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Facebook plans to track which stores you shop, report to advertisers.

6/21/2016

 
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​Privacy advocates and Facebook have been at odds almost since the service made its public debut, and the company’s latest plans to expand its advertising service aren’t likely to play well with anyone who values controlling their own digital footprint.

​Facebook has added new measurement and information tools that make it easier for FB users to find businesses relevant to their interests, according to Adweek, while simultaneously handing those businesses an unprecedented amount of information about the customers that walk through their door.

Here’s how the system works:
If you have location services enabled on your phone, FB will track which local ads it serves you, as well as your response to those advertisements. If you visit a partner store after seeing an ad, FB will know it. This itself isn’t necessarily new; Google debuted a similar service back in 2014 to track whether or not ads drove foot traffic to specific businesses. What is new, however, is FB’s ability to track whether ads result in actual sales.

Adweek reports:
Along with measuring foot traffic, FB is also adding a way to connect which ads lead to actual sales. An "offline conversions API" will allow businesses to match transaction data from a customer database or point-of-sale system with Ads Reporting. The tool will also provide insights about demographics of the people who make a purchase.

FB is also adding a "store locator" option for local ads, which shows address, hours, phone numbers and estimated travel time.

Here is a demo for how the latter function will work:

​As for FB’s visit tracking and data collection, the company doesn’t plan to share individual visitor information with any of its partners. But that info may be easy to extract, depending which demographic data the FB chooses to share.
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For example:
If a store knows that an unidentified male between the ages of 25-34 entered the store at 3:45 PM and left at 4:20 PM, the store could compare the visit against cash register logs to see if a male checked out by credit card around 4:17 PM. If yes, that person’s name can be run through other commercially available databases for a probable match. This type of data mining isn’t unusual. It is the way stores create profiles on their customers.

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