A lot of IOT Analytics use cases are centered around benefits to IT groups – however, good analysis of machine data is tremendously useful for many other stakeholders inside an organization. Today, we will focus on how our Analytics are tremendously useful for Product Marketing groups.
The central theme is the notion of ‘feature propensity’ – that is how much (or how little) customers like various features in a product. In a “non-IOT” scenario, product managers have very little insight into how well a new version of a product is received after it is shipped. They have to rely on semi-scientific surveys and conversations between sales reps and end-customers to gauge the popularity of features.
However, once these products are connected, and operational data regularly parsed and analyzed, one gets a detailed and granular view of the install base. Numerous powerful insights can be gleaned by studying this data and filtering it by various parameters like version number, configuration, and so on. A Medical devices manufacturer used Glassbeam’s solution to get granular insights into data surrounding their product’s performance, including:
- Number and length of procedures conducted by hospitals over days, weeks, quarters etc
- Usage Reports that identify key button presses and duration of presses by different doctors, hospitals and surgery centers
- Fault metrics by type of fault across the install base
Acting on these ANALYTICS, the company was able to refine it’s product roadmap to align more closely with customer needs – a tactic that is now paying great dividends in the form of increased customer satisfaction.