The most important IoT data analytics performance indicators you’ll want to look at after the launch of your product are:
- How many connected products are active?
- How many connected products are inactive, where are they located, and why are they inactive?
- How are connected products moving from unconnected lifecycle states where they are actively connected and in use by end customers (e.g., registered, activated, operated, etc.)?
- What are the consumption or usage rates of the connected products, and when is it time to offer warranty, repair, parts replacement, or replenishment services?
- When will a connected product fail next?
And, in your production phase, the necessary IoT data analytics capabilities include:
- Predictive maintenance
- Geographic analysis
- Product distribution and activity analysis
It’s at the market launch of a connected product when the full power of IoT data analytics begins to emerge. Production deployments can reach tens of thousands of units, or more, so issues of scale become important. The feedback from your products’ IoT data enables executives, product management, operations, and marketing and sales teams to make predictions about connected product performance, including when the product or one of its parts might fail.
And we all know that preventing product failure is more likely to result in a happier, more loyal customers.
For more information on, “How to Optimize IoT Data Throughout the Connected Product Lifecycle,” download our new Ebook: