The Internet of Things, or IoT, is clearly the most exciting invention since the Internet itself. Kevin Ashton coined the term IoT, 17 years ago, to describe the network connecting objects in the physical world to the Internet. Fast forward to the present day, IoT is about pervasive connectivity. This means everything and anything is connected to the Internet in some way. IoT, thus, gives businesses and marketers the opportunity to create, extrapolate and utilize actionable insights about consumers and trends that were unimaginable just a few decades ago.
Prediction is that by 2019, IoT will be the world’s largest device market—double the size of the smartphone, PC, tablet, connected car, and the wearable market combined. There will be reinventions in business models, helping them save millions of dollars in the next decade as the trend comes closer to reality.
A look at the next gen technologies that are imperative for successful IoT implementations, and to drive new business opportunities:
Our analysis shows that roughly 80% of all industrial Internet data contains a location. Utilizing location intelligence and spatial information (the graphically represented location information) for industrial IoT use cases, we foresee impact on municipal processes, changing how governments aid citizens and the way they interact with city services.
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Smart City initiatives, for example, can utilize location intelligence to better understand population distribution. Analysing neighbourhood demographics supports improved routing of public transportation and identifying urban infrastructure inefficiencies to better educate policymakers. When location intelligence is utilized within Smart City applications, city managers will be able to make swifter and better business decisions.
For consumer applications, marketers can provide interactivity in location-based offerings. Marketers are out to exponentially increase their interactions with their customers. And fortunately for them, the market for location-based services has begun a healthy trend by attracting developers to create highly interactive apps for games, learning environments, environmental models, way-finding, shopping and entertainment.
We’re not talking about merely an ad strategy of location-based services that gives you a coupon for Starbucks or Domino’s as you walk/drive near the location. No. This is a more context-aware technology.
Let’s say your Fitbit shows you are a runner, so perhaps you get an ad for a salad rather than pizza, or if your heart rate is high, maybe decaf is on offer rather than regular coffee. There’s more “hot” data (read real-time) to convert into actionable efforts.
IoT and big data management
What enterprises need is a single, unified big data platform to traverse multiple data sources that often don’t easily work together. Data integration, in batch or real time, requires the ability to connect to data from multiple sources either directly or through integration with existing data access technologies. This helps marketers unlock the true value of data by giving them a 360 degree view of their customers that helps them identify relationships, uncover opportunities and engage with customers in a more meaningful way.
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There are many innovations taking place in this space that have given rise to new business applications. For example, with a robust big data platform, a financial company can track a consumer’s spending pattern or it can be used by an insurance company to visually depict a customer’s risk profile. For a retailer or a marketer, it can provide a holistic perspective of each buyer’s unique history, behaviour and preference.
However, enterprises are moving away from managing big data infrastructure themselves, instead concentrating on data analytics and the value they can derive. The promise of IoT can be accomplished by driving partnerships with big data platform providers.
IoT and real time analytics
IoT analytics will become a data science specialized category and discipline. And rightfully so. There needs to be development of such analytical capabilities that supply information while protecting the privacy of individuals. Deep machine learning technologies (based on neural networking) are showing great potential in deducing relationships.
A simple business use case that has come up using IoT analytics is around Beacons, which is about emitting a signal that can be picked up by a smartphone. Retailers are offering deals, promotions, and recommendations on nearby products for customers who opt in. Beacons are estimated to amount to $44 billion in sales by 2016.
Real-time analytics can become a differentiator for companies in the future.
Manish Choudhary is senior vice president, global innovation, and managing Director, India, at Pitney Bowes Inc.