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How to Measure the Impact of Wearables on Mobile User Experience

By Special Guest
Michael Tanner, VP, Products and Marketing, Carrier iQ
September 14, 2015

With the advent of millions of apps and new wearable connections, our smartphones have morphed into personal hubs that increasingly control other devices. Wearables are just the latest devices that monitor, track, entertain, and inform us about everything from our schedules to our heart-rates, sleep patterns and fitness. Coupled with an ever-increasing number of device-resident apps that serve up information, these devices have are beginning to significantly improve our daily lives.

Product Category

2015 Shipment Volumes*

2015 Market Share*

2019 Shipment Volumes*

2019 Market Share*

Wrist wear

40.7

89.20%

101.4

80.40%

Modular

2.6

5.70%

6.7

5.30%

Clothing

0.2

0.40%

5.6

4.50%

Eyewear

1

2.20%

4.5

3.50%

Ear wear

0.1

0.10%

0.6

0.50%

Other

1.1

2.40%

7.3

5.80%

TOTAL

45.7

100.00%

126.1

  100.00%

Source: IDC


For operators and device manufacturers, the adoption of different wearable devices compounds the challenge of understanding how customers experience mobile products in the field. Wearables connect to a more finite number of smartphones, and transmit data over an even more finite number of mobile operators. Consumer satisfaction results from how well everything interacts – from smartphone and wearable stability to network speed, app stability, and the reliability of each paired wearable device.
 
Measuring the actual performance of wearables in the field is challenging, not only because it varies by each mobile smartphone, but also by location, which apps are in use and over time. Some operators and manufacturers have sought a way to use analytics sourced directly from consumer devices to measure how well, and in what context their wearable products perform.


In practice, the data needed from individual devices for business decisions varies widely depending upon stakeholder needs. Supply chain teams, for example, might be interested in device power metrics associated with a tethered smartwatch model or the degree to which Bluetooth or other connections drain power over time in the field. A customer care team might want to understand whether a connectivity issue is a device or network problem, a smartphone or wearable device problem, or if some combination of specific connected devices and apps create performance issues. Or, a marketing group might be more concerned with how overall consumer device performance impacts churn or net promoter scores.


Today, each mobile use case drives stakeholders to find their own methods of sourcing data, with each relying on their own processing upstream, or upon aggregating the data into data lakes for upstream processing. Over the next several years, smartphones are projected to have as many as 100 individual device-resident services that each track mobile activities, according to Gartner research. As the number of deployed devices and different sourcing techniques grow, cleaning, filtering, and reporting across this wide and varied data set quickly becomes costly, both in terms of time and compute resources needed.
 

The best way to efficiently gain a true 360-degree view of wearable performance is to source a single and consolidated view of smartphone performance and wearable telemetry. This will allow the performance of wearables to be understood in the context of location, device stability, network data throughput, network/roaming usage, and other metrics. Implementing such a comprehensive approach allows operators or manufacturers to collect a single view of device metrics that is optimized for later use, and that can be used to gage the complete customer experience.
 

To be effective, mobile device agents that source telemetry should include several key capabilities:

  • The ability to provision each smartphone agent over the air, with the option for consumers to opt-in (or out).
  • The ability to manage deployed agents via a centrally-managed device profile that can vary what information is sourced and when that information is to be transmitted.
  • The ability to perform first level data enrichment directly on each mobile device in order to optimize in-transit data.
  • The ability to tie wearable telemetry to other device and network related telemetry, such as throughput, coverage and roaming information, device stability, Wi-Fi and app usage, coupled with location and time, and to use that data to develop key insights to improve overall performance.
  • Flexible privacy assurance mechanisms that can support each individual vendor’s privacy policy, whether deployed by a device manufacturer or a mobile operator.
  • Highly secured, encrypted communications between each device and the data collection points on the network.

Wearable telemetry is critical to integrating wearables fully into the IoT and its Big Data powerhouse. Hopefully we’ll see executions grow even better over time. 




Edited by Ken Briodagh


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