Meraki wireless access points include a powerful location analytics platform that provides real-time visitor statistics to help measure customer engagement, foot traffic patterns, and guest loyalty across all sites. The information collected by Meraki access points is synced to the Meraki cloud, where dashboard automatically displays a variety of useful statistics. Data can also be exported to custom applications and technology partner solutions via the Cisco Meraki Scanning API, providing a flexible and powerful platform that can be used by a variety solutions, platforms, and teams within an organization.



With the rapid adoption of mobile devices, many organizations can now rely on big data to better understand foot traffic patterns and behavior in a brick-and-mortar environment. This location information, based predominantly on 802.11 wireless and Bluetooth standards, can be used to engage users and optimize marketing strategies. For retail, this can help combat trends such as the erosion of in-store sales to online retailers, who for years have had access to similar data via the analytics produced by online tools (e.g., click-through conversion rates from online advertising).


Smartphones with WiFi can now be used as an indicator of customer presence thanks to a WiFi mechanism that is common across all such devices: probe requests. These 802.11 management frames are transmitted at regular intervals from WiFi devices. The frames contain information that can be used to identify presence, time spent, and repeat visits within range of a WiFi access point. These devices can be detected by WiFi access points irrespective of its WiFi association state meaning that even if a user does not connect his or her device to the wireless network, the device’s presence can still be detected while the device is within range of the network and the device’s WiFi antenna is turned on1.

Since smartphones now have greater than 50% penetration across the general population2, probe requests can be used to build and detect a statistically significant data set regarding the presence of WiFi-enabled devices within range of a given access point. Meraki wireless Access Points and cloud infrastructure gathers this data and presents it in aggregate on the Meraki Dashboard. This is done through intuitive and customizable graphs that can be used to understand trends such as capture rate (passersby vs. visitors), user engagement (total time spent), and visitor loyalty (new vs. repeat visits). Meraki is able to provide these analytics to all organizations by leveraging the industry-leading cloud architecture that is behind all Cisco Meraki products. Additionally, Meraki Scanning API is capable of exporting raw data from the observed probe requests, which organizations can use to integrate directly with third-party data warehousing or analytics platforms. Not only can this facilitate a deeper integration with traditional customer relationship management (CRM) platforms, but, due to its real-time nature, it opens doors to next-generation customer engagement initiatives.

1 The collection and use of location information has raised general privacy concerns. Meraki is sensitive to these issues and has designed location analytics with privacy in mind. Users concerned with having the presence of their device detected by these kinds of systems can avoid detection simply by turning off the WiFi antenna on the device.

2 https://www.comscore.com/Insights/Market-Rankings/comScore-Reports-October-2014-US-Smartphone-Subscriber-Market-Share


Built-in Capabilities 

Meraki offers several built-in capabilities to help understand, track, analyze and monitor location data directly within the Meraki Dashboard. These consist of:

  • Location Data Collection – Automatic cloud-based data aggregation and storage of anonymized location data, used by Meraki built-in features and made available via APIs.
  • Location Analytics – A robust analytics platform is made available within the Meraki Dashboard, included with all Meraki MR wireless products.
  • Location Heatmaps – An interactive map overlay tool available within the Meraki Dashboard and included with all Meraki MR wireless products.

Location Data Collection 

Cisco Meraki Access Points generate a presence signature from any WiFi-enabled device by detecting probe requests and 802.11 data frames, whether or not the device is associated to the network3. WiFi devices typically emit a probe request at regular intervals based on the device state (see Table 1). Smartphones send probe requests to discover surrounding wireless networks, so that they can make the networks available to the user.

Table 1

Device State Probe Request Interval (smartphones)
Asleep (screen off) ~ once a minute
Standby (screen on) 10 – 15 times per minute
Associated varies, could require user to manually search for networks

Probe request interval seen on smartphone OS vendors (iOS, Android, others) – varies greatly based on apps, device upgrades, and other factors4.

Data frames received from all connected WiFi devices and probe requests detected from all devices seen within range (typically up to 100 feet or more) generate “seen device” events on Meraki Access Points. Triple-radio APs have a dedicated scanning radio that listens for probe requests 24×7 on all channels. Dual-radio APs lacking the scanning radio can hear probe requests when WiFi devices probe across all channels. Seen device information is uploaded through the secure management tunnel between the access point and the Meraki cloud.

Meraki’s secure management tunnel is highly optimized for sending and receiving configuration statistics and high volumes of information, and the added overhead from seen device data is close to negligible; the total bandwidth consumed by the management tunnel remains around 1 kbit/s.

Meraki Access Points also detect the signal strength of data frames and probe requests, which can be used to estimate the physical position of the WiFi devices.

Figure 1: Typical probe request from an iOS device – 60 second packet capture taken from Meraki AP, opened using Wireshark.

Location data is largely captured per device using that device’s media access control (MAC) address as a unique identifier. As part of a privacy technique, some mobile operating systems have added functionality that attempts to randomize the WLAN MAC address a device uses, making it more difficult to track by solutions such as Meraki Location Analytics. As the number of mobile devices that implement randomization increases, solutions to detect and locate devices have changed. Meraki provides additional capabilities such as bluetooth information via the Meraki Scanning API, enabling Meraki customers to anonymously include wearable devices as part of their location analytics dataset.

4 Based on empirical evidence from Meraki’s own experiments and those of our analytics partners. This behavior tends to vary greatly based on the operating system and which apps are installed on the phone. For example, if a certain app is very active, it could cause a device that is asleep to probe several times a minute.

Location Analytics 

In addition to the location data collection described above, a powerful analytics platform is made available directly within the Meraki Dashboard in a feature called Location Analytics. Meraki cloud service gathers anonymous location data and runs computations in real time in order to calculate the various client states. Meraki Dashboard then displays key data trends via intuitive graphs that help visualize per-location statistics including capture rate, engagement, and loyalty. These graphs can be toggled between simple and complex views. A calendar function allows the user to zoom in or -out of a given time period to see views as granular as one day (which can show how foot traffic varies and peaks during a certain day) or as wide as several months (which can show seasonal fluctuations).

The goal behind all of the data analytics and graphs presented is to provide a platform for both IT and non-IT departments to understand user presence. By understanding patterns such as foot traffic by time of day and how the capture rate varies across different sites, IT departments can gain a better understanding of network usage and trends. Non-IT departments, such as marketing and business intelligence teams, can gain insights and answer questions such as is my new marketing campaign at site A working based on the foot traffic numbers or do I need to staff more people at site B during peak hours. Some of the different use-cases for which Location Analytics could be useful are highlighted in the following table.

  • Detect total client visits
  • Analyze and optimize window conversion
  • Optimize staffing by time of day
  • Analyze visitor dwell-time and repeat frequency
  • Compare across sites or take averages for sets of sites to understand below or above-average store foot traffic, dwell-time and repeat frequency
  • Optimize and run A/B tests to see if changes in one variable affect outcome of measurable parameters (e.g. capture rate)
  • Analyze data and compare to external KPIs (e.g. average spend per site, average spend per user, average cost per store)
  • Prepare network for weekly or seasonal fluctuations by optimizing policies
  • Correlation of location analytics data with traffic analysis and device fingerprinting data for 360-degree view of user presence, devices and online behavior

For a detailed feature guide on Meraki Location Analytics, please refer to the following knowledge base article: Location Analytics

Location Heatmaps 

Part of Meraki’s location capabilities include the ability to visualize where people are spending time inside a particular location over the course of the day (regardless of whether or not their devices are associated to the wireless network). This data is overlaid on a customer-provided floor plan or Google maps, and can provide organizations with unique and powerful information on foot traffic patterns within an area of a store or building.

Here you can see an example of a large stadium deployment as an event takes place, and attendance grows.

Functions on heatmaps page

Floorplans can be toggled for views on different floors, along with the ability to remove the APs from the display or display different metrics on the APs (e.g. model number, current client count, historic client count, etc). The heatmap page includes a “playback” function – by pressing the play button, it is possible to see how the client density changes throughout the course of the day. Dates can also be toggled to see client density on a specific day in the past.

Underlying Metrics

The heatmaps are calculating using two metrics – (a) the number of devices detected during the time period, and (b) how long those devices dwelled in the area. The colors represent the areas on the map where there is the most “presence.” The intensity is based both on how many devices were detected during the time period and how long those devices dwelled in the area. Areas may be dark red either because there were lots of devices detected, or because there were a few devices that all stayed in the area for the entire hour.

Client Indicators

The heatmap will also plot the calculated location of clients within the wireless network. Grey circles are clients that are not associated to the wireless network that are just probing. Blue circles are clients that are connected to one of the SSIDs served by the wireless network.

Development and API Capabilities 

Meraki offers a variety of application programming interfaces (APIs) that can be used to interact with and interpret data, or make configuration changes in a highly flexible way for custom applications. For example, you may want to create a custom analytics platform that provides a real-time view across all of your retail locations, with metrics that are important to your business.

Scanning API 

Using our globally distributed datacenter architecture, Meraki has created an end-to-end system that can aggregate data from thousands of endpoints for effective collection, analysis, and presentation of this data on the Meraki Dashboard and in custom applications. With built-in analytics, comparisons can be run between different sites and time periods, and Meraki’s network tagging functionality allows for an unlimited variation of comparisons by creating batches of networks that can be grouped together based on district, region, or any other preference. In addition to the built-in location analytics view, the Scanning API enables Meraki customers to detect and aggregate real-time data for custom applications.

The Scanning API delivers data in real-time from the Meraki cloud and can be used to detect WiFi (associated and non-associated) and Bluetooth Low Energy (BLE) devices in real-time. The elements are exported via an HTTP POST of JSON data to a specified destination server. The raw data is aggregated from all access points within a network on the Meraki cloud, and sent directly from the cloud to an organization’s data warehouse or business intelligence center. The JSON posts occur frequently, typically batched every minute for each AP.

Using the physical placement of the access points from the Map & Floorplan on the Dashboard, the Meraki cloud estimates the location of the client. The geo-location coordinates (latitude, longitude) and X,Y location data accuracy can vary based on a number of factors and should be considered a best effort estimate. AP placement, environmental conditions, and client device orientation can influence X,Y estimation; experimentation can help improve the accuracy of results or determine a maximum acceptable uncertainty for data points.

Scanning API

Bluetooth Location Analytics 

Meraki APs with an integrated Bluetooth Low Energy (BLE) radio can detect and locate nearby Bluetooth Low Energy devices. This data is then provided via API to third-party applications. Examples of such devices include smart watches, battery-based beacons, Apple iBeacons, fitness monitors, and remote sensors. 



Analytics Platforms

The Meraki Scanning API is data rich, which enables powerful and highly-detailed analysis. However a powerful platform for storing and analyzing the data is key.

Splunk is a solution that makes it simple to collect, analyze and act upon the untapped value of the big data generated by your technology infrastructure. The Splunk Enterprise product can collect and store data from any number of sources and allow you to build your own analytics and dashboards. You can “splunk” the data from the Cisco Meraki Scanning API using the Presence Data Receiver. The Scanning API is a JSON-based feed of all wireless devices in range of your network, and with Splunk it can now be used as a source of marketing intelligence.

One example of Splunk’s ability to analyze data captured from the Scanning API is to provide a reporting dashboard for analyzing foot traffic. Splunk is able to group visits by a customer and calculate a duration, similar to the functionality of the Meraki built-in Location Analytics, but Splunk allows you to change these settings and define your own analytics dashboard. The video below by a Splunk SE walks through a dashboard built for a customer to track the customers per day, average visit length, return visits, and weekend vs. weekday traffic. This data was produced by just one Meraki MR access point, but this solution is used today by Meraki customers with more than 5,000 access points. Note that this works for Wi-Fi devices as well as Bluetooth devices.

Retail stores with long lines want to track the line wait times in the lobby or check out area, and Splunk can determine wait time using the data from Meraki. The video below walks through a Splunk report that was built for a customer. Note that to identify an area such as a lobby, AP tags are recommended to label the area where people are waiting. By tracking the duration of visits in a specific region, and putting users into buckets such as “no wait”, “5-10 minute” wait. Note that this works for Wi-Fi devices as well as Bluetooth devices.


 Kibana lets you process and visualize Elasticsearch data and navigate the Elastic Stack. Combined with a powerful database service such as DynamoDB, users can store, process and analyze Meraki Scanning API collected data using AWS. A solution guide is available that provides a walk through the process of building a Meraki Scanning API receiver using the AWS Lambda service by Amazon.


Solution Examples


As part of an in-depth customer case study, this video from Cisco Meraki customer Ladbrokes focuses on retail analytics using our built-in Cloud-based Wi-Fi location technology. For this solution, nothing else is required besides Meraki MR access points and a cloud license.

Ladbrokes: The value of analytics

As part of an in-depth customer case study, this video from Cisco Meraki customer Ladbrokes focuses on retail analytics using our built-in Cloud-based Wi-Fi location technology. For this solution, nothing else is required besides Meraki MR access points and a cloud license.

Using the built in analytics dashboard, and the compare option, Ladbrokes can easily compare the performance of their various locations to each other, or to the performance across all locations. View the full video case study here.

The Prada Group uses Cloud4Wi Volare with Cisco Meraki to transform in-store customer experience in over 500 stores worldwide.
Watch the full case study

For more information on The Prada Group and Cloud4Wi Volare, visit the App Directory

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