Analytics for bricks-and-mortar retail by Turnstyle

Turnstyle is a startup with a unique vision: to deliver to physical retail stores, a.k.a. bricks-and-mortar, the analytics equivalent of what has been available online for a long time.Turnstyle website home page

The holy grail is providing actionable business insights that enable merchants to deliver value to their customers, and for those customers to derive benefits and higher satisfaction from this effort.  Everybody wins.

What do customers want?  First, they seek their needs being met by relevant products and services available at the right time, at the best possible price. They also want convenience, as in ease of procurement.  Great service, delivered as friendly and timely assistance. Price breaks, whenever promotions are available, without having to ask.  Also, some customers may appreciate helpful suggestions of other items they might be interested in.  All of this is what makes online retailing so successful.

Analytics for bricks-and-mortar retail

So, how do  bricks-and-mortar retailers figure out how to satisfy their customers’ needs in a timely, time-efficient, convenient and price-sensitive way?  By learning about their customers’ needs and habits: what attracts their interest, where they spend time in the store, and what information they seek to make informed purchasing decisions, and possibly other aspects of their lifestyle that shape who they are and what they care about. That’s why retailers need information about their customers. And that’s what Turnstyle delivers to them.

Turnstyle Solutions approaches the problem in three different ways:

  1. by detecting customers’ physical presence at the stores to learn about shopping patterns: how often they come in, what days, at what times, how long they stay.  Whenever possible, also learning what they do inside the store: what categories they visit, what attracts their attention
  2. by providing customers access to free Wi-Fi service at some stores: in exchange, they log  in with their social media accounts, voluntarily enriching their personal profiles
  3. by aggregating customer data across a larger area with multiple merchants, providing deeper insights into personal interests and buying habits, so as to generate actionable information

Participating merchants receive periodic reports detailing findings and actionable insights, enabling them to cater to their clientele with services and offers that speak, not just to customers’ habits and needs, but also to their lifestyles.

A great example is Happy Child, a restaurant and bar on the trendy Queen Street West neighborhood, downtown Toronto.Happy Child on Facebook For instance, through Turnstyle, Mr. Fan Zhang, Happy Child’s owner, learned that, in November 2013, 170 of its customers visited local clubs, 250 went to the gym, and 216 come in from the upscale Yorkville neighborhood.  With this information in hand, Mr. Zhang decided to launch a promotion catering specifically to customers’ taste and lifestyle: workout  tank tops bearing Happy Child’s logo. It was a hit.

Another Queen Street restaurant, Czehoski, chose to hire an 80′s music DJ on Friday evenings when they learned that almost two thirds of its patrons were over 30.  This insight was possible after users of Czehoski’s free Wi-Fi service logged in with their Facebook accounts.

RSquared Cafe, RSquared at Yelpa Queen Street coffee shop, provides free Wi-Fi to its clients, and in exchange, enables some personal demographic information to be collected when they log in with their Facebook account.

Rac Boutique, a women’s clothing store based in the Yorkville neighborhood offers fashion and lifestyle accessories.Rac Boutique home page  They also benefit from a deeper understanding about their clientele’s demographics and lifestyle, which helps them tailor their offerings accordingly.

In each case, the goal is to enable merchants to better understand their customers, so as to more effectively meet their needs and expectations.

Tackling Personal Privacy

Customer identities are not used to learn of their movements;  only their devices’ MAC address is collected, and all behavior data is aggregated.

As we know, a MAC address is simply the unique identifier of a mobile device’s Wi-Fi interface.  Given the widespread use of Wi-Fi connectivity on mobile phones and tablets, it can be used as a de-facto identifier of these devices.  Though by themselves MAC addresses are not related to any personally identifiable information, they can complement information collected by other means.

Naturally, the emphasis on building richer customer profiles raises personal privacy concerns. As it has been observed by privacy advocates, time and location may enable inferences about a person’s habits or needs. For example, it could be possible to infer that somebody has a medical condition if someone were to monitor visits to clinics or specific doctors’ offices.  Given such potential, it’s very important for providers of customer behavior analytics to clearly and transparently state the rules they abide by for handling this data.Future Privacy Forum

Companies covering new ground, with innovative technologies that may have societal impact beyond their intended target, clearly see the need for proactively and transparently subscribing to a code of ethics that unambiguously reassures the public.  For instance, Turnstyle’s adherence to the Future of Privacy Forum guidelines is the correct approach by a company concerned about their social responsibility over issues of personal privacy.

This is worth noting: Turnstyle has set up a “do not track” option on their website, that allows any concerned user to explicitly opt-out of future data collections.  In addition any past history that may have been collected about  them is deleted.

As societies grapple with the implications of applying innovative new technologies, this is clearly a good approach for balancing the benefits of innovation with potentially undesirable societal implications.

Looking at the future

Retail has always been a competitive battleground.  The shift to online retail by many consumers will continue to weigh heavily on merchants large and small, given the convenience of online shopping.

As we know, bricks-and-mortar retail offsets online shopping with unique advantages of its own.Clothing store endcap Among them: the ability to touch and try the items, or simply to see them under different lights.  The immediacy of the purchase, as customers can take the items home right now!  The ability to be assisted in person by a knowledgeable salesperson, or the ability to enjoy a product or service in a welcoming environment (think your favorite restaurant).

All of these advantages can be sharpened and emphasized when merchants learn what really matters to their customers, what their cultural and/or personal preferences are, what would increase the positive attributes of that next customer experience.  That’s precisely what innovative technologies such as location-based analytics provide.

Behind the scenes

Navizon’s hardware-based products automatically compile the raw data that makes these insights possible.   Navizon I.T.S. (Indoor Triangulation System) detects the Wi-Fi signals emitted by devices like smart phones and tablets, triangulating their location as they move around a store, or their proximity to a desired spot, or simply counting their numbers.  Neither direct connectivity to Navizon I.T.S. nor installation of mobile apps are required.  Notably, no personally identifiable information is collected from anyone.

Easy-to-deploy and integrate products such as this, provide flexible building blocks for implementing innovative applications in the real world.Navizon I.T.S. (Indoor Triangulation System)

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Location-based In-store Analytics in Retail

Location-based analytics in physical retail environments provide business insights valuable to stores and brands by analyzing in-store customer behavior.Father and daughter at the supermarket

All retail environments, both physical and online, are concerned with understanding what customers do inside their stores.  For bricks-and-mortar stores the questions may include: at what time do customers come in? Do they rapidly dart in and out seeking specific items? (E.g.  milk or bread.)   Do they linger, exploring different sections?  (E.g. shoes, lingerie, cosmetics and the latest jeans.)  Do they notice and stand in front of new displays?  Do they pay attention to endcaps?  Women's clothing store windowDo they appear to scan various sections in search of something?  What percentage of them go through the checkout (a conversion)?  Or simply exit the store without buying anything?  Are visitors’ paths through the store similar?  Are “shallow” visits prevalent?  And if so, why?  Does it happen that potential customers walking in the store take a peek at the length of the checkout lines and leave because they are too long?   What times during the day/week does this happen?  And by the way, are these new or repeat customers?  How often do they return? At what times?  Do they come on Saturdays? Or right after work throughout the week?  It’s a long list.

Data analysis enables physical store managers to

  • segment their customers according to buying behavior, such as time of day or items basketSupermarket laundry products section
  • learn where customers spend their time: they enter the store, visit specific departments, given aisles seeking product categories, then looking at specific items before purchasing (or not)
  • understand what sections of the store are less visited, to inform layout changes
  • learn the effectiveness of their cash/wrap section at busy times by measuring queue lengths
  • assess the success of in-store promotions and marketing efforts
  • measure the impact on sales of long lines at the registers during the busiest times of day.

Brands also benefit greatly from this data.  Every brand tries to stand out.  The best placement is often off-the-shelf, on a dedicated display or an endcap where the brand and its products are showcased.  Fashion clothing store windowHow many customers actually seek it? How many stop by?  How many others looking for other products in the same category pay attention to it?  Is there correlation between the number of interested visitors and increased sales?  Most definitely a brand will avoid being displayed in a section with few visitors, or with plenty of visitors at the wrong time of day (e.g. dinner foodstuff when visitors come in for breakfast items).  Clearly, analytics based on measuring visitors behavior can be very relevant for product placement, promotions and marketing campaigns, most of which often command large budgets.

How is data collected?

Achieving the greatest insights requires following the average customers at deeper levels of granularity, from the store, down to section, aisle, category and specific products within it.  Woman using smartphone at supermarketThe traditional way to do this relies on trained observers (people) deployed through the store, discreetly observing customers’ behavior, recording their observations, often aided by video cameras.

Enter location technology-based analytics, enabled by the proliferation of smart phones: we can track people’s whereabouts by determining the location of their mobile devices over time.

Collecting device location data for retail analytics depends on several key factors:

  1. the ability to track visitors unobtrusively, without requiring people to connect to any system or activate mobile apps on their devices
  2. the ability to track all device brands
  3. obtaining location accuracy with granularity down to the aisle level, covering multiple floors and buildings, if necessary

Why location accuracy matters

Detecting and triangulating a device’s position by sensing the signals emitted by its Wi-Fi radio is a very practical approach, given the widespread availability and use of Wi-Fi services inside buildings.  Also, many people never turn off their phones’ Wi-Fi radio.  A location accuracy of about 2 or 3 meters is possible, enabling aisle-level  granularity.

The question is often asked as to whether it is possible to use a store’s existing Wi-Fi infrastructure to collect the data.  Clearly, it is possible to collect some data, but unfortunately, location accuracy will drop down to 10-12 meters of worse, making aisle-level granularity impossible.  The reason why is that existing Wi-Fi systems are deployed for connectivity, not for location. Access points located in the center of rooms or sparsely distributed through a space make it nearly impossible to triangulate devices’ location with acceptable accuracy.  Collecting section-level visitor counts is possible, but aisle-level location is not.

In-store analytics

Collecting the right data is only the beginning.  It must be aggregated, processed and presented to deliver the desired insights.   Navizon customers provide several great examples.

They deliver real-time in-store shopper behavior analytics, enabling stores to get to know their customers by providing store and brand managers with actionable insights. Supermarket produce sectionThe systems being deployed at some of the largest retailers in North America, South America, Europe and Asia leverage Wi-Fi technology to deliver deeper analytics to retailers, helping them improve their store execution performance and merchandizing effectiveness.

They provide real-time, in-store shopper behavior analytics with aisle-level accuracy and seamless POS integration. This lets retailers follow their customers through their in-store experience: where they went inside the store, how much time they spent in different areas of the store, observe what captured their interest and ultimately what they puchased.  This type of analytics, which has been available for online shopping, is now being brought to the bricks-and-mortar world powered by Wi-Fi technology.

Behind the scenes

Navizon’s hardware-based products enable automatically compiling the raw data to deliver all these insights.  Navizon I.T.S. (Indoor Triangulation System) detects the Wi-Fi signals emitted by devices like smart phones and tablets, determining their location as they move about, or their proximity to a desired spot, or just counting their numbers.

Privacy is always a concern.  However, note that it is impossible to identify who the people are or obtain their phone numbers.  No personally identifiable information is ever collected. Only device’s unique identifiers, their MAC addresses, which can be easily hashed or scrambled for greater privacy protection.

To collect location data, sensors are placed throughout a store (e.g. in every corner), to detect mobile phones whose Wi-Fi radios are active.  The system estimates in real time the sequence of locations as mobile devices move through the site.  Average location accuracy of about 2 or 3 meters is sufficient to know whether the device is on a specific aisle, standing in front of an endcap or queuing at the checkout line.  A new era of retail analytics is now possible.Navizon I.T.S. (Indoor Triangulation System)

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Indoor Location at Big Brother Brasil (BBB14) by Navizon

The new season of Big Brother Brasil  began on January 14, 2014.

Big Brother Brasil, also known as Big Brother, Brazilian Edition, is the biggest and most popular reality TV show in Brazil, and one of the most talked-about in Brazilian TV history.  The current season is BBB14.

Produced by Rede Globo, or simply TV Globo, the show is about a group of complete strangers that share a house for up to three months, relentlessly followed by TV cameras, without any contact to the outside world: no access to TV, radio, computer, phones, newspapers or outside people.  Housemates, referred to as “brothers“, compete with each other, the object being to be the last remaining contestant in the House.

The TV audience follows the brothers’ every move via live video through various websites. They also comment and vote.

BBB14 brings a new dimension to the show: the location of all brothers is monitored in real time with one-meter accuracy.  The audience can now follow everybody’s location throughout the House via a live feed from SALA DE CONTROLE (the Control Room).

Who will be the winner of BBB14?  We’ll just have to keep an eye on everyone, wait for three months and see.  It will be exciting.

Behind the Scenes

How are brothers tracked? Each of them carries an RF (Radio frequency) device, a Wi-Fi tag, that enables locating them in real time and tracking their movement throughout the House over time.

Navizon’s real-time locating system (RTLS), Navizon I.T.S. (Indoor Triangulation System) provides location data which is displayed on TV Globo’s website. Viewers can now tell who is by the pool right this minute.  By combining a RTLS and Navizon Wi-Fi tags, locating and tracking people and resources for entertainment or commerce through a physical space is now possible. Another first for TV Globo!


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