An Oracle blog about Internet Of Things

  • July 2, 2016

Injecting IoT into Big Data Analytics

Gib Bassett
Industry Principal

The Internet of Things, or IoT, presents many opportunities for retailers and consumer goods
organizations to drive business improvement. Among these is the use of data
from sensors, devices and products to improve Big Data Analytics. Consider the
following scenarios:

Consumer Products

A household products company offers an internet connected
button in the consumer’s home to place a replenishment order manually, which is
delivered same day. Or, the product itself features smart packaging that
“knows” when it’s nearly depleted and triggers the re-order autonomously. Demand
is better understood among these customers and predictable such that
fulfillment is streamlined and anticipated. As a consequence of all this, high
frequency customers are isolated, a personal relationship is developed, and
they are targeted for testing new products and acting as champions in new
product rollouts.


An appliance company’s product sends usage information back
to the company to identify potential quality issues and collect feature
utilization to aid product development. The appliance also now acts as a conduit
for developing a relationship with the customer. Thus marketers can propose new
ways to use the product to improve satisfaction and referral, or recommend the
purchase of complementary appliances. In a commercial context, freezers and
other storage or display machines that ensure product quality or safety,
require maintenance, or have the capacity to measure inventory, present similar
opportunities when the customer is a business (retailer) rather than a consumer.

Omnichannel Retailer

A retailer employs beacons in its stores which trigger
personalized offers to customers on their smartphones. Or even better, the
offers also reflect product availability, which is tracked from the shelf, to
the storage room, to the distribution center, and reflects inventory across
physical and online stores. As a result, regardless of commerce channel,
digital promotional offers reflect actual availability to avoid out of stock
situations for high demand promotions, winning the customer’s business and
ensuring a satisfying shopping experience leading to greater loyalty. This same
capability could also offer supplier brands the opportunity to bid on real time
mobile promotional opportunities to avoid excess inventory.

These are three scenarios playing out today in progressive
adopters of Big Data Analytics who recognize the potential of “data in motion,”
or the type of streaming data often associated with IoT. Big Data Analytics is
fundamentally about generating new insights on data in many formats from many

Data created by sensors, devices and products, in
combination with many other sources, is invaluable in the above three scenarios
to inform decisions related to:

  • Demand Forecasting

  • Product Launches

  • Research and Development

  • Customer Satisfaction and Advocacy

  • Cross or Upsell

  • Personalized Offers

  • On Shelf Availability

These are all analytical use cases which can be executed
absent IoT data, but are greatly improved with IoT data. This is today
simplified with the Oracle IoT Cloud Service, which works in conjunction with
Oracle’s Big Data Cloud capabilities to realize a variety of high value use

The ability to ingest and manage data from IoT and
numerous other sources within and outside a company is essential to powering many
Big Data use cases. To better understand this, check out
Gartner and Forrester coverage of the Big Data platform markets.

Companies are struggling to increase the scale of the use
cases they can explore with Big Data. So simplifying the acquisition and management
of data, as well as the data science process itself, is critical. These are all
attributes of the Oracle Big Data Cloud value proposition, which is further
enhanced by the ability to seamlessly incorporate IoT data in many use
cases via Oracle IoT Cloud Service.

Gib Bassett,
Retail and Consumer Goods Industry Principal

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