AranduCorp

Customers rarely explicitly reveal their preferences. They usually do so implicitly in their purchases and transactions. Analysing their purchases, we can gain insights on what customers want, how much they are willing to pay, and how they choose between competitors and competing brands.

Consider the following example: Suppose a person’s credit card transactions includes a hockey stick. Would this indicate that the person likely plays hockey? What about if the same credit card is used during hockey season to buy hockey gloves and jerseys? Would this indicate, then, that the person likely plays hockey? What if the person purchased only a particular hockey team’s jerseys consistently? Would this indicate loyalty to that team? Predictive analytics can help answer those questions by “figuring out” what is on the customers’ mind.

One business that illustrates profoundly the power of analytics is Wal-Mart. Wal-Mart’s ability to use predictive analytics to guess what customers will be interested in, how much they will buy, and at what price and its ability to act based on that information has made it a leader in the retail industry. For example, Wal-Mart have determine that before a hurricane, customers stock-up food items that do not require cooking or refrigeration. In that market segment, they found that Kellogg’s Strawberry Pop Tarts are the most popular. We can expect that Wal-Mart will make a rush order of Pop Tarts just before the hurricane hits.

In short, predictive analytics allows retailers to “figure out” what is on the customers’ mind. Using this knowledge to optimize the performance of the entire value chain is key to outmaneuver competitors and guarantee success in today’s competitive marketplace.

To learn more:

• Wikipedia’s entry on predictive analytics
• Competing on Analytics by T.H. Davenport and J.G. Harris

What is predictive analytics?

Predictive analytics is an umbrella term that groups techniques from data mining, machine learning, and statistics. Predictive analytics is used to process trends, historical data, and current data to make informed predictions about future events.

What is the market size for predictive analytics?

According to IDC the revenues for predictive analytics reached US$ 1,244 Millions in 2006.

Which firms are major users of analytics services?

The list is big but some of the major users of analytics are:
Wal- Mart, Dell, Amazon, Capital One, Boston Red Sox, Honda, Intel, Verizon, Novartis, Marriot, Netflix, Monster Canada, Scotiabank, ConocoPhillips Norway, and Environment Canada.

Who are the major players in analytics?

SAS, SPSS, Visual Numerics Inc., Oracle, Teradata, Microsoft, Insightful Corp., IBM, Fair Isaac, Unica Corp.

In which application areas are analytics services commonly used?

Some of the areas in which analytics are used are:
Supply chain management, research and development, customer selection, pricing, quality assurance, financial performance, and recruitment.

What are some of the popular tools used for analytics?

Three of the most popular are: SAS Enterprise Miner, SPSS Clementine, and Oracle Data Miner

What training is available on predictive analytics?

Some universities offer training on data mining, statistics, and machine learning. You might want to check with your local universities. Most of the vendors mentioned above also offer good training programs. You can also find small companies such as AranduCorp that offer training in particular areas (machine learning and data mining in AranduCorp’s case).

Where can I learn more?

For a high level picture on the use of analytics you can have a look at the book:
Competing on Analytics: The New Science of Winning
by Thomas H. Davenport and Jeanne G. Harris