Hotel Chain Uses Big Data to Increase Bookings
Red Roof Inn recognised the need to target these stranded passengers to offer overnight hotel accommodation. It also recognised that many travelers use smartphones to look for emergency accommodations. Therefore, Red Roof Inn implemented its Big Data strategy by .....
Pizza Chain Makes More Sales in Time of Power Outage
Using the same methodology of Red Roof Inn, a pizza chain uses a mobile app and mobile marketing campaigns to deliver discount coupons to area experiencing power outage leaving residents unable to cook.
Free Public Wi-Fi Networks at Shopping Centres
A technology solution company in Australia, through its installations and management of free public Wi-Fi networks for shopping centres and retailers, is putting Big Data into the palms of retailers. Through a connection to the consumer’s mobile phone, consumer data can be captured, tracked and distilled for the retailer – allowing them to make data driven decisions, and ultimately maximise their profits.
Using Big Data in Product Design
In a Southeast Asian nation where 3 main ethnics are Malay, Chinese and Indian, one cable television operator designed ethnic viewing package based solely on demographic: Malay package for Malay families, Chinese package for Chinese families, and Indian package for Indian families. This was considered safe and avoided selling inappropriate or sensitive content to the wrong target audiences.
In 2011, a startup company in Seattle known as Decide.com initiated a bold ambition of building a price-prediction engine for zillions of consumer products, but mostly technology gadget. The company deployed powerful computer to obtain data feeds from e-commerce sites and other price and product information that could be found on the Internet.
Big Data at Macys.com
Macys.com utilizes a variety of leading-edge technologies for big data, most of which are not used elsewhere within the company. They include open-source tools like Hadoop, R, and Impala, as well as purchased software such as SAS, IBM DB2, Vertica, and Tableau. Analytical initiatives are increasingly a blend of traditional data management and analytics technologies, and emerging big data tools. The analytics group employs a combination of machine learning approaches and traditional hypothesis-based statistics.
Big Data at Sears
These days the company is using big data technologies to accelerate the integration of petabytes of customer, product, sales, and campaign data in order to understand increase marketing returns and bring customers back into its stores. The retailer uses Hadoop to not only store but process data transformations and integrate heterogeneous data more quickly and efficiently than ever.
Boosting customer relationship and store revenue via retail analytics
A Malaysian cafe chain was able to boost its business by adopting a WiFi-based Customer Relationship Management solution from Tapway, which helped to collect valuable customer behavior data and to monetize by targeted advertising and promotions via email and SMS.
Online etailer Uses Big Data To Detect Patterns And Anomalies
The leading consumer health, beauty, and home-care online retailer wanted to ensure outstanding customer experience by analyzing real-time customer behavior on the website and track orders continuously. The company chose Striim for real-time data integration into Kafka, streaming analytics, and data visualization, delivered in a single enterprise-grade software platform.
Striim collects website log data, enriches with customer data from transactional databases in real time via log-based change data capture, and analyzes the streaming data to detect any patterns and anomalies. It delivers insights via real-time dashboards and allows real-time monitoring of key metrics. It can also predict any website performance issues to prevent impact on customer experience.
Prevents website performance issues via real-time, predictive analytics.
Eliminated the performance impact of running ad-hoc queries on the production OLTP systems.
Offers targeted products to buyers based on real-time, and deeper customer insight.