While mature market CCTV manufacturers in the United States and Europe are fighting to develop new products focusing in High Definition, Megapixel, Video Analytics, long-term warranty, etc., emerging markets (like Latin America, Africa and Asia Pacific) CCTV purchases are 99% defined by price. That explains why Asian manufacturers succeed so well, not only in their internal markets but also exporting security products to countries with the same buying profile.

So, the big question is how can mature market manufacturers succeed in emerging markets? Following the river? Not exactly… lessons must be learned from the regional voice of customer and then the product portfolio adapted for those markets – definitely in this case the same products do not fit all.

But if price is a competitive advantage for products from Asia Pacific, it is possible to create some differentiators that make real differences for the customer and swing some advantage back to mature market manufacturers. Many times they are willing to pay more for the added benefits – local inventory (or quick delivery) and local warranty (or free warranties) are key differentiators, but product localization (language translation for user interface and technical documentation) also go a long way to making inroads.

Selling CCTV products in emerging markets is very challenging but not impossible – we just need to hear the voice of the market and deliver those differentiators.

Learn more about CCTV in YOUR Emerging Market with a FREE Consultation.

Do you do business in emerging markets, what other differentiators should be considered? Let us know in the Comments area below.

Most video analytics operate by simply detecting pixel changes or motion on the camera view. This is useful in low activity settings (like a perimeter fence) where not much happens and security personnel want to pay attention to every activity. However, in busy retail, simple motion-based analytics produce too many false positives. Users looking for when an item on a shelf moved will get hits for everyone who walked in front of that shelf.

In Foreground/Background Separation analytics the software analyzes the video and separates foreground and background motion, people vs. assets, and records those movements as different object types. So when a user wants to see when merchandise leaves the shelf, they do an asset search, looking only for background activity. This results in fewer false positives – getting you to the video you need faster.

For instance, a loss prevention Investigator wants to monitor a rack of expensive, high-theft handbags. Simple motion-based alarms alert him every time a person walks between the camera and the shelf. With Foreground/background analysis, the Investigator defines an asset alert (focus on background activity) and only receives alerts when the merchandise moves.

Additional parameters, allow him to tune the alerts to differentiate between normal customer shopping behavior and a shelf wipeout, for example.

What other aspects of Video Analytics would you like to learn about? Post your question in the comments area.