14 answers
1
Question
Asked
892 views
How big data, artificial intelligence and machine learning will shape marketing jobs? Which are the most valuable skills I need?
#marketing #technology #business #computer-science
Login to comment
14 answers
Updated
Roselle’s Answer
Big data, artificial intelligence and machine learning make it easier to predict shopping and buying behavior of potential customers. All data that can be collected in these ways, can help decision making and focusing on specific target customers. In the past few years this has lead to more personalized/customer oriented and specifically targeted marketing campaigns and approaches. Customers started to be treated as VIPs, and continue to expect this and get the most value our of any service/product. For marketeers, the customer experience (or used experience) has become more important, whether online or offline.
Since there are, usually, many alternatives for a product or service, many companies start focusing more on current clients (instead of potential new clients). Loyal customers require less effort and costs to be convinced to buy your products, and can also be great success stories. The power of positive reviews should not be underestimated and can make a great marketing campaign, for example as part of corporate storytelling, which is a great way to position a brand/product/service.
The skills necessary for this shift are therefore both soft skills like empathy, storytelling, creativity/design, persuasion, and courage to do what others did not think about yet, and "hard/technical" skills like statistics and very strong data analysis/interpretation/visualization skills, in order to support ideas with data.
Since there are, usually, many alternatives for a product or service, many companies start focusing more on current clients (instead of potential new clients). Loyal customers require less effort and costs to be convinced to buy your products, and can also be great success stories. The power of positive reviews should not be underestimated and can make a great marketing campaign, for example as part of corporate storytelling, which is a great way to position a brand/product/service.
The skills necessary for this shift are therefore both soft skills like empathy, storytelling, creativity/design, persuasion, and courage to do what others did not think about yet, and "hard/technical" skills like statistics and very strong data analysis/interpretation/visualization skills, in order to support ideas with data.
Updated
halee’s Answer
- Less optimizations set targets and can focus on creatives and strategy
- Can replace operations for marketing when it comes to project management and tracking
- Soft skills become more important/valuable - strong presentation skills and collaboration
- Keep up with technology changes, try to learn what is coming, don’t be afraid
- Can replace operations for marketing when it comes to project management and tracking
- Soft skills become more important/valuable - strong presentation skills and collaboration
- Keep up with technology changes, try to learn what is coming, don’t be afraid
Updated
Jen’s Answer
I don't think you can go wrong with learning business statistics and some basic programming.
Updated
Sibyl’s Answer
Big data, AI and machine learning are so important and relevant for marketing these days to improve customer experience. We're getting so much data in the data lake these days through social media, and we need AI and machine learning to learn about our customer's digital journey and behavior, so we can properly target our customers and provide relevant and personalized content to them.
Updated
Mike’s Answer
Luis, keep in mind that there are a number of facets to analytics. Try to hone in on what area excites you most. One area where I feel like I've had success is at the "end of the chain". A lot of my role is taking the analysis and crafting it into a story that's easily understandable for folks not as data-oriented. For that, having some business orientation (what is the big picture and implications for the business beyond that data point?) and an understanding of the area you're analyzing so the numbers are not just numbers.
Updated
halee’s Answer
Depending on the role within marketing, some roles will be very data/analytics heavy. With so many new tools and ways to track consumer behavior, data and analytics have become increasingly important in marketing. Regardless of the role, it’s helpful to have basic knowledge of how data and analytics can be used. In particular, focus on how to synthesize large data sets using tools like Excel, SQL, and Google Analytics. It’s less important to have knowledge of AI and ML, although these can become helpful when understanding how to automate marketing.
Updated
halee’s Answer
Data, artificial intelligence, and machine learning is definitely shaping the current marketing jobs landscape. Almost all marketing jobs require some technical knowledge. New marketing jobs that are heavily involved in big data, AI, and or machine learning would be marketing analyst, marketing operations, product marketing, marketing automation, etc. While still in school, classes that could help you get started in this field are: statistics, data, computer science, economics, and or research.
Updated
Daniel’s Answer
Hi Luis,
The emerging technologies you have mentioned are changing the future of the professions. As the transformation takes place in a specific field such as marketing, I believe you need to look at two critical perspectives - what continues and what changes. American Marketing Association defines the term marketing as the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large. I would expect the processes involved may change drastically, especially in communicating, for example, but the objectives of finding and satisfying the values would not.
With that, I will share a story of a power tool company. In their new marketing employee training program, they showed an excellent presentation of their shiniest power drill set and asked if this is what we are selling. After a brief moment of a few chatters, the picture of a concrete wall with three holes came up, and the presenter stated that this is what we are selling.
I hope this helps and wishing you best of luck!
The emerging technologies you have mentioned are changing the future of the professions. As the transformation takes place in a specific field such as marketing, I believe you need to look at two critical perspectives - what continues and what changes. American Marketing Association defines the term marketing as the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large. I would expect the processes involved may change drastically, especially in communicating, for example, but the objectives of finding and satisfying the values would not.
With that, I will share a story of a power tool company. In their new marketing employee training program, they showed an excellent presentation of their shiniest power drill set and asked if this is what we are selling. After a brief moment of a few chatters, the picture of a concrete wall with three holes came up, and the presenter stated that this is what we are selling.
I hope this helps and wishing you best of luck!
Updated
Cat’s Answer
It sounds like the other answers have a lot of information on the business side of this question, so I will focus on the programming part of it. I recommend learning a lightweight scripting language to start you out. Python is increasingly popular for data science and machine learning, thus will have lots of resources to help you along the way. I would start there. There are a lot of libraries (code that will give you helpful functionality tailored to machine learning/ data science/ ai) that you can bring into your projects and are what the industry are using and are free to use. Some of the more popular ones include TensorFlow, Pandas, Keras and NumPy (documentation for these are excellent so they are very easy to use). Jupyter notebooks are a good tool for python as well, they are very easy to use and Google even has an editor where you can use them very easily (https://colab.research.google.com/notebooks/welcome.ipynb).
check out jupyter notebooks
practice with small python projects
try out some big data science libraries
do a small DS project (definitely start small :D)
Cat recommends the following next steps:
Updated
Peter’s Answer
Luis, big data, machine learning and artificial intelligence are all quantitative in nature - so a solid experience in math, statistics (& probability) and actuarial science is definitely a good starting point. If you care to venture out further, I think you should also look into the ensuring that these mathematical models and constructs do not introduce any form of bias in their outcomes and not taking the results of these man-made models as correct and empirical. There is an emerging field on Ethics and Data Science that you should also consider. Areas under this domain include data use consent, data control and transparency, data consistency, trust, etc. Hope this helps. Good luck! - Peter
Updated
Amy’s Answer
Big data, machine learning, and artificial intelligence makes it easier to target a specific demographic for marketing. Using the data collected from sites like Google, Facebook, and Twitter, marketers can determine who is likely to buy the product based on taste preferences before they market. If you are looking at a career in marketing,
I recommend learning statistics, programming, and data mining. There is a high demand for people with these skills to go through all the data that has been collected by large corporations over the years
I recommend learning statistics, programming, and data mining. There is a high demand for people with these skills to go through all the data that has been collected by large corporations over the years
Updated
M’s Answer
This is a hard question everyone is trying to figure out! Machine learning and AI require strong data inputs. Understanding data and synthesizing are very important. The ability to understand customer trends, know which variables are working, finding audiences and come up with personas, etc. are just some examples. The output of machine learning is great to have but you need to understand how the machine operates.
Also important is the ability to think creatively. This can mean a lot of different things, like what is going to differentiate your campaign from competitors, how can we optimize this product, what is new and innovative from a design and new products area, brand content and messaging, and creatively measuring effectiveness.
Also important is the ability to think creatively. This can mean a lot of different things, like what is going to differentiate your campaign from competitors, how can we optimize this product, what is new and innovative from a design and new products area, brand content and messaging, and creatively measuring effectiveness.
Updated
John’s Answer
Human Resource Management departments will utilize some basic AI functions to analyze key words and phrases in job applications to speed up the process and make it more efficient. This is one way it is implemented. Basic marketing knowledge and basic code writing skills should put you in the right direction.
Updated
Nitasha’s Answer
Great Question. Big Data, Artificial Intelligence (AI) and Machine Learning (ML) have been buzz words in the industry for quite some time, but really understanding what they mean and how it can help shape any industry is an interesting pathway to understand.
Data, in general, provides meaningful insights by correctly structuring and modeling it. Data engineers work on modeling the data accurately by extracting data from various applications and transforming it to provide meaningful insights. Insights around how companies are performing, how their customers are using their products, whats adoption rates look like, etc.
Basic skills needed for a Data Engineer are as follows -
1. SQL (Structured Query Language) You can learn basics of SQL here https://www.tutorialrepublic.com/sql-tutorial/
2. Databases - Any relational or non-relational database, you can learn basic fundamentals of the database here http://www.esp.org/db-fund.pdf
3. Python- Excellent advantage to know any scripting or Python language for working in Big Data.
Once the data is structured and modeled, Data Scientists can apply machine learning algorithms to predict the trends on data for the future. It helps companies, businesses understand what their products can or cannot do in the future. It helps companies make informed decisions on running marketing campaigns etc.
Basic skills needed for a Data Scientist are as follows -
1. Mathematics
2. Probability and Statistics
3. Linear Algebra
4. Programming in Python, Java etc
5. Basic courses on machine learning and AI (https://www.coursera.org/learn/machine-learning)
Data, in general, provides meaningful insights by correctly structuring and modeling it. Data engineers work on modeling the data accurately by extracting data from various applications and transforming it to provide meaningful insights. Insights around how companies are performing, how their customers are using their products, whats adoption rates look like, etc.
Basic skills needed for a Data Engineer are as follows -
1. SQL (Structured Query Language) You can learn basics of SQL here https://www.tutorialrepublic.com/sql-tutorial/
2. Databases - Any relational or non-relational database, you can learn basic fundamentals of the database here http://www.esp.org/db-fund.pdf
3. Python- Excellent advantage to know any scripting or Python language for working in Big Data.
Once the data is structured and modeled, Data Scientists can apply machine learning algorithms to predict the trends on data for the future. It helps companies, businesses understand what their products can or cannot do in the future. It helps companies make informed decisions on running marketing campaigns etc.
Basic skills needed for a Data Scientist are as follows -
1. Mathematics
2. Probability and Statistics
3. Linear Algebra
4. Programming in Python, Java etc
5. Basic courses on machine learning and AI (https://www.coursera.org/learn/machine-learning)