Analyst and Data Scientist skill set in Digital Marketing. Reasons to go to Web Analytics. Part 1.

Today most of the business somehow works in the network, and the main weapon of the online business is the data. And the more data, the more correct decisions can be made by company employees.

It is important to work with the data, because today it is the source of accurate answers to questions about the product and marketing. Previously, companies had to either guess, or rely on long-term studies.

At the beginning of the century, there was very little available data. Then companies learned how to work with analytics in real time, and the Internet marketer cope with the amount of information. Now there is a lot of data. So much that the specialist has to deal with it. Even a small online store gets 200-300 advertising campaigns a week. These campaigns are divided into different segments, different value propositions and go through several steps. To understand which campaigns work, companies need to track the path for each of them from the first touch to the target action. There are other sources, there is user behavior after purchase. In short, there is a lot of interesting.

The work with data looks like this: for example, a marketer needs to calculate ROI from the spent advertising campaigns. He asks the web analytics to build funnels for campaigns. Further, knowing the budget and the cost of production, the marketer concludes whether the campaign worked or not. Also product managers, business developers, traffic managers, even PR specialists need web analytics help. The web analyst is their eyes, without which the work gets complicated.

Data need to be collected, cleared and based on it correct conclusions can be made.

Collect - means to be able to find data. It's like hunting: you need to place traps in the right places, if you want someone to be caught.

Clean - sometimes extra data makes you only confused. The web analyst must know exactly what is important for making a decision. This requires an understanding of business metrics and business objectives.

Interpret - to make the right conclusion, you need to understand the logic of decision making. Ultimately, marketers interpret the data, but without understanding the logic, the web analyst risks giving the wrong answer.

Web-analysts should have following qualities: love of numbers, love for accuracy, meticulousness, curiosity, ingenuity. Students from the faculties of applied mathematics, statistics, sociology, and others, where there is an emphasis on numbers can try to work in this field, and just those who like to dig into the information.

5 reasons to look in the direction of web analytics.

1. The growing demand for specialists

A few years ago, only one digital company out of 20 had a web analyst. Today there is a web analyst in 1 out of 10 companies. Tomorrow this position will be in each company.

2. Career growth

Web-analyst works in tandem with other specialists and quickly absorbs knowledge from related professions. This helps to get horizontal growth. If you get bored, there is always marketing, business development and other professions, in which knowledge of web analytics systems also add weight.

3. Interesting problems

There are no two identical funnels. Web analytics is a constant explosion of the brain, a constant search for truth, digging deep into the information noise.

4. Self- assessment

Everyone wants to be friends with a web analyst, because spoiling the relationship it's easy to lose "vision."

5. Non-career development

Working with data is a useful skill in life. A person who devotes himself to this profession, perceives reality differently, becomes more pragmatic and more rational.

How about this news which proofs that data scientist and analyst are perspective professions. HR Company Glassdoor named 25 best jobs in the US for 2017, the leader of the rating is the data scientist profession. In the 2015 ranking, the data researcher's job was ninth, with the assistant doctor on the first place. The list also includes the profession of analyst, UX designer, hiring manager, tax manager, mobile application developer, marketing manager and electrical engineer. When compiling the rating, Glassdoor specialists were based on anonymous feedback from employees.

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