- 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
What is the overall impact of data on marketers and their companies
What is the overall impact of data on marketers and their companies? Data allows companies to create competitive and successful prodcuts.
How do you become a data driven marketer?
- The ability to create highly personalised, targeted campaigns
- More consistent messaging
- Concrete evidence on what’s working, and what’s not
- Improved audience segmentation
- Getting to know your customers (even before they’ve made a purchase)
- Improved product development
What type of data analytics is most difficult
Prescriptive analytics is comparatively complex in nature and many companies are not yet using them in day-to-day business activities, as it becomes difficult to manage.
If applied effectively, predictive analytics can have a significant impact on business growth.
What are the two main predictive models
Two of the most widely used predictive modeling techniques are regression and neural networks.
Which algorithm is best for prediction
Naive Bayes Naive Bayes is a simple but surprisingly powerful algorithm for predictive modeling.
The model consists of two types of probabilities that can be calculated directly from your training data: 1) The probability of each class; and 2) The conditional probability for each class given each x value.
Which model is best for prediction?
- Decision trees: Decision trees are a simple, but powerful form of multiple variable analysis
- Regression (linear and logistic) Regression is one of the most popular methods in statistics
- Neural networks
Is AI the future of marketing
Over time, machine learning and AI marketing will help modern marketers mature to personalize offerings as customers discover and shop, optimize their journeys and click paths, better predict what they want next, present more personalized recommendations to them, and drive innovation on all fronts.
How AI will impact digital marketing
With the help of AI technology, marketers can spot micro trends and even predict trends.
They can then make strategic decisions As a result, brands can reduce digital advertising waste and ensure that their spend delivers the best possible results.
Why is targeted advertising better
Targeted advertising allows brands to send different messaging to different consumers based on what the brand knows about the customer.
The better a brand can demonstrate that it understands what its customers want and need, the more likely customers respond to advertising and engage with the brand.
What is augmented marketing mix
Definition of augmented marketing: Augmented marketing is the idea of adding value to a proposition via an additional, innovative offer.
The word ‘augmented’ means “having been made greater in size or value”. So by laying on extra benefits, augmented marketing increases the chances of a sale.
What is computer data analysis
Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain.
Increasingly, data analytics is done with the aid of specialized systems and software.
How is data used to create content?
- Determining what worked and what didn’t is all relative
- Identify top-performing posts by goal
- Analyze your low-performing posts
- Always look at engagement and sentiment
- Get inspiration from Google Analytics data
- Tap into brand-relevant conversations
What are the biggest challenges to AI marketing success?
- Many popular media sources have created hype around AI
- There isn’t enough skilled workforce to fill AI-related positions in organizations
- AI software needs high-quality data
- AI software needs significant investment
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.
References
https://www.webfx.com/blog/marketing/prescriptive-analytics/
https://emerj.com/ai-sector-overviews/predictive-analytics-for-marketing-whats-possible-and-how-it-works/
https://www.mathworks.com/discovery/predictive-modeling.html
https://builtin.com/data-science/tour-top-10-algorithms-machine-learning-newbies
