There are many articles extolling the virtues of IoT technology. They discuss its different features and benefits, how it will revolutionize the world, and show how it will save lives. You read about businesses increasing profits, reducing pollution, increasing crop yields, and save rhinos from poachers in Africa. These are all true. However, if you are building an IoT product; or, perhaps, thinking about creating a new product, it’s important to understand the reasons behind the exponential growth of IoT. Who’s funding the technology, and why?
Conversational Analytics is the data from IoT users’ human-to-machine (H2M) conversations – including chatbots, where the “machine” is actually a database. For example, when you control your Nest thermostat with your mobile app, you leave a digital “paper trail.” Google, who acquired Nest in 2014, knows what temperature you like to run your air conditioner at, when you are most likely to turn it on, and when you typically turn it off. They also know when your wife changes the temperature and you change it back.
This data goes into the Google marketing engine and helps them display relevant ads on your web browser; the ones you are most likely to click on and purchase something. For example, if you like running your air conditioner at a steady, Arctic, 65-degrees Fahrenheit, and your wife (when you’re not looking) bumps it up to 75, the next time a heat wave is in the forecast, you may see ads for iced tea or air conditioner filters. Your wife, on the other hand, may see ads for sweaters and down comforters. Having this insight into your actual behaviors provides Google with the ability to create a new revenue stream for themselves, which far outweighs any profits they could make on sales of Nest thermostats themselves.
There is a saying that “data is the new oil.” The data you receive is so valuable that some companies are actually giving away smart products, for free or at cost, in exchange for receiving the data they generate from users’ interactions with them.
Conversational Analytics can also be used to save lives, as in the following example. There is a company in Europe that had a problem with forklift accidents. The problems weren’t actually occurring in Europe, where they had high safety standards, but rather at their offshore facilities in developing countries, where the local worker safety laws were different.
Keep in mind, when it comes to something as serious as a forklift accident, being notified after it happens, is like closing the barn door after the horse has already escaped. It’s already happened! The real solution would be to stop the accident from happening in the first place!
In order to do that, we need to understand why these accidents keep occurring. We know the forklift hit something or someone because it’s pretty obvious. However, how many near misses has this driver had before he finally hit someone? Why were there near misses? This kind of data is not being reported at all, for various reasons. So, if you don’t have the underlying data, you can’t solve the problem. This company turned to intelligent IoT messaging’s Conversational Analytics to help them solve the problem.
They installed inexpensive proximity sensors on every forklift, and beacons in the safety gear the people wore, such as the vests and hard hats. Any registered violation (meaning, near miss) that was picked up by the sensors, got sent immediately to the shift supervisor and plant manager and was recorded in the official company log book.
Almost immediately, it was very clear to see which drivers needed additional training, and in what areas they needed to focus. Implementing IoT technology helped this company increase the quality of their work and reduce waste by cutting down on damaged goods, as well as reducing injuries and saving lives.
Here is an example of how Conversational Analytics helped a business beat their competition by improving their product, resulting in an increase in revenue. The company makes robot vacuum cleaners in Asia. One challenge with vacuum cleaners is that they’re not exactly conducive to having workable phone conversations anywhere near them! This company deployed Intelligent IoT Messaging technology (which includes an intelligent chatbot that’s able to communicate with people over any standard messaging, social media, or chat channel, such as SMS, Facebook, Twitter, WhatsApp, Skype, etc.), and in the first 24 hours, their system recorded many commands to “shut up,” with some colorful metaphors inserted in between those words.
They wanted a mute feature! Within 40 minutes, this company was able to actually deliver this “differentiating” feature, while the competition wasn’t even aware of the need! Think about it! Within 40 minutes of analyzing their report, a company was able to implement a customer-affecting change to their IoT solution, worldwide – while their competition was completely in the dark that the need even existed! Talk about speeding up development time. If you implement this kind of technology for your IoT solution, how will your competition even be able to compare with you?
In conclusion, there are many benefits to IoT technology. For the end user, the benefits are pretty obvious. It increases the quality of their lives, by saving them time, money, reducing hassle, or bringing them closer to their loved ones. For the manufacturer, IoT with Conversational Analytics helps them create uncapped revenue streams by providing insight into people’s wants and needs, many times before the end users even know that the needs exist!
My question for you is, what kind of data do you wish you knew about your customers?
Struggling with IoT? Don’t know what your strategy should be, or not seeing the business results you need from your current strategy?
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