Marketing…analytics? How does marketing relate to data? Does it even relate to data? Well, yes.
Most people in the business world view marketing as a one-dimensional profession: making flyers, managing social media, and all other art-related tasks. Oftentimes, there’s a stigma around the level of analysis and critical thinking involved in marketing, but that is where firms go wrong.
Data is everywhere and marketing is a small branch within the data world that your firm should be aware of if you want to retain customers and track your campaigns’ performances.
From customer-centric marketing to targeting the right demographics to keeping up with fast-paced data trends, let’s dive into both the marketing campaigns you can run and the tools used on campaign data to draw valuable conclusions.
Here are just four of the most popular marketing campaigns:
- Search advertising and search engine optimization. Have you ever Googled how to do something? Where to get a service done? Chances are, everyone turns to Google when they are seeking information. Thus, you want to make sure your firm is using the best keywords, bidding on the position of where your ad is shown, and tracking metrics like impressions and click-through rate (CTR).
- Display advertising. Although display ads generate a smaller CTR, they are just as effective if your firm wants to bring awareness to the company to people for the first time.
- Mobile advertising. As smartphones have taken over the consumer world, there are vast marketing opportunities, whether this is through social media or apps. Make sure to utilize these often free tools to attract younger generations and keep up with your competitors.
- Email campaigns. Your firm likely already sends out emails to consumers or prospects. However, do you track the number of people who click on links? The unsubscription rate? These are pieces of data that should be monitored.
Now that we have established common marketing campaigns and the data that can come from them, let’s get into the tools used to draw conclusions from the data results. Here are four of the most popular:
- Logistic regression. Logistic regression can arguably be one of the most important tools in determining the different effects variables have on each other. For example, I could enter the variable, “saw_ad,” as an independent variable, and “purchased,” as another. The regression would be able to tell us the effect of seeing an ad on whether or not a user clicked on it and purchased a product. You can then conclude that the ad caused the purchase.
- RFM analysis. R stands for recency, F for frequency, and M for monetary. Marketing analysts use RFM to group consumers into different groups based on each variable. This method is used to analyze past spending behavior and target only those with the “best” predicted behavior going forward.
- Machine learning and artificial intelligence. Although complicated in nature, there are tests like neural networks that can be run through data software to work with large amounts of data.
- A/B testing. A/B testing can be done with almost anything. For example, you can send 500 consumers email A and 500 consumers email B. The difference in how they react will demonstrate the email that might be the more profitable email. From here, you can make the changes necessary or decide to send the better email out to the entire database.
Thus, there is data rooted in many popular marketing campaigns and many tools used to analyze such data. Start researching which campaigns and metrics work best with your firm’s capabilities to stay ahead of the stigma that marketing involves no data. Best of luck!