Lecture_1 Flashcards
What is data
Represents a collection of data points (discrete unit of information)
How much percentage of customers are willing to share their information in exchange for some benefits?
67%
What is customer data?
- Encompasses a broad spectrum of infomation about the people and businesses your company serves.
- Essential asset for understanding your customers and their goals, how your business fits into the equation.
Four types of customer data
- Identity data
- Behavioral data
- Descriptive data
- Qualitative data
What are the usages of identity data?
Identity data can be used to personalize communication, maintain contact detail, identify buyers’ personas.
What is behavioral data?
General patterns ciustomers perform when interacting with your business and when using your products and services.
Example: Page views, email open rate, Clicks…
What is descriptive data?
Any additional information about a customers will help to better understand their habits and intention.
Example: Income, family details.
What kind of data are from survey?
Qualitative data
What is qualitative data?
Additional information regarding preference data, desirability and sentiments,.
What kind of data will tell the channel conversions?
Behavior data and qualitative data.
The availability of data nowadays
- Smartphones and the Internet made data abundant.
- Every activity creates a digital trace.
- Data volume increases with IoT.
What is “digital universe”?
The data created and copied every year.
The quality of data has changed to
Analyze rapid real-time flows of unstructured data.
The value of data change from
Targeting ads better to turn the data into AI or cognitive sercies.
Four areas of data analytics deployment
Lead generation
Match the people
Maximize LTV
Get right price
What is lead generation?
Identify the right customer at the right time.
What is match the people?
- Understand what drives sales success.
- More effective resource allocation.
- Integrate email, calendar and CRM to identify the actions correlate with success.
How to maximize CLV?
Implementing next-product-to-buy algorithms.
Using ML to identify customer discontent(不满), help increase retention.
DEal analytics can provide
Price transparency and allow sellers to make trade-offs during negotiations
Insights Value Chain
Consist of technical foundations and business foundations.
What are factors in technical foundations?
Data (new data sources…), analytics (ML/descriptive statistics…) and IT (cloud sourcing, SQL…)
The insights value chain is multiplicative
True
How to transfer data insights into value?
See slides