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Here are some key questions an enterprise should ask when looking to define a consumer centric IoT strategy.
The promise of the Internet of Things (IoT) extends to
almost all industries and markets. Coupled with the power of big data, IoT can
offer massive improvements in messaging personalization and product
customizations through complete customer empathy and supply chain efficacy.
However, starting with IoT and unlocking its value often ends up being a
daunting task for managers. This blog proposes a simple exercise to help design
your IoT strategy and implement a customer and user centric IoT ecosystem.
The typical challenge faced by managers charged with
designing and building the IoT strategy and ecosystem for an enterprise is
often three-fold. First, how should relevant signals be defined, generated and
collected. Second, how should these signals be stored and processed and Third:
How should business value be generated from these signals.
An IoT ecosystem is not only hard to implement but hard to
manage also. These ecosystems are highly prone to problems ranging from
malfunctioning sensors that over or under sample, broken or suboptimal data
delivery pipelines that lose or corrupt data, inefficient or ineffective
processing systems that are not able to derive meaningful insights from the
data and incomplete action and feedback loops that make it a challenge to adapt
the system based on the newly identified insights. These problems make it
harder for enterprises to generate additional business value and increased
customer delight from their IoT investments.
Managers struggling with how to get started with IoT should
follow this simple approach. This approach is based on the fact and
understanding that the strongest potential of IoT will be in the area of
customer satisfaction through deeper and complete customer empathy. Managers
looking to make progress should try and fill in the blanks as given below:
If I Knew ___ about my customer/user, I would ___
What information or insight into your customer or user’s
profile would enable you to make your product or service the best available
option for your user built in such a way that it has the highest potential to
delight them? Sensors can be used to collect this information about your user’s
profile and this information can then be used to either design better products
and services or offer a better personalized and contextualized experience.
For example, Redbox; the movie and game vending machine
company could use information about a user’s demographics such as gender, age,
occupation, education etc to better design the collection of movies offered at
each vending machine. From the recommendations sent to the user offline (email)
or shown when the user is at the vending machine to the offers made to the user
while they are browsing movies and games can be better customized and optimized
for conversion.
By placing sensors in these vending machines that can track
the temperature, humidity, precipitation, foot traffic patterns and user
characteristics, Redbox can instantly customize the look & feel of the
vending machine, the messaging displayed on the screen around and inside a user
session and the stock mix to better serve the predicted demand at a specific
vending machine location.
If I Knew My Customer/User was doing or planning to do ____,
I would _____
What information or insight about your customer/user’s plans
or tasks could enable you to either design better products and services or
offer your products and services in a more relevant manner? Sensors can be used
to collect inputs that signal intent of the user in either near real time. They
can also be used to collect information that can predict a future user need or
intent.
For example, by embedding sensors in shoes, Nike can collect
changes over time in how the foot makes contact with the shoe and how the shoe
makes contact with the surface below it. These signals can be plotted over time
to detect the optimum time for shoe replacement in order to minimize foot
damage while maximizing user comfort and derived value from the shoe.
The same information collected from the shoe can also be
used to model the physical activity and condition of the user and this
information can be used for medical, physical and health tracking and
improvement programs.
The same sensors can also be used to generate social signals
indicating the user’s location at any given point in time and this information
can be shared with other users nearby who might be socially relevant or
interesting.
If I Knew ____ about my customer/user’s habit, I would ____
What information or insight into the customer/user’s habits
and patterns would enable you to make or provide better products and services
to them. Sensors can be used to collect data that can reveal patterns or habits
in the user’s daily workflows. These patterns can be used to build models of
behavior or matched against known patterns to reveal the associated needs and
wants of the user to best fulfil their workflow.
For example, understanding a user’s travel patterns at the
individual level such as between work and home, home and groceries or patterns
on the weekends vs. weekdays etc could help Starbucks present better messaging,
offers and deals to their customers that is adapted and customized to the
user’s presence across location and time. This could mean that Starbucks can
identify the go to place for coffee for a user due its proximity to a location
frequented by the user.
It can also mean that once a user enters a Starbucks store,
the service offered to them can be customized to suit their needs and preferences.
Starbucks could create a deep understanding of what the user likes and does not
like on weekdays vs. weekends, mornings vs. evenings, summer vs. winter, near
home vs. near work or at public locations like airports and sporting arenas and
utilize it to provide superior customer service and drive delight.
6 Tips For Getting Started With IoT
Once the goals and design of the IoT ecosystem has been
defined, managers should keep the following tips and best practices in mind as
they implement their ecosystem.
Types of Sensors: Sensors can be embedded in things that
users interact with (stores, vending machines etc), in things that customers
carry on them (clothes and shoes, phones etc) and things that customers use
(cars, devices, appliances). Sensors can and should collect information about
the user’s environment (weather, location), user (demographics, what they are
doing, how they are doing it, when and where they are doing it) and should be
enhanced with information from other sensors that have relevant contextual time
and location information such as correlation or causal events and locations.
Mobile Apps as Sensors: Mobile apps that run on devices have
access to the various sensors embedded in the mobile device such as motion,
temperature, ambient light etc. These apps offer a rich target for
instrumentation to collect data from these sensors.
Baseline Sensory Information: The location, time and channel
of the sensor should be collected by default and used to tag all information
collected about the user and what they are doing.
Balancing Privacy and Value: Information payloads sent from
sensors can contain a lot of information that can enable enterprises to build
very comprehensive and detailed profiles of customers and end users. However,
the data collected should be determined after due consideration to privacy and
laws and regulations. Information should be stored and processed with the
intent and goal to protect user privacy
Design for Change: Your business priorities, product mix and
use cases will change. Designing an IoT system that can deal with new sensor
endpoints, new sensor technology, new or updated information payloads and new
ways to process the data on the backend will ensure that the IoT ecosystem
continues to deliver sustained usage and value.
Design for Inconsistency: Sensors and sensory networks tend
to be inconsistent due to hardware problems and/or network problems. The IoT
ecosystem needs to be resilient to problems, errors and outages. Design should
incorporate the ability to handle and adapt to incomplete data, corrupted data
or non existent data.
Conclusion
Enterprises looking to capitalize on IoT need to think
customer and user first. Designing the IoT strategy and ecosystem around the
end user/customer needs in order to deliver on their needs and wants adapted
and contextualized to the demand is the key to success in the post IoT world.
Success in this goal require that the entire IoT strategy and implementation is
purpose driven to drive customer empathy and customer delight. At the same
time, enterprises need to ensure that the data they collect and how they
collect and process it is non intrusive to the end user, does not go against
the expectations of usage of the user and is only used to drive customer
satisfaction.
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