IoT communication: Four ways your products talk to you

Your products are telling you how consumer IoT can achieve mainstream adoption. Are you listening to them?

October 13, 2017

5 Min Read

By Jess Groopman

Product companies and OEMs have been working on re-configuring and re-imagining their products with sensors, network connectivity and IoT communication capabilities for years now. Nonetheless, the consumer-facing side of the Internet of Things has struggled to gain mainstream adoption; none of the world’s major consumer electronics markets have reached more than about 20% adoption of IoT tech. While consumers themselves cite privacy and security concerns, they also express significant interest and appeal in home automation products and services, so why the breakdown?

One reason is reflective of the market today: Manufacturers and smart home service providers are struggling to adequately listen to what their products are communicating. Given the complexity of connected product hardware, software and experience design, this isn’t surprising, but understanding the what, how and where to listen to IoT communication is an essential first step.

Performance: Connected products communicate their status

The most obvious signals manufacturers receive via IoT communication are around performance. While certain basic machine-to-machine (M2M) telemetry and remote sensing have been on the market for decades – on/off, temperature thresholds, fuel levels – managing these data effectively remains a paramount challenge for connected product manufacturers. Performance data flowing off smart home devices are essential, not just for performance monitoring but for ongoing product and service innovation.  

  • Functionality: Are software, hardware and/or firmware performing as designed, adhering to expectations and regulatory compliance?

  • Anomalies: Are products, software and hardware exhibiting abnormal behavior? Where are these signals occurring in the technology stack, and what additional testing or patches should be applied?

  • Maintenance: What areas are showing signs of faltering, and how can these data optimize service team preparedness and minimize or prevent downtime? Over time, how can historical data inform probability of future failure and optimize pre-emptive support?

[See Jessica Groopman speak on UX and AI at Smart Home Summit this November.]

It’s also critical for product companies to recognize insights within individual devices and in aggregate, across all devices. A single product’s performance data is essential for real-time functionality and support, but aggregate insights across a fleet, specific region or customer segment can also yield population-level or historical insights – both useful for running any kind of machine learning on product data.

Customer interactions: Connected products communicate on behalf of customers

Understand products as interactive touchpoints in which every interaction had with the product serves as a signal about that customer, their intent and over time, their preferences and behaviors. It used to be manufacturers were altogether blind to product experience after the point of sale. Connected products, mobile apps and analytics help shed invaluable light on the obvious richness of customer interactions.

Listen for:

  • What features are used and how

  • Where products or certain features are used

  • What other brand channels are used in conjunction

  • Signs of friction in user workflows (e.g., app uninstalled)

  • Signals of intent in user workflows (e.g., shopping cart abandonment)

  • Signals of social intent (e.g., connect with others using the same device)

  • How product interactions inform marketing, advertising and sales opportunities

Product interactions: Connected products communicate greater context

Any smart home product or service provider worth their salt is not merely adding a mobile app to their product; instead, they are re-orienting the product as a hub of interoperability with other devices and other services. In the age of personalized marketing, proactive sales and all manner of data-driven enterprise automation, context is key. Product companies that listen for the following are gaining more context than ever possible through traditional products:

  • What other devices or products are communicating with your product (via APIs, standards or apps)?

  • How are users integrating product data or services and for what use cases?

  • What are users wanting to connect but cannot?

  • How might other devices add value to the product? (e.g., Alexa integration could improve hands-free or voice enablement using less resources than a proprietary build)

Product innovation: Connected products communicate opportunities for improvement

One of the most compelling opportunities of connected products is how hardware/software configurations enable improvement and appreciation – not depreciation – over time. Product performance, customer interactions and product interactions all inform areas to improve. Some can even be delivered through an over-the-air software update, as we have come to expect of our smartphones and as Tesla has rolled out across its vehicles. Other improvements may be rolled into longer-term R&D initiatives and inform productizing, partnerships, new revenue opportunities, customer strategies, etc.

Audio manufacturer Marantz uses speaker data to inform product innovation. Marantz’s connected audio speakers enable the company to understand how its customers use the product. It knows where the product resides, how often it’s turned on and off, and what music is played from which streaming services. These data have already informed simple tweaks to product development and marketing, such as the introduction of a shower speaker line and a rugged speaker line for garage purposes. The company uses this data for proactive customer service, as well as for cross- and upsell campaigns to great effect. It is even considering productizing B2B streaming data to music streaming companies.

If there is a single takeaway, it is that product companies must rethink the role of their products. Products are no longer static endpoints. Your product is now a hub of context. Whether individual or at scale, interactions and the data flowing from them are foundational to the viability of the product in real time, and over time.

As machine learning and deep learning are applied to pull in myriad other data streams beyond sensor data, it amplifies both the opportunity and the challenge of learning from and predicting context. Connecting products is really only the beginning; listening, interpreting and integrating what they’re communicating is where the tangible benefits lie – for your customers, your business and your ecosystem. 

[Smart Home Summit is where the smart home industry’s savviest players meet to forge partnerships and make the connected home a global reality. Visit the site to learn more about the agenda, speakers and networking opportunities.]

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