Month: May 2019

By understanding consumer behavior and what drives their purchasing decisions, you can increase sales of your products and services.

Why do people buy? How do they buy?

Predicting consumer’s behavior is one of the biggest challenges faced by marketers around the world. Consumers are constantly being exposed to new technologies as well as promotions about products and services.

Converting an interested prospect into a customer requires an understanding of your prospect’s behavior using data analytics tools.

Tapping into the consumer behavior is key to increasing sales and profits online.

Top Reasons for Analyzing Customer Behavior

• Gain insights –  Identifying consumer segments with cluster analysis customer database.
• Attract and engage – Targeting customer segments with right offers by analyzing historical purchases and profiles.
• Improve retention – It enables calculation of customer value and proactive approach to retention of customers.

Why has customer behavior analytics become a vital tool for ensuring marketing success?

• The number of online shoppers in US is projected to reach 224 million in 2019 (Statista 2017)
• M-commerce will reach $284 billion by 2020 (BI Intelligence)

Consumer Behavior Revealed By KPMG Studies

Online shoppers’ behavior:

• 42% – Researching about products
• 21% – Reading expert and user reviews
• 16% – Price comparison sites
• 14% – Searching discount coupons

Most important attributes when deciding where to buy:

• Best price — 36%
• Preferred website — 30%
• Best delivery options/price — 17%
• Stock availability — 14%
• Peer advice — 2%
• Returns policy — 1%

Sites where consumers shared feedback:

• Seller’s website – 47%
• Facebook – 31%
• Manufacturer or brand website – 18%
• WhatsApp – 17%
• Instagram – 12%
• Online forum – 11%
• WeChat – 11%
• Blogs – 10%
• Twitter – 9%
• YouTube — 4%
• Snapchat – 3%
• Pinterest – 3%
• Others – 21%

The Path to Purchase Journey:

1. Awareness – Triggers and Influencers
2. Consideration – Product and Company Research
3. Conversion – Where and When to Buy
4. Evaluation – Experience and Feedback

Models of Consumer Buying Behavior Process:

• Economic model
• Learning model
• Psychoanalytical model
• Sociological model

Major Types of Predictive Modeling

1. RFM Model

• Recency – customers who have spent money on a product or service in the recent past are more likely than others to spend again
• Frequency – customers who spend their money repeatedly on a business are more likely than others to spend again
• Monetary – customers who have spent the most money at a business are more likely than others to spend again

1. Black-Box Model

External stimulus response – factors leading the customer to make buying decisions:

• Environmental stimuli – Economics, Technology, Culture
• Marketing stimuli – Product, Price, Promotion

1. Personal Variable Model — consumers make decisions based on internal factors.

• Personal opinions, belief systems, values, traditions, goals

1. Complex Model — This model considers both internal and external variables

2. Contemporary Models:

• Nicosia model
• Howard-Sheth
• Bettman
• EBK model
• Markov model

Statistical Analysis and Market Research Tools

• Conjoint analysis
• Hypothesis Testing
• Tests for statistical significance
• ANOVA: The analysis of variance
• Discriminant analysis
• Factor analysis
• Cluster analysis
• Multiple regression analysis

By leveraging customer behavior data with your marketing, you can attract, acquire and retain more customers.

Predicting Consumer Behavior with Data Analytics [Infographic]

Credit: Dot Com Infoway – Digital Marketing Company