How will Big Data affect/benefit me/my business?
One area where Big data analytics is noticeable is to deliver targeted personalised advertising, directly based on your buying habits or previous browser search, enabling the potential for a higher return on the cost of marketing. You may have seen adverts in your Yahoo email that relate to products you have recently searched on. i.e. flights to specific locations.
Blink Box customers will see adverts based on what they have purchased from Tesco with or without a loyalty card.
Data visualisation to show of data in different ways to gain more business insight, for example:
Transactional data for a financial institution shown in a bar type chart will identify spikes which could be fraudulent transactions, allowing for further investigation. The data can be automatically profiled with exception reporting highlighting areas of concern.
Car rental giant Avis Budget has launched a new marketing sciences organization fueled by big data analytics to better serve its customers. Now, the company is able to target customers by brand, segment and other key factors to bring them more value than ever before – Get the inside scoop on how Avis carried out this transformation and the lessons they learned along the way.1
How Can Ecommerce Merchants Use Big Data?
Merchants can use Big Data in many different scenarios. This can include comparing traffic to a particular product to the sales of that product.
Mark Ledbetter, global vice president for SAP Retail offered this example to Retail Info Systems News, a magazine. “Retailers can compare the volume of website traffic for a given product versus number of sales of that product. You would expect a correlation between web traffic and sales — consumers find the product they want, and then they buy it. But if you find a lot of web traffic and few sales, something is wrong. It’s a signal to keep the product, whereas in the past, it may have been discarded due to low sales. Now you just need to confirm the product is competitively priced, has a compelling and informative presentation, an array of colors and sizes, and all other aspects that are required to incent the customer to make that final, and most important, step: the purchase.”
Where does Big Data link to DG & DQ?
Organisations Gartner has surveyed estimate that poor-quality data is costing them on average $14.2 million annually.
The increasing types of data are changing the focus of data quality, requiring the technology to be specialist where needed, but also all-encompassing. Data is growing in volume, variety and velocity, and data quality technology needs to keep up with the growth rate.
Information Governance is setting stringent expectations on the need for data quality and how it is managed and monitored. Failure in governance is often linked to poor execution of processes, and the evidence is often in the way the data that is collected. Effective data quality technology (whether manual or high-tech) can keep the data in check and meet requirements of your governance programmes along with the necessary reporting and actions to resolve failures.
Gartner reports “Those planning to deploy data quality tools over the next 12 months cited information governance programmes as their most common intended use case, at 57%”.
Data profiling and visualisation of data quality is seen to be critical in understanding the nature of quality, with the focus shifting from just fixing the data to preventing the problem – see previous blog on Identify, Cure and Care. Uncovering issues before they become unmanageable is critical to successful business operations, and being able to convey the impact of data quality in a language that business sponsors and stakeholders recognise is seen as critical for approval and remediation.
Gartner state “CDOs, information governance teams and other roles in the business will also become more involved.”
Is Big Data Only for Big Companies?
Any sized company can benefit from Big Data. Amazon is a pioneer in its use, but smaller ecommerce companies can benefit as well. “Big data is quite simply data that cannot be managed or analyzed by traditional technologies,” according to Rebecca Shockley, global research leader for business analytics at the IBM Institute for Business Values, quoted in IBM’s Forward View magazine. “So what is considered big data for one company may be different for another company. ‘Big’ doesn’t have to be really that big; it’s just bigger than what you’re used to dealing with,” she adds.
Many business-analytics consulting firms exist to help smaller companies deal with Big Data. Software to deal with Big Data is also available. As Big Data becomes entrenched in more companies, the software tools will become more sophisticated and less costly.
It is important to seek a positive return on investment for Big Data. It helps to have a strategic intent as to how you will use the data when you start out. Ask the right questions that identify the specific decisions that data and analytics will support to provide favorable business outcomes. Initially keep things simple and then move on to more sophisticated uses.
Big Data and Analytics Solution Identification Method
Consider the following method to identify your Big Data business challenges and how to move forward to a solution.
A Powerful Tool; Be Careful What You Use It For – Warning!
Big Data can provide detailed insights into customer behavior that can be unsettling. Here’s an example. Early last year a 15 year-old girl in Minneapolis went to her local Target store and purchased unscented body lotion. Target assigns every customer a guest ID number tied to a credit card, name, or email address. Target maintains a history of everything that person buys along with demographic information.
Within a few weeks, Target mailed the girl coupons for pregnancy and baby-related items. The girl’s father found the coupons and in an angry mood went to talk to the Target store manager, accusing him of encouraging his daughter to become pregnant. The store manager, unaware of why the coupons were sent, apologized. He called the father a few weeks later to again say how sorry he was. But this time the father apologized. It turns out that Target, using Big Data analytics, knew more about the man’s family situation that he did. The girl was indeed pregnant. It turns out that pregnant women buy a lot of unscented lotion.
In short, Target’s analytics are so good it can predict the trimester of pregnancy based on what a female buys. But Target received a good deal of negative feedback after this story was publicized.
1. Author: CSC Town Hall http://www.csc.com/big_data/insights/97741-how_avis_budget_uses_big_data_in_marketing
DG – Data Governance
DQ – Data Quality
IG – Information Governance
CDO – Chief Data Officer