MF Data Analytics and Business Buying
Behaviour
Save
Students also studied
PHI IMG Population and Sampling Methods Research Methodologies Sampli
12 terms 6 terms 10 terms 6 terms
Nathan_Olsen230 Preview EnchantedLeaf Preview BrookeLitch Preview Blu
What is 'Big Data'? 'Big Data' is the act of collecting large data sets from traditional and digital
sources to identify trends and patterns.
It implies using large amounts of data, as part of a data-driven approach to
marketing.
What are the 7 V's of analysis for data-driven marketing? 1. Volume (amount of data)
2. Velocity (the speed at which the data is generated)
3. Variety (the kind of data available)
4. Validity (the interpreted data having a sound basis in logic or fact).
5. Veracity (the accuracy of the data).
6. Value (the importance).
7. Visualisation (presenting the data in a manner that is in a state of being able to
see or be seen)
Define 'data analytics'. The art and science of turning large quantities of data into meaningful,
commercially valuable information.
What is the 'Internet of Things (IOT)' and where can IOT IOT is a term used to describe the fact that almost all products and services
data be gathered from? collected data as part of their everyday operation.
IOT data can be gathered from physical objects such as toasters and refrigerators.
Define 'Data'. Data is a collection of neutral facts.
Define 'Analytics'. Analytics is the organisation of data into meaningful information.
, What is 'dark data' and why does it exist? Dark data is data that will never be able to be analysed even though the company
has stored this data.
This exists because there is so much data being created, analytics cannot keep up
in many instances.
What are the two broad categories of data in data 1. Structured; Data is structured if it is organised in a meaningful and systematic
analytics? way. E.g survey results, sales data, etc.
2. Unstructured; Data is not organised in any manner. E.g. from Twitter, Facebook,
and blog posts to obtain text, pictures, and video.
Special skills are needed to analyse unstructured data.
What is the significance of data-driven marketing? A marketer must augment their intuition with facts, and organisations must ensure
they have the right people and the right tools.
This also requires marketers to know how to use and interpret data as well as
knowing how to use relevant statistical software to do so successfully.
Give examples of a traditional and modern use of data- Traditional;
driven marketing approach. From customer book purchase history. Keep records for product returns and look
to see how promotions impact sales.
Modern (By Amazon):
Predict preference by looking at commonalities between customers. E.g. John &
Jane both bought 'Lord of The Rings'. Jane bought 'Game of Thrones'. Recommend
'Game of Thrones' to John.
What is 'Data-driven Marketing'? This refers to the marketing insights and decisions that arise from the analytics of
data about or from consumers.
They ket to insightful data and analytics is transforming the data into meaningful
objects for the business.
- Knowledge of data analysis techniques are secondary.
- Requires insight in using the data you have.
What is the significance of understanding and obtaining An organisation must know the context in which the data was gathered and
data and how is this achieved? entered into the database and makesure the data measured what it was supposed
to measure.
To help make sense of the data, marketers must often use a specialised analyst
called a data scientist.
- Data science represents the intersection between statistics, programming and
business skills.
- Requires not only technical skills but insight into business and human behaviour.
What are some challenges for data-driven marketing? Data-driven marketing can lead to challenges as well;
- Good statistical results not communicated effectively.
- Decision makers mistrust in data-driven results. Especially when data goes
against intuition
- Consumers less enthusiastic about using data to their advantage.
- Over reliance on data also be an issue. What if important data was not
collected?
Behaviour
Save
Students also studied
PHI IMG Population and Sampling Methods Research Methodologies Sampli
12 terms 6 terms 10 terms 6 terms
Nathan_Olsen230 Preview EnchantedLeaf Preview BrookeLitch Preview Blu
What is 'Big Data'? 'Big Data' is the act of collecting large data sets from traditional and digital
sources to identify trends and patterns.
It implies using large amounts of data, as part of a data-driven approach to
marketing.
What are the 7 V's of analysis for data-driven marketing? 1. Volume (amount of data)
2. Velocity (the speed at which the data is generated)
3. Variety (the kind of data available)
4. Validity (the interpreted data having a sound basis in logic or fact).
5. Veracity (the accuracy of the data).
6. Value (the importance).
7. Visualisation (presenting the data in a manner that is in a state of being able to
see or be seen)
Define 'data analytics'. The art and science of turning large quantities of data into meaningful,
commercially valuable information.
What is the 'Internet of Things (IOT)' and where can IOT IOT is a term used to describe the fact that almost all products and services
data be gathered from? collected data as part of their everyday operation.
IOT data can be gathered from physical objects such as toasters and refrigerators.
Define 'Data'. Data is a collection of neutral facts.
Define 'Analytics'. Analytics is the organisation of data into meaningful information.
, What is 'dark data' and why does it exist? Dark data is data that will never be able to be analysed even though the company
has stored this data.
This exists because there is so much data being created, analytics cannot keep up
in many instances.
What are the two broad categories of data in data 1. Structured; Data is structured if it is organised in a meaningful and systematic
analytics? way. E.g survey results, sales data, etc.
2. Unstructured; Data is not organised in any manner. E.g. from Twitter, Facebook,
and blog posts to obtain text, pictures, and video.
Special skills are needed to analyse unstructured data.
What is the significance of data-driven marketing? A marketer must augment their intuition with facts, and organisations must ensure
they have the right people and the right tools.
This also requires marketers to know how to use and interpret data as well as
knowing how to use relevant statistical software to do so successfully.
Give examples of a traditional and modern use of data- Traditional;
driven marketing approach. From customer book purchase history. Keep records for product returns and look
to see how promotions impact sales.
Modern (By Amazon):
Predict preference by looking at commonalities between customers. E.g. John &
Jane both bought 'Lord of The Rings'. Jane bought 'Game of Thrones'. Recommend
'Game of Thrones' to John.
What is 'Data-driven Marketing'? This refers to the marketing insights and decisions that arise from the analytics of
data about or from consumers.
They ket to insightful data and analytics is transforming the data into meaningful
objects for the business.
- Knowledge of data analysis techniques are secondary.
- Requires insight in using the data you have.
What is the significance of understanding and obtaining An organisation must know the context in which the data was gathered and
data and how is this achieved? entered into the database and makesure the data measured what it was supposed
to measure.
To help make sense of the data, marketers must often use a specialised analyst
called a data scientist.
- Data science represents the intersection between statistics, programming and
business skills.
- Requires not only technical skills but insight into business and human behaviour.
What are some challenges for data-driven marketing? Data-driven marketing can lead to challenges as well;
- Good statistical results not communicated effectively.
- Decision makers mistrust in data-driven results. Especially when data goes
against intuition
- Consumers less enthusiastic about using data to their advantage.
- Over reliance on data also be an issue. What if important data was not
collected?
