Ashutosh Malegaonkar
As Cisco DevNet’s Co-creation strategist, Ashutosh does more than making things come to life. With more than 24 years of industry experience with varying roles, he's obsessed with innovating new ways of creating amazing solutions and experiences. He has an avid passion for innovation and anything that can make life simpler.

Brick and mortar retailers face competition on all sides. Some customers may only go out as a last resort, wanting to see an item that they have found online. Other customers may go out for the shopping experience and to see what is available. Some may look for the same product on the web for a better price, sometimes even while they are in the store. Making the shopping experience easy, personal and pleasurable is one area where physical retailers can compete with online retailers.

Retailers need to understand the customer’s experience from the time they near the store to the time they leave. Do they just walk past the store? What happens if they come in? How long do they stay? The truth is retailers know very little about what a customer does, from the time they near the store until the time they leave. How many people walk by because the storefront does not entice them enter? Their only data point might be the point of sale system. Retailers need more information to engineer and improve the customer experience.

For example, one of the complaints about retail stores is that customers are on their own when it comes to finding out if a product is right for them. At buying time, it is natural for a customer to want to confirm that their decision is correct. The customer decision point is an opportunity for the retailer to personalize the customer experience. Putting a salesperson in front of the buyer at the right time can enhance the shopping experience. At the wrong time, it can detract from it. If someone is “just looking” they may not want to be bothered. However, if someone is trying to decide on a color or style the intervention might be welcome. Timing is what differentiates the pushy salesperson from a trusted advisor.

However, what is the right time? Creating this balance is where the appropriate data and analytics play an important role. To solve this riddle, retailers need data to answer some of the following questions:

  • How much time has the customer spent in the same area of the store?
  • Has the customer picked up an item?
  • When is the right time to dispatch a salesperson?

Answering these questions and many others are critical to modern retailers. They are competing against Amazon, eBay, and AliBaba, and creating an excellent customer experience in their physical stores are their greatest asset versus their online competitors. As a result, retailers must understand how customers are using their stores and responding to the environment to enhance the customer experience.

Cisco Meraki MR access points (AP) and MV Cameras Provide Key Information about Customer In-Store Behavior

Cisco Meraki allows retailers to obtain and analyze the information they need by taking advantage of their existing WiFi infrastructure. The Meraki MR APs allow capture of movement data while the Meraki MV Camera provides the video detail to complete the picture. These devices are wireless and can be installed and managed in the cloud, without any additional equipment. More information about device management using Cisco Meraki Cloud Managed Wireless is available at

Information Provided by the Cisco Meraki MV

Today a large percentage of people carry a mobile device. The Meraki MR can detect this device and map its movement near and throughout the store, whether or not they log into the in-store WiFi.

The out-of-the-box (OOTB) dashboard shown above provides the retailer with an understanding of:

  • Proximity- how many people are passing by the store, actually coming in and connecting to the in-store WiFi
  • Engagement-how long people are spending in the store
  • Loyalty-people who are return visitors

The proximity data allows the retailer to consider the amount of foot traffic passing the store and how well their storefront displays and window advertising are doing to get people to enter the store. It can answer questions such as:

  • How does this week’s storefront compare to last week’s in terms of customer engagement?
  • How do different discounts on window advertising impact the number of people entering the store?
  • Do my storefronts have different effectiveness in different locations?

The data also provides the marketing department the ability to do A-B testing of marketing strategies.

The engagement information provides a macro measure of the customer’s in-store experience. Are people entering the store and leaving immediately or are they being engaged by the merchandising? The dashboard can easily be adapted to display time intervals that are appropriate for the analysis in question.

While we only know the customer by their device, that device is unique. That provides the retailer with a measure of customer loyalty. What percentage of the customers are engaged enough to return. How does that compare with business plans and marketing efforts? Are highly discounted specials introducing people to the store, creating loyal customers and additional sales?

Meraki MV allows much more in-depth analysis as this OOTB heat map shows:

This heat map is a single snapshot of what is going on across time. It can provide the retailer with an indication of which areas of the store are most heavily visited. The colors indicate how long a visitor has lingered in the area. Filters, time stamps, and streaming capabilities that are built into the dashboard allow for analysis of foot traffic through the store over time. The heat map can help determine the effect that product placement and promotions have in leading people to under-visited portions of the store.

All the Meraki data can be aggregated at a variety of levels to allow for cross-store or time comparisons, as well as A-B testing of different store layouts or other marketing strategies.

To further personalize the shopping experience, the Meraki MV dashboard can be configured to send an alert to a salesperson when a customer has spent a given amount of time in an area. Dispatching a salesperson enhances the customer experience.

Going A Step Deeper with the Cisco Meraki MV Camera

While the Meraki MR provides detection and general movement of the customer through the store, the Meraki MV camera captures a video of what the customer is doing. For example, what racks of clothing are getting the most attention from customers? The Meraki MV camera provides a video stream that is searchable by activity. We can look at two or more racks and search for an event such as picking up an item. The ability to search for a specific event allows the retailer to find only the videos that are of interest. The built-in machine learning feature allows the camera to get smarter over time by learning which objects and video streams are of interest.

Another customer experience enhancement couples the MV Camera with the MR access point information. When a loyal customer enters the store, the MR detects them. The MV camera can capture an image of that customer. The salesperson receives the alert along with a picture and can greet that customer and welcome them back to the store.

Further Analysis

The power of analytics is enhanced when data from different sources are integrated.

Merakibeat is an Elastic Beats plugin that enables data collection and the creation of an analytics pipeline for multiple Meraki APIs including the Meraki MV Camera and MV Scanning API. This pipeline allows the retailer to integrate multiple Meraki data streams with other enterprise data from their Point of Sales or Customer Relationship Management (CRM) systems.

As the diagram indicates, this data can be merged using elasticsearch and analyzed using Kibana, creating insights about revenue and other Customer KPIs.


Cisco Meraki devices provide retailers with a way to leverage their existing WiFi infrastructure to obtain insights about what happens from the time a person nears their store to the time they leave. Further, it allows them to integrate this data with other enterprise information. This end-to-end customer behavior can be used to evaluate and improve the retailer’s efforts to enhance the customer experience and increase sales. It allows store-level activities to be transparent as opposed to a black box with a POS system as the only measure.

The OOTB analytics, provided by Meraki, allows the retailer to achieve an understanding of their customers’ in-store experiences quickly. The amount of time to make marketing decisions becomes days instead of weeks or months. Between-store comparisons can be built and ideas tested, and successful approaches deployed.

Meraki analytics, while powerful on their own, can be coupled with other available data to provide accurate and faster decision making. The Meraki APIs allow for additional customization of analytics beyond the OOTB analytics provided.

Retail executives may ask themselves if investment in the kind of technology Meraki offers is worth the expense. As we've seen, the reality is that in a world of global competition, where retailers are under attack from all sides, they need to use this technology to enhance and improve on their in-store investments.

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