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    Joshua Bowcott
    Empower and Delight Customers by Enriching Self-Help and...
    Entry posted March 16, 2017 by Joshua BowcottWhiz, last edited April 4, 2017 by eleepHero, tagged Best Practices, Product / Product Release 
    Empower and Delight Customers by Enriching Self-Help and Automatic Engagement, 3 of 4

    We have discussed what it means to realize value with the IoT Enabled Time to Value process. We also discussed how Self-Serve Registration and Increased Visibility gives insight into your customer. But how do you turn this into cost savings and customer retention? The data coming from your connected devices, when harnessed properly, will allow you to grow revenue, reduce cost and provide customers with a great experience! Today, we will look at steps three and four on the maturity curve and see how IoT data will truly unlock more potential for your business. Let’s dive in!

    “IoT Enabled Time to Value – A Multi-Step Approach

    Enrich Self-Help

    Deflection is one of the key measurements for cost saving in a Contact Center. Data from a connected device exposed through Self-Help services can improve your customer’s ability to self-service. Through customers sharing relevant and detailed device data about the current state of their device, the system can leverage automated systems to make recommendation and enable customers to take action. Using IoT Data, brands can surface self-service tools such as knowledge, embedded videos, installation instructions and configuration settings when responding to  customer questions.

    For example, a recently purchased new refrigerator. Upon activation there seems to be a wide temperature fluctuation in the main compartment. The consumer’s question about how to properly configure multiple zones within the refrigerator can result in a response specific to the make, model, installation date and current state of operation. The consumer could also receive detailed instructions on how to properly configure the refrigerator and a checklist of related maintenance items to check; for example: verify the air intake area is not blocked and that someone did not recently place a hot container in the compartment, both of which may causes wide fluctuations in temperature.

    IoT data integrated into the response to the customer’s inquiry enables brands to deliver a more detailed and personalized response.    

    Now, what if the brand wants to provide an experience where the customer does not need to ask for assistance? What if the IoT enabled device could log a service request on behalf of the customer?

    Automatic Engagement

    At this point in the value model the brand will be considering a change that is transformational to their business engagement model! The brand shifts from a model that is reactive, where IoT data augments an inbound interaction, to a proactive model. In the proactive model inbound IoT originated interactions are equivalent to existing channels supported by the contact center. For example: in addition to channels like chat, email, social and phone calls, there are now “IoT Channel” interactions originating from connected devices streaming into the contact center. Contact center managers now need to align service levels and agent resources to support the new IoT interactions.

    If we continue with the refrigerator example above; after three months of use the consumer receives a proactive notification email stating that based on usage it is time to replace the water filter. Along with this notification are directions to the closest brick and mortar store to purchase the filter and a link to an on-line store. The notification may also include a link to a “how to” installation video that will guide the consumer through replacing the water filter.

    In this example, the IoT device created an incident based on water flow usage. The brand automatically engaged with the customer, based on the IoT data shared and defined business processes, thereby preventing an inbound call about low water flow, where to purchase a filter, and how to install a replacement filter.

    Brands enabled with IoT data can decide whether they wish to deliver an augmented inbound experience or make an investment to deliver a proactive experience.  Ultimately the customer and the business win!


    In my next blog, I will explore using IoT data to do automated self-solve and the possibilities with preventative and predictive maintenance.

    In the meantime, if your organization is thinking about (or already doing it!) proactively using IoT data, please leave a comment and share how you’re approaching a solution. If you have questions, share those too! We would love to hear from you.