Data analytics are all the rage in marketing these days. Marketers use analytics to measure and manage their campaign performance, which helps them to see how effective their different strategies are, identify any problem areas, and thereby get better at optimizing the return on investment (ROI) of their marketing efforts. Data analytics also offer insights into various aspects of consumer behavior, allowing marketers to track and stay on top of the latest trends.
Even though there are many benefits to data analytics, several marketers are still intimidated by it. Others have tried it, but are dissatisfied with their results so far and so they quit early. Many marketers also feel like they would not have the time to learn how to analyze their data properly, or are unconvinced that analytics could really help improve their marketing efforts.
Still, with the amount of data produced worldwide, most business owners realize that taking the time to develop an analytics team will lead to greater success. In fact, many finance leaders are realizing that data isn’t just for analysts – it’s becoming necessary for all roles. Smart organizations will focus on encouraging data literacy in every job level, especially marketing!
Are you a marketer who doubts the advantages of adding data analytics to your already busy workflow? If so, keep reading below as we explain some everyday analytics concepts that are helpful to know for marketing. We also included some links to valuable resources on the internet that you can dive into and learn more. Start honing these analytics concepts now, and you will be able to use them in 2020 to impress your clients, get a raise from your boss, and take your marketing to the next level!
Sampling – A great low cost, low involvement method to quickly learn basics about your data and make decisions to do further studies or check the quality of your efforts.
- Sampling in Market Research – from SMstudy
- Sampling Techniques – from Towards Data Science
- A Gentle Introduction to Statistical Sampling and Resampling – from Machine Learning Mastery
Central Limit Theorem – An astonishing facet of the universe where pretty much everything tends towards the average of the population (heights of people, disposable income, average engagement, etc.).
- The Central Limit Theorem – from StatQuest with Josh Starmer
- Using the Central Limit Theorem in Business – from Study.com
- Central Limit Theorem: Definition and Examples in Easy Steps – from Statistics How To
Golden Ratio – Another mathematical pattern found in everything, from seashells to music to earthquakes to the next viral hit on YouTube.
- Golden Ratio – from Wolfram MathWorld
- What is the Golden Ratio? What You Need to Know and How to Use It – from Canva
- Using the Keyword Golden Ratio to Improve Conversion Rates for Affiliate Marketing – from SEMrush
Confidence Intervals – Two numbers you can use with an average to explain the variation in your data. Next time you compute an average in Excel, go the extra steps to calculate your 95% confidence interval and put it next to the average in brackets. This will give your boss some extra information about your data and looks impressive.
- Introduction to Confidence Intervals – from Lumen Learning
- How to Find a Confidence Interval: The Easy Way! – from Statistics How To
- Confidence Intervals: A Guide for A/B Testing – from Business 2 Community
Histogram – A useful frequency graph that visually maps the distribution of your data. Useful in targeting and identifying segmentation.
- Histogram – An Overview – from ScienceDirect
- Histograms, Clearly Explained – from StatQuest with Josh Starmer
- How to Make Histograms: Their Examples & Types – from Digital Vidya
Correlation – When two characteristics seem to have a relationship, they are called correlated. You can’t say that one causes the other, but there are some useful insights you can draw. Here’s an example: hotter days bringing people out to the beach might explain why ice cream sales go up when shark attacks go up.
- Statistics 101: Understanding Correlation – from Brandon Foltz
- Correlation vs. Causation in Marketing Analytics – from Socedo
- What is Correlation and How Can Marketers Use Correlation Effectively – from TapClicks