I work as a full-time data scientist, but I also do a lot of freelance SEO analytics projects. In fact, my first ‘data’ role was an SEO marketing analyst. Even though I no longer work in marketing full-time, I like to keep up with the trends, and I’m excited that more data driven marketing trends have emerged in recent years.
Based on my combined experience with digital marketing and data science, I created a list of the top five data driven marketing trends for 2023. Read on to learn more about applying data to your marketing strategy.
Predictive analytics can involve anything from a simple classification model, regression, or forecasting. Specifically in marketing, forecasting sales with time series models like Autoregressive Integrated Moving Average (ARIMA) is gaining traction.
A recent article by Capital One covers different types of ARIMA models for sales forecasting. This kind of work typically requires a data scientist but recent advances in technology have also lowered the barrier for entry by allowing analysts with less coding experience to leverage forecasting tools.
Another use case for predictive analytics in marketing is churn prediction. Depending on the predictive model, churn prediction can involve classifying customers or even predicting when they will churn so that you have the potential to intervene with an email, an advertisement, or a relevant blog post.
This ties in closely with predictive analytics because many of these models (ARIMA, logistic regression, random forest, survival analysis, etc.) are easily coded using Python. However, there are also useful tasks that can be automated with basic python scripts. For example, Search Engine Journal published an article listing 8 python libraries for SEO.
The requests library allows users to make api calls, which is incredibly useful when combining data from multiple marketing sources. For instance, AHREFS, SEMrush, and GA all have an api that can be accessed with python scripting. This not only helps automate reporting but also allows marketers to glean meaningful insights related to keyword research and competition.
As everyone transitions from universal analytics to GA4, it’s important to note the shift from different hit types to event-based modeling. In universal analytics there were page hits, event hits, ecommerce hits, and social interaction hits, but in GA4 all of these aspects are captured as events. This allows marketers to track more granular user behavior. In addition, GA4 has cross-device and cross-platform tracking which makes it possible to track engagement and conversions more accurately with the help of the event data model.
By shifting to GA4, marketers have the chance to dive deeper into their data and understand their customers. Therefore, it’s important to understand how to track different events in GA4 and event parameters like site search terms.
We all know about Chat-GPT by now, but have you heard about Auto-GPT? If you get an OpenAI api key, you can start leveraging the GPT model with python. Essentially, you can run the application and create prompts for the GPT model to complete tasks. Examples include writing code for an SEO project, building a web app, optimizing your Google Workspace, and even ordering a pizza when you’re working an 18-hour day.
It’s recommended that users set up a virtual environment or docker container to run Auto-GPT and they should also have a strong background in coding to understand the capabilities and limitations.
Yes, looker studio is a good option for GA and GSC reporting, but if you’re looking for a more sophisticated solution, you’ll want to check out either tableau or plotly. With tableau, you can create interactive dashboards and campaign managers by connecting multiple data sources and blending them. Coursera and Udemy both have courses for leveraging tableau for marketing analytics.
As someone who prefers coding with python, I think plotly is another great option. The great thing is that there’s a low code option too. Plotly is free to use on an individual level but if you’re looking to publish dashboards using Dash, you’ll want to look into the enterprise pricing. These types of data visualization tools can make the difference between a pretty dashboard and a dashboard that is actionable.
Whether you have an entire marketing analytics team or you’re working with a single analyst - these data-driven marketing trends for 2023 are valuable for agencies of all sizes. Get started with some of these tools by partnering with a trusted SEO agency. At Hire a Writer, our marketing analytics team is proficient in SQL, python, HTML, and more. Contact us today to learn more.
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