Tag Archives: Mobile phones

Track Shoppers by Mobile Phone Signal

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How much do you think retailers know about your behavior? If you said “a lot” you are correct – but few shoppers know to what extent retailers know and gather data about them on every store visit. With new technology from retail-tracking start-up company Nomi, retailers will soon be able to track the amount of time shoppers spend in stores, the departments that are visited, and even the displays that cause shoppers to stop in their tracks and perhaps make a purchase.

Nomi uses technology that captures the shoppers’ mobile-device IDs as they enter store locations. The retailers’ WiFi network tracks the mobile phone signals to a 1-3 meter distance, then uses machine learning to calculate spatial relationships. The product can track several metrics of consumer shopping patterns, including: window conversion (% of customers who walk into store off the street), customer loyalty (% of customers who have been to store previously), visit duration (average amount of time in store), bounce and engagement rate (% of customers who leave immediately or stay for a while), visit frequency (how often customers enter store), and device type (type of phone customers are using).

Retailers are already testing Nomi’s product to test window displays and determine which display garners the higher window-conversion rate. Other retailers use the software to track how long it takes for customers’ orders to be filled.

There are possible privacy implications to the tracking software, even though Nomi stated that the unique device IDs it tracks are never tied to personally identifiable information. However, there is no notification given to consumers that their phones and movements are being tracked. This seems to contradict the Children’s Online Privacy Protection Act, which requires that mobile application providers obtain parental consent when mobile apps are aimed at kids under the age of 13. Nomi counters that it is working on an opt-in system that will allow shoppers to identify themselves in return for getting coupons and deals from the retailer.

Group Activities and Discussion Questions:

  1. Bring up Nomi’s company information: www.getnomi.com
  2. Examine competing products from RetailNext (http://www.retailnext.net)and Path Intelligence (http://www.pathintelligence.com).
  3. How do these products assist retailers with understanding consumer behavior?
  4. In teams, have students identify stores that could most benefit from using this technology.
  5. How can the data be used in the short-term? In the long-term?
  6. Discuss in class the privacy implications of this tracking software.

Source:  Ad Age Daily, 2/11/2013

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Hello… What should I buy?

 

It was a busy holiday shopping season. There was a lot to do, and there were a lot of different choices for shopping and products. And with all the turmoil, isn’t it nice to know you never had to shop alone?

In a survey recently conducted by Pew Internet Research, they found that more than 50% of adults used their mobile phones while they were shopping in a store over the holiday season. What did we all do while on the phone during shopping trips? We not only asked our friends and family for advice about a purchase (38%), we also looked up reviews (24%) and prices (25%) for products while we were in the actual store.

Retailers need to beware! The Pew research showed that after looking up reviews and prices, nearly one in five of these mobile shoppers eventually bought the product, but they bought it from an online supplier instead of the physical store. The competition is getting tougher for the traditional brick-and-mortar retailers. Online presence and customer service is critical.

 

Group Activities and Discussion Questions:

  1. Ask students if they have used their cell phones to get advice while shopping? When was the last time? What were they buying? Why did they call someone? What happened?
  2. Have students go to the Pew Internet Research site – http://pewinternet.org/– and access the report.
    • What are five key findings from the report?
    • How could these findings be used in a retail location?
    • Assign different retail locations and products to different student groups. (Example: food, clothing, entertainment, etc.)
  3. Observation project for students:
    • Have students divide into teams and select a retail location to observe.
    • Put together a protocol for the observation. Suggestions: number of people using phone while shopping, by gender, by age, by location, by purchase decision.
    • What are the results from the observations? How could this information be used by marketers?

(Source: Pew Internet Research Center)

http://pewinternet.org/Reports/2012/In-store-mobile-commerce.aspx

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