Lesson 2: Variables and Data Flashcards
Data that cannot be counted, measured, or easily expressed using numbers.
Qualitative
Information a company collects directly from its customers and owns.
First-party data
Is the process of cleaning, and transforming raw data prior to processing and analysis
data preparation
Is any information collected by an entity that does not have a direct relationship with the user the data is being collected on
third-party data
Indicates how reliable a given dataset is across key dimensions like completeness, consistency, accuracy, and more.
Data Quality
Information all about consumers, from their household, demographic and lifestyle details to their behaviors and buying
Consumers analytics data
A numerical type of data that includes whole, concrete numbers with specific and fixed data values determined by counting
Discrete data
Ensure your data is consistent within the same dataset and/or across multiple datasets.
Consistency
Data that can take any value
Continuous
Data that can be counted or measured in numerical values.
Quantitative
Characteristic of members of a population.
Variables
Observations of variable
Data
Contains variables and observations
Dataset
Numbers with known differences between variables, such as time.
Interval
Numbers that have measurable intervals where difference can be determined such as height or weight.
Ratio
Data used for naming variables, such as hair color.
Nominal
Data used to describe the order of values, such as 1= happy, 2= neutral, 3 = unhappy.
Ordinal
Ensure data is close to the true values
Accuracy
If it measures what it is supposed to measure.
Validity
The degree to which all required data is known
Completeness
The degree to which the data is specified using the same unit of measure.
Uniformity
Is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset
Data Cleansing
A script is a series of analytics commands that are executed sequentially and used to automate work within analytics.
Scripting
To extract data from a source, convert it into a usable format, and deliver it to a destination. This entire process is known as ELT (Extract, Load Transform)
Data Transformation
A central repository of information that can be analyzed to make more informed decisions.
Data warehousing
Data Life Cycle
Create - Store - Use - Share - Archive - Destroy
Data shared by another organization about its customers ( or its first-party data.)
Second - party data
DATA COLLECTION METHODS USED IN ANALYTICS
• Surveys
• Transactional Tracking (POS System)
• Interview and Focus groups
• Observation
• Online Tracking (Internet Cookies)
• Forms
CONSUMERS ANALYTICS DATA
Descriptive
Behavioral
Interactive
Attitudinal
Six Effective Ways to use your first-party data: Segment your audience and create engaging customized emails that are relevant to that group.
Emails
Six Effective Ways to use your first-party data: A/B test using customer data on your landing pages to see which message resonates amongst a particular audience.
Landing pages
Six Effective Ways to use your first-party data:
Target distinct personas through paid advertising across channels
Paid ads
Six Effective Ways to use your first-party data:
Create tailored content in a variety of formats (e.g. blogs, videos,
ebooks).
Social media
Six Effective Ways to use your first-party data:
Offer early-bird access to sales, discounts or
free content (e.g. a relevant eBook)
Loyalty programs or membership
Six Effective Ways to use your first-party data:
If you’re a B2B marketer, use this data to create relevant and personalized content
Account-based marketing
Data Types: Pass/Fail
Binary
