Data Mining

What is data mining?

It is the process of analysing data from different perspectives and summarising it into useful information, including the discovery of previously unknown interesting patterns, unusual records or dependencies

What are benefits of effective data mining?

• Identify previously unseen relationships between business data sets

• Better predict future trends and behaviours

• Extract value (e.g performance insights) from big data sets

• Generate business actions built on data insights

What are examples of how data mining can help a business improve competitiveness?

• Sales forecasting: Analysing when customers bought to predict when they will buy again

• Database marketing: Examining customer purchasing patterns and looking at the demographics and psychographics of customers to build predictive profiles

• Market segmentation: A classic use of data mining, using data to break down a market into meaningful segments like age, income, occupation or gender

• E-commerce basket analysis: Using mined data to predict future customer behaviour by past performance, including purchases and preferences

What are real-world examples of data mining?

• Dunnhumby and Tesco:

  • Dunnhumby pioneered data mining to help Tesco better understand its customers.

  • Dunnhumby launched the Tesco Clubcard loyalty program. Using data about past customer purchase habits, Tesco was able to stock its stores based on predictions about what customers might want in the future. It was revolutionary for the UK retail market.

• Strawberry pop-tarts and hurricane:

  • As a result of its data mining, US supermarket giant Walmart discovered that sales of Strawberry Pop-Tarts increased by seven times prior to a hurricane. Since this discovery, Walmart has placed the Strawberry Pop-Tarts at the checkout prior to a hurricane.