We are part of Big Data ecosystem wherein we enable and trigger events that produce data, capture it, analyze it and then we consume it. Our world. is now more interconnected and intelligent than ever in history. In year 2000, we had approx 800,000 petabytes of data in this world. We expect this number to reach 35 zetabytes by 2020 or sooner. Imagine the wealth of knowledge that is trapped in this data and how it touches our lives one way or other every moment.
As the amount of data available to companies is on the rise, the processing and analytical capability is on the decline. It’s very key for businesses to know which to cherry pick (“use case”) before embarking on Big data implementation. In this part of Big data use-case series, I will focus Retail, Manufacturing and Automotive industry.
Use-cases in Retail and Consumer Packaged Goods Industry:
a. Customer Sentiment Analysis
Start of this year, Coco-Cola had the most facebook fans – 35M+. The point is fans are generating major brand awareness for companies by talking to their friends and families and indirectly acting as extended sales team for your organization. It’s very crucial for Retail and CPG industry to know the market pulse and market dynamics that will allow retailers to plan for inventory and stocking before products hit the shelves.
b. Customer Care Call Centers
Without any delay, using Call center record data, retailers can now monitor customer feedback immediately at point of instance. Also based on voice/speech analysis combined with social media and competition data, retailers can retain customers providing Next Best Offer outbidding competition.
c. Campaign management and customer loyalty programs
Billions of dollars are spent by companies on ads and campaigns. It has been hard to measure the success of campaigns in real meaningful metrics. With social media data and direct customer touch-points from survey, call centers, blogs, product review boards, it has become possible to capture key metrics for campaign management. This will allow to channelize the advertising dollars in optimal medium giving highest ROI.
d. Supply Chain and Logistics
Managing and optimizing supply chain distribution and logistics is key to success for every retain and CPG company on this planet. Every sensors and RFID data can now be tracked and assessed to know exact location of product that will allow planning for optimum usage of warehouse space, distribution and delivery methods.
e. Window Shoppers
Big Data technologies such as Hadoop and in-memory computing are ideally suited to collecting and analyzing unstructured data types like the web logs that show the movements of every customer though an internet storefront. Web traffic data can then be combined with existing business intelligence applications and sales data to provide new insights.
f. Predicting Customer Purchases
The holy grail of retail has been to anticipate what consumers need even before they realize they need it. There’s no better way to beat the competition than to make an attractive offer and get a customer’s business before they even realize they need your product, or consider evaluating alternatives. Today, retailers of office supplies are able to track purchases of customers’ in-store credit cards and rewards cards and, based on purchase history, anticipate when a consumer might need to reorder a product.
Other areas where Retail industry can leverage Big data
- Location based marketing – using smartphones, tablets and geo-location data, retailers can target their customer based on locations
- Merchandizing – Retailers and CPG companies can optimize planning and merchandizing design by capturing and analyzing RFID, sensor data from warehouses to shelves.
Use-cases in Manufacturing Industry:
a. Supply Chain and Logistics
Managing and optimizing supply chain and logistics is key to success for every manufacturing company on this planet. There is tremendous amount of information that is generated from the Planning and Raw Material procurement to Distribution/Warehousing stage of the process. This information is very valuable to organization to simulate for potential breakdowns and delays in the process. Also every RFID data can now be tracked and assessed to know exact location of product that will allow planning for optimum usage of warehouse space, distribution and delivery methods.
b. Customer Care Call Centers
Most of the manufacturing companies have been collecting call center data records (CDR) for warranty and customer complaints. With Big data tools and technology, companies can use the Call Records to know immediately customer discontent using voice/speech analysis or text analytics. In addition, this information can be used to correlate with social media and internal reports from quality and customer/product surveys and competition analysis.
c. Preventive Maintenance and Repairs
With advancement in technology, every engineering device is now embedded with sensors and RFID that can actively transmit vital information about machines – machine variables (temperature, oil level, humidity…), production rate, waste metrics, life expectancy and breakdown information. Any production downtime is a potential huge loss of revenue to companies due to loss of production output, cost of repairs and waste generated in the process. All the machine logs can now be used by companies to proactively plan for downtime using real-time information preventing waste, preventing major repairs and minimal downtime.
d. Customer Sentiment
Customer sentiment analysis has crossed boundaries using feeds from Tweeter, Facebook, Google, Blogs, Reviews…. Eminem is officially the first person ever to get over 60 million Facebook fans. Start of this year, Coco-Cola had the most facebook fans – 35M+. The point is fans are generating major brand awareness for companies by talking to their friends and families and indirectly acting as extended sales team for your organization. Customer Sentiment analysis provides potential to reduce the loyalty decay rate, increase sales by providing vital consumer feedback on products including packaging and distribution.
Use-cases in Automotive Engineering Industry:
a. Vehicle Insurance:
If you look at any of the fancy German cars to Ford cars, you will find inbuilt tablet shaped computer screen on your dashboard showing key information about your car using “telematics” (telecommunications and informatics). Many embedded sensors on your vehicle are constantly collecting information. This will include distance, speed, duration, geo-spatial/gps locations – city/highway/street, neighborhood, driving patterns, parking style and many others. These are key valuable information for assessing the driver risk for potential accidents. All these real-time streams and machine logs from thousands of cars and trucks on the road will constitute Big Data for insurance companies. Based on the information, Insurance companies will be able to proactively provide alerts, warnings on real-time basis and also personalized insurance pricing.
b. Personalized Travel & Shopping Guidance Systems
Your ride will be able to give you optimized travel and shopping experience by providing personalized bargain deals based on GPS locations to nearby outlets/malls/stores and individual’s recent likes on Social Media sites – Facebook, Twitter, LinkedIn, Instagram, Pinterest, Google+, … and mashed with Groupon, Bargain Deals and coupon sites.
Also using telematics and geospatial information, vehicles will deliver personalized recommendations for travel on vacation spots using individual preferences from social media sites and localized travel destinations. If individual has expressed interest in Hiking on Social media site, it will show local hiking trails; if someone liked casino or bars, it will show local casino and bars along with coupons and deals.
c. Supply Chain/Logistics
Providing real-time RFID/sensor data to Distributions/Logistics Fleet providing for aggregated real-time dashboards using streaming feeds. This will allow Distribution and Logistics companies to plan for better distribution of products,
Vehicle sensors will actively transmit vehicle information to nearby authorized dealers that will be bidding for your business for repairs and maintenance. For large fleet companies, this will allow for proactively repairs and maintenance needed on the vehicles based on analytics using potential downtime, availability of parts at repair shops, probability of failure before next maintenance, loss of business … The decision to send the vehicle to repair shop will be automated and guided by systems unless human override occurs.
e. Vehicle Engineering
Based on real-time streams of data feeds from RFID and active wireless sensor networks, vehicle engineering can be improved significantly making cars safer, efficient and cost effective.
f. Vehicle Warranty
Vehicle sensors will be providing proactive information to Warranty centers about potential failure in vehicle parts and control systems. These timely alerts to owners will enable preventive maintenance and timely repairs that will reduce repair cost during warranty period
g. Customer Sentiment
This is something marketing, advertising and sales will spend their every dollar to know what customer sentiment on your product line is. In addition, it will be also key to know what consumers think about your competition. Companies can mine this information from Tweets, Facebook, …..
h. Customer Care Call Centers
Every companies has been collecting call center data including recorded voice but didn’t know how to use mine this information. With Big data tools and technology, companies can use the Call Records to know immediately customer discontent using voice/speech analysis or text analytic. In addition, this information can be used to correlate with social media and internal reports from quality and customer/product surveys.
While all these use cases just makes up the tip of an iceberg for Big Data potentials, the intention here is to give you sample use cases that will trigger your thought process that will allow you to think using big data to your organization needs for new opportunity or competitive advantage. Big Data is full of valuable, voluminous, velocity and variety of information! Though 10 years from now, most of the companies would have implemented same or similar use-cases, the leader will be one who chose to elect the right use case for Big data path. While opportunities are endless, key is to know where you begin…. Think Big but Act Small!