Industrial IoT

How to Leverage IoT Session Analytics to Understand your Connected Product

3 min readThe definition and analysis of sessions take different forms within various analytics tools, [...]

3 min read

The definition and analysis of sessions take different forms within various analytics tools, and in many cases offer compelling KPIs that help businesses make more meaningful decisions by analyzing changes over time. To start with, let’s briefly review the concept of sessions in regard to web, mobile and IoT analytics:

Within web analytics, sessions are defined from the perspective of website visitors. From the moment they land until they leave a web site – one can interpret the aggregated statistical data about the number of pageviews, clicks, impressions etc.

With respect to mobile analytics, sessions are defined as a single period of user interaction within an app. Sessions then serve as containers of measured activity (e.g. views, errors, app crashes & behavior flows, transactions, etc.).

Within the world of IoT analytics, the concept of sessions is more complex and flexible as it can take very different forms depending on the nature of the connected products, their applications and the desired outcomes. The primary goal would be assess product performance and behavior between various operational and usage states.

Some examples of Sessions Analytics Use Cases across various IoT verticals

IoT Commercial & Industrial Equipment

  • Time-to-Fail Analysis – assess product health from start of operation to the time when a first fault or potential failure state is observed. The manufacturer has the flexibility in defining the potential types of fault/failure events, as well as use the platform’s machine learning capabilities to identify new failure states.
  • Production (Operation) Cycle Analysis – statistical analysis of various time-series events between operation_start and operation_stop states to characterize product behavior during a production cycle, as well as compare the behavior between cycles and across products.

Industrial equipment manufacturers can use these KPIs to evaluate asset utilization, boost asset efficiency, observe degradation and trends, and upsell new services. Other examples include monitoring product performance between different system modes (or states), comparing manufacturing batch runs etc.

IoT Consumer Products & Smart Home

  • Customer Activity Analysis – understand the behavior of a smart home solution between door open/close, panel on/off, door lock/unlock, to improve product automation, boost customer experience and highlight anomalies.
  • Behavior Profiling – profile consumer interactions  with connected product and mobile app to better understand what is happening within a usage window, e.g. issues with connectivity, anomalies within a usage session, statistics of various product ‘cycles’, etc.

Using Session Analytics to Drive Business Outcome

The same way that web and mobile session analytics tools are used to ultimately increase traffic and boost conversions, IoT manufacturers and solution providers can use mnubo’s IoT Session Analytics library to achieve powerful business results:

  • Reduce customer churn by enabling the analysis of (re)engagement rates, disconnection rates, evolution of customer behavior over time (cohorts), etc.
  • Improve product usage by allowing the comparison of behavior between production batches, operational routines and sequences, and other usage windows.
  • Increase customer engagement by facilitating new business models and services such as usage-based pricing strategy, human-centric product experience etc.
  • Lower costs of operations by improving processes, optimizing resources and proactively addressing potential product issues and service downtimes.

Here are all the industrial IoT insights

Interested in understanding how IoT analytics and insights libraries such as Session Analytics can help accelerate your connected product strategy? We’d be happy to show you.