Big Data and Analytics

Question 1

Which key areas can be impacted when combining Big data with an integrated marketing strategy?

Answer 1

1. Customer Engagement - who, where, how and what they want
2. Customer Retention and Loyalty - what makes them return and remain
3. Marketing optimization and performance - optimum spend across channels and media, focused, continuous testing and improvement

Question 2

Name 5 types of Big data

Answer 2

1. Big data itself - hese are the classic predictive analytic problems, where you want to analyze trends or push the boundaries of scientific knowledge
   when mining a mind blowing amount of data.
   In general, the larger the dataset, the more precise the conclusion.Still, the vast scope means rethinking where and how the data gets stored and shared.
2. Fast data. Fast datasets are still large, but
   the value revolves around being able to deliver a good enough answer now. Or at least somewhat accurate traffic forecast today is better than a much more detailed analysis tomorrow, or a week from now.
   In reality, in our business environment, this is the type of data applications most companies will use, the fast data.
3. Dark data. This is the information you have but can’t easily access today. Think about video streams, photographs, handwritten common cards ingress data from security. Dark data is information you have but can’t easily access. Estimate that approximately 80% of data is unstructured data, and more is probably going to grow.
4. Lost or ignored data. This is often data that is collected in an operational environment.
   It could be in manufacturing processes, in chemical boilers, or even in the retail environment.
   This is a lot of data that is collected, but not necessarily available for big data analysis. Unlocking that potential is another huge opportunity.
5. New data. This is where new data consists of information we could get and want to get, but likely aren’t having and investing in harvesting now.
   This could include in the commercial space user location data from all customers,
   behavioral patterns from smartphone users.

Question 3

What is Machine Learning?

Answer 3

Type of AI that enables software / systems to learn and improve their accuracy and predictive outcome without being explicitly programmed

Question 4

What is AI?

Answer 4

AI - science and engineering of development of intelligent machines. Learning / Planning / Problem solving outcomes by Sensing -> Comprehension -> Action capabilities

Question 5

What is NLP?

Answer 5

Natural Language Processing is the process whereby computing is used to analyze, understand and derive meaning from human language in a smart and useful way

Question 6

What is NLU

Answer 6

Natural Language Understanding - computing to understand and process language and expression, i.e., drawing conclusions from the understanding

Question 7

Name 3 types of big data for Marketing

Answer 7

1. Customer data
2. Operational data - metrics re. marketing campaigns, budgets and resources
3. Financial data sources - revenue, profits and other objective financial information

Question 8

Name sources of Big data

Answer 8

3 Main varieties

1. Transactional data - invoices, orders etc.
2. Machine data - data gathered from equipment, data gathered via sensors / devices (realtime data) and online tracking data
3. Social data - data obtained from social media platforms

Question 9

What are 3 data challenges for Marketing

Answer 9

1. Getting the right data
2. Knowing which analytical tools to use
3. Knowing how to go from data to insight to impact

Question 10

What are the 3 generic steps to go from Big Data to Marketing

Answer 10

1. Use big data to dig deeper for deep insights
2. Get insights from data to those who can use it - not only marketing insights, but sales, customer support, forecasting etc.
3. Smaller more frequent projects and implementations - no use waiting for too long for a big outcome. Smaller key objectives

Question 11

Name 5 ways to utilize Big Data in marketing strategy

Answer 11

1. Monitor Google trends to inform global or local marketing strategy.
2. Use digital information to more clearly define your customer profile - ICP (ideal customer profile)
3. Creation of real time customer personalization for buyers
4. What contents moves customers down the sales funnel, e.g., content scoring on twitter
5. Integrated predictive analytics into lead scoring and sales conversions.