According to Forbes, “CMOs have the shortest tenure of anyone in the C-suite.” Why is that? One explanation is that as the amount of available data has exponentially increased, CMOs (and others in the marketing world) are spending more and more time tediously compiling metrics and less and less time actually “doing marketing”.
Is there a solution to this?
Nope, nothing can be done. End of article. Thanks for reading.
Of course there’s a solution….combining marketing analytics and automation! Automating marketing analytics enables an accurate and thorough compilation of all marketing data that is siloed across multiple platforms.
Warning: if you are a marketer who enjoys mind-numbingly tedious tasks and hates the thought of saving extra time to promote your company’s product and services, then the following information is not for you.
Before we get into the automation of marketing analytics, let’s first get a definition of what it is. Marketing analytics is the practice of measuring, managing, and analyzing data related to marketing campaigns and initiatives, with the goal of optimizing and improving their effectiveness.
Basically, let’s look at a bunch of numbers and if most of them are going in the right direction then what we are doing is working.
Using a wide range of techniques, tools, and methods, such as predictive modeling, segmentation analysis, and A/B testing, data is collected and analyzed from multiple sources, such as customer behavior, sales data, and market trends.
Without marketing analytics, you're just guessing; and If you're just guessing, you're likely lighting money on fire.
A few things marketing analytics can be used to measure are the ROI of marketing campaigns in order to determine which channels and tactics are most effective, whether the most profitable customer segments are being targeted with relevant messaging, and what actions a customer’s future behavior may include.
Marketing analytics is essential for knowing if your campaigns and strategies are working. The problem, though, is the process. First, you have to scramble to pull data from many different analytics services, aggregate it, try to cobble it into something halfway presentable (and understandable), and then hope that your data aligns with the sales team.
There is a better way.
Automating marketing analytics refers to the process of using technology, software, and algorithms to streamline and optimize marketing data collection and perform analytical tasks and data processing. By leveraging tools such as artificial intelligence, machine learning, and data visualization, you can create a more efficient and effective system for understanding customer behavior, identifying trends and patterns, and making data-driven decisions.
When you automate marketing analytics, it can reduce errors that may arise from manual data entry. It can also help marketers to identify patterns, trends, and correlations that might be hard to notice with manual analysis, and use this information to optimize their marketing strategies.
Automation makes processes faster, more efficient, and more accurate. But how does that specifically translate into making it easier to report marketing data?
When automated, here’s what the following looks like:
Dashboards: Provide a visual representation of key marketing metrics in real-time to quickly identify trends and track progress.
Email Marketing: Trigger specific actions based on customer behavior.
Predictive Analytics/Modeling: Forecast future trends and proactively adjust campaigns and strategies. (e.g. identify customer segments with high purchase intent)
Social Media Listening/Monitoring: Track brand mentions, engagement rates, and respond to customer inquiries or complaints. Basically, slay the dark funnel.
A/B Testing: Test different versions of web pages, emails, or ads to optimize conversion rates and determine what resonates best with their target audience.
Reporting: Automatically generate reports based on pre-defined metrics and KPIs.
Web Analytics: Track website traffic, user behavior, conversion rates, and other website performance metrics.
If you buy a Ferrari but neglect to perform regular oil changes and tire rotations, then it’s not going to perform optimally. Likewise, if you automate your marketing analytics but neglect some of the following best practices, then it won't deliver the desired results.
Before implementing any automation, you need to make sure it’s aligned with your business objectives. To do this, you need to define your marketing goals, key performance indicators, and be clear about the key metrics you wish to track (e.g. conversion rates, customer acquisition cost, customer lifetime value).
You can use the data you have collected to create custom reports that show your key metrics and KPIs. This will allow you to track your progress and identify areas where you need to improve.
Marketing analytics automation relies heavily on accurate and reliable data. Ensure that your data is clean, complete, and up-to-date before automating any processes.
There are a host of marketing analytics automation tools available, but not all of them will be right for your business. Choose the tools that best align with your needs, goals, and budget, and ensure that they integrate with your existing marketing technology stack.
Move over Salesforce. HubSpot is a powerful tool that can help you track and analyze your marketing efforts. Some key features and benefits of marketing analytics automation in HubSpot include data tracking, customizable reports, automated data analysis, real-time collaboration, attribution reporting, and A/B testing.
Marketing analytics automation will be most effective when there is adoption of a culture of data-driven decision making within the organization. To do this, encourage teams to use data to inform their decision making and prioritize data literacy training. In addition, a framework should be established which outlines roles, responsibilities, and workflows.
Regularly monitor the performance of your processes to ensure that they are delivering the expected results. Use the data collected to optimize and improve the processes over time and test different strategies and tactics to see what works best and make changes accordingly.
Automation makes everything better. Well, almost everything. While there are many potential benefits of automating marketing analytics, there are also some potential drawbacks and disadvantages to consider.
Marketing analytics automation is not completely “set it and forget it” (at least not yet). The tools can make mistakes or provide inaccurate results if they are not properly calibrated. Without human oversight, these mistakes may go unnoticed and lead to incorrect conclusions or decisions. Also, these tools lack human intuition, meaning they are designed to follow predetermined rules and patterns, but they may not always account for factors that only a human can detect or understand.
This stuff ain't cheap, especially if you need to purchase specialized software or hardware. Smaller companies may not have the budget to invest in such tools, while larger companies may need to allocate a significant amount of resources to upkeep and upgrade them.
Anytime you’re collecting and analyzing data, privacy regarding customer information needs to be among the biggest priorities. Automated marketing analytics tools require access to sensitive customer data which can increase the risk of data breaches or cyber attacks. It is important to ensure that these tools are used ethically and in compliance with relevant laws and regulations.
Although data is the lifeblood of marketing analytics, it should not be the only factor considered. Over-reliance on data can lead to tunnel vision, where marketers become fixated on the numbers without considering other important factors such as customer feedback, market trends, or industry insights.
There’s an endless amount of data, and it's only going to grow exponentially over time. By automating marketing analytics, you can proactively adjust strategies and save time on repetitive tasks while improving accuracy. As long as you remember that human oversight is still needed and that data is not the be-all-end-all, then your data collection process will be much more efficient and productive. And who knows, it may even help some CMOs stick around a little longer.