Prescriptive analytics use a combination of techniques and tools such as business rules, algorithms, machine learning (ML) and computational modelling procedures.
These techniques are applied against input from many different data sets including historical and transactional data, real-time data feeds, and big data.
What is descriptive analysis business analytics
Descriptive analytics is the process of using current and historical data to identify trends and relationships.
It’s sometimes called the simplest form of data analysis because it describes trends and relationships but doesn’t dig deeper.
What are the advantages and disadvantages of prescriptive analytics?
- Pro: Make informed, data-driven decisions
- Pro: Simulate probability to reduce risk
- Pro: Increase efficiency
- Con: Only effective with valid input
- Con: Not as reliable for long-term decisions
- Con: Not all prescriptive analytics providers are legit
How does Netflix use prescriptive analytics
How do you use it? The Netflix example spans both predictive and prescriptive analytics.
Prescriptive analytics allows business analysts to parse through data and determine what customers are most likely to buy (or, in this particular example, watch) and then timely make those recommendations.
What is a prescriptive model
Prescriptive analytic models are designed to pull together data and operations to produce the roadmap that tells you what to do and how to do it right the first time.
What is an example of descriptive analytics
Examples of metrics used in descriptive analytics include year-over-year pricing changes, month-over-month sales growth, the number of users, or the total revenue per subscriber.
Descriptive analytics is now being used in conjunction with newer analytics, such as predictive and prescriptive analytics.
What is prescriptive data
Prescriptive analytics is the process of using data to determine an optimal course of action.
By considering all relevant factors, this type of analysis yields recommendations for next steps.
Because of this, prescriptive analytics is a valuable tool for data-driven decision-making.
Do you think advertisements could have negative effects
What adverts often try to do, is make you feel bad about yourself by lowering your self-esteem in order to persuade you to buy that specific product which claims it will make you happier and a better person.
The most common way they do this is by making you feel bad about your body image or how you look in general.
What is propensity modeling
Propensity modeling is a set of approaches to building predictive models to forecast behavior of a target audience by analyzing their past behaviors.
That is to say, propensity models help identify the likelihood of someone performing a certain action.
Do people like targeted ads
When we asked people if they want to receive personalised ads we found a majority (57%) don’t want to receive any – whether political or commercial – and a further 26% don’t want to receive targeted political ads.
Only 11% of people said that they were happy with their personal data being used to target them with ads.
What is uplift in data science
Uplift modeling is a causal learning approach for estimating an experiment’s individual treatment effect.
Using experimental data, the end-user can calculate the incremental impact of a treatment (such as a direct marketing action) on an individual’s behaviour.
References
https://www.marketingevolution.com/knowledge-center/the-role-of-predictive-analytics-in-data-driven-marketing
https://www.yourmembership.com/blog/market-research-associations-leads-better-decision-making/
https://waxcom.com/healthcare/the-pros-and-cons-of-targeted-marketing
https://quizlet.com/494990294/im-012-total-recall-b-flash-cards/
