― 

CONSUMER

BEHAVIOR

...the higher the expectations about unselected alternatives, the lower the level of satisfaction with the chosen good.

“ “Michael R. Solomon, Consumer Behaviour: A European Perspective

OUTLINE

1 Consumers vs Customers

2 Influences on Consumer Behavior

{ }1 Consumer vs CustomerWhat is the difference?

-Customer refers to a person who buys

the goods or commodity and pays

the price for it-Consumer is the

user of those goods.

VISUALgetConsum

er or Custom

er?

Consumer or Customer?

Differentiating PointsBASIS FOR COMPARISON CUSTOMER CONSUMER

MeaningThe purchaser of goods or services is known as the Customer.

The end user of goods or services is known as a Consumer.

ResellA customer can be a business entity, who can purchase it for the purpose of resale.

No

Purchase of goods Yes Not necessary

Purpose Resale or Consumption Consumption

Price of product or service Paid by the customer May not be paid by the consumer

Person Individual or Organization Individual, Family or Group of people

{ }2 Influences on Consumer Behavior

Selective Attention: The individual focuses only on a few details or stimulus to which he is subjected. The type of information or stimuli to which an individual is more sensitive depends on the person. Selective Distortion: In many situations, two people are not going to interpret an information or a stimulus in the same way. Each individual will have a different perception based on his experience, state of mind, beliefs and attitudes. Selective distortion leads people to interpret situations in order to make them consistent with their beliefs and values.Selective Retention: People do not retain all the information and stimuli they have been exposed to. Selective retention means what the individual will store and retain from a given situation or a particular stimulus.

• Perception

Family Life

Cycle

If you want to understand today, you have to search yesterday.“ “

- Pearl Buck

The weather channel can predict what products its customers will buy based on local weather predictions. This knowledge is then used to sell very specific ads to local companies. The first warm day in spring in Chicago is good news for the local airco manufacturers. This may be an obvious example, but just like the daily weather forecast, they can predict consumer behavior every day of the year. Digital ads account for half of the weather channel’s advertisement revenue. By linking their big data story to the fast adoption of smartphones they are expecting to generate a marked increase in digital revenue. Their goal is to create the perfect ad for every individual consumer.

• Case 1: The Weather Channel

Thanks to their social command center, the popular fast food chain Taco Bell is able to predict the success of product innovations with 90% accuracy. Every year, some 18 million messages on Taco Bell are posted online and the real-time analysis of these data helps them predict success or failure with eerie precision. Thanks to the use of big data they haven’t had a failed product launch in over 15 years.

• Case 2: Taco Bell predicts success of a new product

Opening up a new coffee shop is always a calculated risk. In one location the shop may be buzzing with customers whereas 100 yards down the road, that same new Starbucks may be forced to close shop six months later.Researchers have used Foursquare data to determine which locations are most suited for a new Starbucks. For Starbucks, the degree of competition turned out to be the deciding factor in customer frequency. The study revealed that the Foursquare data in itself are not enough to make the right choice. The prediction becomes more accurate when the Foursquare data are added to existing socio-demographic data. The combination of offline and online data improves the odds of success for a new Starbucks outlet.

• Case 3: Starbucks can predict the ideal location to open up a new coffee shop

Wonga.com is a financial player in London. The company gives payday loans to consumers and is one of the fastest growing players on the British financial market. They discovered that evaluating creditworthiness based on the classic data and bank blacklists was not enough to make an accurate assessment.Wonga created its own algorithm to evaluate its clients correctly. They use classic data supplemented with data taken from social media. Every new customer brings new data and makes the assessment more accurate. Adding data from social media gives a clearer picture of consumer spending behavior than impersonal financial data. This has proven particularly useful for the evaluation of creditworthiness and it has also made the organization more profitable.

• Case 4: Wonga.com evaluates creditworthiness

REFERENCEShttp://keydifferences.com/difference-between-customer-and-consumer.htmlhttp://smallbusiness.chron.com/customer-consumer-definitions-5048.htmlhttp://www.aipmm.com/html/newsletter/archives/000434.phphttp://theconsumerfactor.com/en/4-factors-influencing-consumer-behavior/http://catalog.flatworldknowledge.com/bookhub/reader/8111?e=sirgy_1_0-ch12_s02http://www.marketingteacher.com/family-life-cycle/http://stevenvanbelleghem.com/blog/the-predictable-consumer-4-case-studies