only conducted once and often utilize clients’ declarative data. Big Data analysis allows for appraising the real potential within a mall’s catchment area, including how many potential clients remain and what are the chances for attracting them.

Agnieszka Winkler, Associate Director, Retail Advisory Services, Colliers International