Data-Driven Sales (5 cr)

Objectives (course unit)

Sales has changed based on customer behavior, digitalization and global business. Digitalization changes every business and data brings more opportunities to the future of businesses and to the decision making. ​

After the course student know how digitalization is changing the world of doing business, sales and marketing and how to use data in sales and marketing. Students have new methods and technologies to do sales on a more effective way. As a part of this course students are able to increase their critical thinking on how to do sales and marketing today.

Content (course unit)

During the course students are able to consider the role of data, insight and analytics in demanding sales work. Students are also able to understand better how AI is influencing to the future of sales and what are the new ways to do sales already today and in the future. All these new ways bring also more opportunities for sales and marketing professionals to make decisions based on data.

Relevant questions to find answers during this course are for example: ​
- How changed customer behavior and digitalization affect to the work of sales? ​
- How to do selling today?​
- What kind of digital tools should be used?​
- How does data and AI impact on future sales and marketing?​

This course will be held in close collaboration with company representatives and the learning is based on literature, lessons and assignments.

Join course Data-Driven Sales and win the game in the future!​

Prerequisites (course unit)

-

Assessment criteria, satisfactory (1-2) (course unit)

The student can name how data is used in sales context. He/she knows how to gather sales data. He/she is aware of how artificial intelligence is used in sales. The student can make general decisions based on sales data.

The student meet the minimum course objectives. He/she participate in the contact lessons. The student complete the course assignments on a satisfactory level. The student's performance indicate that he/she meet the minimum requirements set in the curriculum of the course.

Assessment criteria, good (3-4) (course unit)

The student is familiar with using data in sales context. He/she knows how to gather, analyze and interpret sales data. He/she is aware of how artificial intelligence is used in sales. The student can make decisions based on sales data.

The student meet the course objectives. He/she participate in the contact lessons. The student complete the course assignments. The student's performance indicate that he/she meet the requirements set in the curriculum of the course.

Assessment criteria, excellent (5) (course unit)

The student is highly competent in using data in sales context. He/she possess a comprehensive understanding of gathering, analyzing and interpreting sales data. He/she is familiar with the application of artificial intelligence in sales. The student can make meaningful decisions for the company based on sales data.

The student meet the course objectives sovereignly. He/she successfully participate in the contact lessons. The student complete the course assignments on a distinguished level. The student's performance indicate that he/she has outstandingly fulfilling all the requirements set in the curriculum of the course.

Location and time

We meet 6 times at TAMK - You are warmly welcomed! We'll start every time at 3 pm and and ens at 6 pm. Team of Vainu.io is present at every lecture!
18.9. Modern sales and marketing at G00-10 TAMK
25.9. Data & data in sales ​at G00-10 TAMK
2.10. Contacting and social selling at G00-10 TAMK
9.10. Mathematics and Sales & modern IT-systems at G00-10 TAMK
23.10. AI and the future of Sales at Backstage at G00-10 TAMK​
30.10. Team cases and reflection at Backstage Y-kampus TAMK

Assessment scale

0-5

Teaching methods

Please meet us at marketing event held by Vainu.io​ on XXX!
The learning during this course is based on lectures, assingments and on individual reading. For passing this course, you must attend for five lectures.
The course will be held in a close collaboration with company called Vainu.io. The responsible teacher is principal lecturer Pia Hautamäki Y-kampus TAMK.
Team Lead of the course behalf of Vainu.io is Mika Jordanov
Other company representativies during the course:
CEO Mikko Honkanen​ at Vainu.io
CTO Tuomas Rasila​ at Vainu.io
(Sani Leino, Antti Merilehto)​
Lecturers from TAMK:
Senior Lecturer Pekka Pöyry, TAMK​
Senior Lecturer Sven Rassl, TAMK​
Dr. Pia Hautamäki Y-kampus, TAMK​
​

Learning materials

Gentsch, P. (2018). AI in Marketing, Sales and Service: How Marketers Without a Data Science Degree Can Use AI, Big Data and Bots. Springer.
Hughes, T., Gray, A., & Whicher, H. (2018). Smarketing: How to Achieve Competitive Advantage Through Blended Sales and Marketing. Kogan Page Publishers.
Matthews, B. (2018). Sales enablement. Newark: John Wiley & Sons, Incorporated.
Roberge, M. (2015). The Sales Acceleration Formula: Using Data, Technology, and Inbound Selling to go from $0 to $100 Million. John Wiley & Sons.

Student workload

Data-Driven Sales is 5 credits course and this means 135 hours of work​ which includes:
- 6 lessons​
- Assignment 1: Team assignment based on Vainu’s case
- Assignment 2: Book reading & learning diary​
All the information will be found in TABULA​! You will get the key to Tabula on our fisrt meeting!
Vainu.io will bring their software for students to use​ during the course.

Practical training and working life cooperation

The student team need to find a company to whom team will be making the team work.

Further information

We meet 6 times at Y-kampus and Backstage - You are warmly welcomed! We'll start every time at 3 pm and and ens at 6 pm.
The course is conducted in cooperation with vainu.io. Team of Vainu.io is present at every lecture.
18.9. Modern sales and marketing
25.9. Data & data in sales ​
2.10. Contacting and social selling
9.10. Mathematics and Sales & modern IT-systems
23.10. AI and the future of Sales
30.10. Team cases and reflection

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

The student is not attending to the lectures and do not finish assignments.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

The student can name how data is used in sales context. He/she knows how to gather sales data. He/she is aware of how artificial intelligence is used in sales. The student can make general decisions based on sales data.
The student meet the minimum course objectives. He/she participate in the contact lessons. The student complete the course assignments on a satisfactory level. The student's performance indicate that he/she meet the minimum requirements set in the curriculum of the course.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

The student is familiar with using data in sales context. He/she knows how to gather, analyze and interpret sales data. He/she is aware of how artificial intelligence is used in sales. The student can make decisions based on sales data.
The student meet the course objectives. He/she participate in the contact lessons. The student complete the course assignments. The student's performance indicate that he/she meet the requirements set in the curriculum of the course.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

The student is highly competent in using data in sales context. He/she possess a comprehensive understanding of gathering, analyzing and interpreting sales data. He/she is familiar with the application of artificial intelligence in sales. The student can make meaningful decisions for the company based on sales data.
The student meet the course objectives sovereignly. He/she successfully participate in the contact lessons. The student complete the course assignments on a distinguished level. The student's performance indicate that he/she has outstandingly fulfilling all the requirements set in the curriculum of the course.