Marketing research as continuous practice in Retail

If the pre-Socratic philosopher Heraclitus sat in front of a notebook today to analyze customer flow data from a department store dashboard, he would certainly say “I told you so”. According to him, nothing is permanent except change. This ancient perspective, which highlights the ever-changing nature of things, can be verified by any retail manager who relies on smart tools to manage brick-and-mortar stores. In other words, everything flows.

This is precisely what modern technologies capture when assessing reality. They allow numbers to speak right before our eyes, so that change becomes evident. In this new context, management decision-making can’t be based on static plans or paced only by the calendar.

Indeed, Big Data allows for a dynamic measurement of reality. And guess which market is the most influential to the growth of Big Data today? Correct: video surveillance.

In a study published by IDC last June, it says “most of the data is being generated by video surveillance applications”. By 2025,it is estimated that the number of network devices, such as the IP cameras, will reach 41.6 billion worldwide. According to IDC, the video surveillance category will drive a large share of the IoT data created.

As more devices are connected to the network, many companies are expanding their capacity to get business insights in an agile way. But are they aware of this opportunity?

Understanding the customer

Large companies often rely on investigative methods, such as focus groups and interviews, to support their decisions when facing a specific management problem. The marketing researchers go and collect primary data and cross reference it with internal sources and market information. Then managers use it to understand fundamental issues like:

  • Consumer predisposition to adopting new habits
  • Segmentation of the target audience
  • People’s attitude towards a brand

Indeed, traditional marketing research methods allow companies to understand today’s challenges and project trends, especially to support relevant management decisions. Of course, other methods are also common when it comes to supporting decisions – like reports extracted from CRM (customer relationship management) or BI (business insight) tools. But what if the existing IoT devices became a regular source of data and even generated alerts for marketing managers and store managers to analyze the peaks and act accordingly?

This is the reasoning behind the use of video surveillance cameras as sensors to capture data and generate live reports. With a high processing capacity, these cameras send data that can be displayed independently or as part of a BI platform used by the retailer. This can help retailers understand things like:

  • The effectiveness of a marketing campaign by looking at the increase of customer flow during a specific timeframe on a specific day.
  • Brand acceptance amongst a particular target audience , such as a higher proportion of men or women, or by age range.
  • Conversion rates (daily, if needed) by cross referencing the number of visitors with POS (point of sales) data.
  • Number of shoppers waiting in line to trigger the opening of an extra cashier.
  • The value of areas at a shopping mall or a store based on customer flow, in order to support the negotiation of rent or merchandising spaces.

Things to keep in mind

Some retailers are already taking advantage of this, both to enrich their business acumen and to quickly respond to opportunities or threats. But it’s nice to consider some limitations as well:

  1. Understanding why

Like any quantitative analysis, the data generated by network devices can’t confidently support hypothesis about shopper motivation. In other words, a report based on people counting at a store entrance can be useful, but it doesn’t say much about the reasons for this flow.

  1. Illogical use of numbers

Depending on the criteria, establishing targets based on data collected by IoT devices can lead to misinterpretation. The numbers presented by the reports must have a direct relation with the object of the research. For instance, a low percentage of male visitors doesn’t imply that the promotion for this target audience is not effective (since shoppers are not always consumers).

Despite the challenge posed today by e-commerce, physical stores can incorporate a digital mindset. Afterall, what is physical can be translated into dynamic data and allow for an effective and fast decision. Part of the solution is already sitting in the managers’ stores in the form of video surveillance cameras.

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