So, are you a Digital Marketer who knows to run paid ads on Google and Facebook.
Believe me, in today’s time one of the easiest jobs is running digital ad campaigns on Facebook and Google.
I am sure you agree on that part
But, the challenge always comes on how to optimize these campaigns at the best. It’s very difficult to identify what’s exactly working for a campaign.
Let’s identify the most common challenges faced by Digital Marketers or say paid media specialists while running paid media ads.
Most of the time we don’t exactly know why or why a conversion did not happen. What type of targeting, placements ,creatives is actually leading to a conversion. Or what is going wrong in the campaign due to which there are no conversions
So, basically we are not able to figure the WHY behind the things.
With so many channels available, obviously major channels being Facebook and google ads, it’s very important to choose the right channel for the right type of campaign. Often we are confused about which channel we should advertise in order to get the maximum ROI possible.
The third and most important of all is the budget. Since we always want to get maximum results out of our budget. It’s a very challenging task for a digital marketer to allocate the right amount of budget to any given channel.
These are the major problems faced by today’s Digital Marketers. In order to maximize the campaign performance and optimize the campaign to the fullest let’s see what we can do. And how to solve these problems.
To get a solution to the above problems we have to do a deep down data analysis to a granular level.
Here is where python comes to the rescue.
While learning to code in python is not necessary for Digital Marketer, doing so can definitely help to analyze Digital Marketing campaigns at granular level.
By just learning basic python you can analyze and optimize your Facebook as well as Google ads campaigns and derive actionable insights.
Basically, you will be able to identify areas where your budget is getting wasted. Hence, you will be able to optimize your marketing campaigns better. Learning python and applying on your own is always affordable and exciting.
We are happy to share with you about the Online Certification Course on Using Data Science in Digital Marketing by Medialytics Ninja
This course will basically help you to analyse, optimize and automate the digital marketing campaigns using data analytics tools like Python.
Watch the below video to understand how python can help you optimize your campaigns
Video Guide: Python for Digital Marketing
Once you enroll for this course, you get lifetime access to all the videos + frameworks to analyze your campaigns by directly importing the campaign data.
Also, the course has been developed keeping in mind Absolute Beginners
What will you learn in the course?
- Marketing Analytics Framework
- Basics of Python
- Python Libraries: Pandas, Seaborn
- Important Metrics in Digital Campaigns
- Data Cleaning, Wrangling & Sorting
- Feature Engineering
- Campaign KPIs Visualization
- Combined Effect of various factors like Ad Copy, Creative, Targeting, Time, Platform etc. on CTR & Conversions in a single graph
- Preventing Budget Wastage on Channels
- Reporting Actionable Insights
Python for Digital Marketing course is available only at INR 499/- for a limited time.
Yes, less than a price for your pizza or dinner!
Over 1500+ Digital Marketers have already enrolled for the course in the last 3 months, and you should also go for it without giving a second thought.
Lots of big companies spending money on marketing automation.Digital Marketing automation will be the next big thing in the upcoming years.and this course will surely help you to be prepared for those times.
So, what are you waiting for, enroll today and optimize your campaign like a pro!
Disclaimer: We are an official affiliate for the course and we only promote those products which we truly believe that will provide value to our readers. The purchase won’t cost you anything extra but we will get a small amount to keep this site running.