Around 329 million terabytes of data are generated, copied, consumed, or captured every day*. And, whether you’re representing a large organization, a small team, or simply your own small side hustle, you need to be able to analyze all those numbers to see your business thrive.
For a team, it’s a daunting task; for an individual, it can be downright impossible.
For a machine, though? Well…
Below, we talk you through everything AI (Artificial Intelligence) analytics. What are they? How can they improve your web analytics endeavors? And what are the key aspects of AI analytics you need to know about – in terms of both benefits and challenges?
Let’s take a look.
AI analytics refers to the application of AI and machine learning techniques to analyze and interpret complex datasets. It involves crunching these numbers, and – through the use of algorithms, statistical models, and computational power – deriving from them meaningful insights, patterns, and predictions.
AI analytics can automate repetitive tasks, uncover hidden patterns, and make accurate inferences and predictions – all in a timeframe that would be impossible even for whole teams of the most highly trained humans. With AI, you can unlock deeper insights, improve the efficiency of your work and decision making, and use data to inform your business’s future.
Some examples of AI analytics tools include:
- Google Cloud AutoML
- Microsoft Azure Cognitive Services
- Tableau (from Salesforce)
- Amazon SageMaker
- IBM Watson Analytics
Google Analytics 4 (GA4), while not an AI analytics tool by trade, does incorporate elements of AI and machine learning capabilities. To learn more about the platform and how to add it to your web analytics setup, explore our step-by-step guide to how to set up GA4.
Whether you’re in charge of analyzing a one-person hobby website or data for a huge organization, AI can help you achieve various aims.
Some of the ways AI analytics can improve your web analytics include:
- Enhanced data accuracy and precision: AI algorithms – machine learning models in particular – can be trained to process colossal datasets with high levels of accuracy. This reduces the impact of human error and means that the algorithms – which learn from historical data patterns to predict what’s ahead – can offer more precise results in the long run.
- Real-time analysis and actionable insights: by facilitating data analysis in real time, AI offers immediate insights into trends and patterns – even as they shift and evolve – allowing you to respond faster to emerging opportunities,
- Improved anomaly detection for potential issues: with AI as a live, ever-updating resource that not only learns normal patterns but deviations from them, too, you’ll be able to act quickly to address potential issues or threats as they arise. In large organizations, where cyber attacks and data breaches are an all-too-real threat, this capability is particularly crucial for recognizing and acting on unusual data patterns.
- Personalization and user behavior prediction: through AI, you can personalize your analytics to your specific user preferences. By understanding your behavior, AI can predict your preferences and proclivities, offering personalized content or recommendations, contributing to more effective marketing strategies and enhancing your overall experience as a user.
Want to learn more about the intersection of AI, marketing, and business technology? Read our top 10 list of the best AI marketing tools to benefit your online brand.
We’ve already touched on a few of AI analytics’s benefits – personalization, speed, accuracy – but the fact is that the drawcards of AI analytics surpass mere number crunching. Moreover, they encompass increased efficiency, improved decision making, and enhanced customer satisfaction, right across the board.
So what kind of boost can AI analytics give your analytical efforts?
Well for a start, AI analytics can:
- Save you money and time: by automating repetitive tasks, AI means you don’t need manual (read: human) labor when it comes to data processing and analysis. This frees up your time, and – because AI doesn’t need to sleep, eat, take breaks, or command a hefty salary – saves you a large chunk of your operational costs, too.
- Boost customer loyalty: by using AI to analyze customer behavior, preferences, and feedback, you can tailor your products and services to your client base, and use targeted marketing to meet their unique needs. By demonstrating to your customers that you see them as individuals – rather than mere numbers – you can increase their levels of loyalty and satisfaction, and improve their overall experience with your brand.
- Prevent fraud: by identifying unusual patterns and behaviors, machine learning algorithms can detect – and prevent – fraudulent activities in real time, safeguarding your customers’ most sensitive data and maintaining trust with your client base.
- Streamline your business’s operations: with AI automating tasks and optimizing processes, you can revolutionize once-mundane jobs: from inventory and supply chain management to demand forecasting. More efficient workflows, fewer mistakes, and improved performance throughout your business? Sounds good to us!
To learn more about AI’s benefits for the consumer, specifically, zoom in for a closer look at how you can improve the customer experience with AI.
Despite the wealth of benefits AI analytics offers, it does come with a range of considerations you’ll need to be mindful of before you jump in.
- Data privacy concerns and ethical considerations: just as AI analytics takes its strength from huge datasets, that data is – somewhat ironically – one of its big issues, too. As AI analytics relies heavily on data, privacy concerns regarding that information’s collection, storage, and use naturally arise. So, too, will you need to address ethical considerations – such as algorithmic bias and the responsible use of AI – to maintain trust with your fellow team, plus customers, and stakeholders.
- Initial implementation costs and resource requirements: putting AI analytics systems into place often requires a hefty outlay – with investments in technology, infrastructure, and skilled personnel all adding to the balance sheet.
- Need for skilled professionals to interpret and manage AI-driven insights: while AI analytics tools are brilliant, they – like most forms of AI – require a human touch to get the most out of them. And without a data scientist, AI specialist, or analytics expert, you might struggle to get the very best out of your AI web analytics tool or approach.
- Overcoming resistance to change within organizations: your company might fully realize the benefits of AI analytics – and if so, brilliant. But if your colleagues and superiors are the type to accuse AI of “stealing our jobs”, then you might have some mindsets to change. Fortunately, there are many strategies – including change management, clear communication, and inclusive education – that can help overcome this resistance, and instead foster a culture of innovation and open-mindedness.
In one article, we spoke at length about the transformative potential of AI in ecommerce. In another, we discussed AI and the future of web design. And here, we’ve discussed AI’s role in real-time data analysis, anomaly detection, and predictive modeling – and its ability to enable faster, more effective decision making.
But really, analytics, web design, and ecommerce merely scratch the surface of AI’s full capabilities. In a year of ChatGPT, Midjourney, and wearable AI devices, it’s clear that we’re only at the beginning of AI’s odyssey.
As for your – and your business’s – odyssey, where are you hoping AI takes you?
Let us know in the comments section below!
Because of this, AI analytics excels in handling unstructured data and providing proactive, personalized recommendations – which means that it’s perfect for the data handling needs of most modern businesses.
What’s more, AI’s ability to handle diverse data types, from clicks to unstructured content, provides a more comprehensive understanding of user interactions. This adaptability goes hand in hand with accuracy – giving you more precise insights into user engagement and website performance.
To combat this, you’ll need to work hard to stay informed and compliant with all the relevant regulations, remain committed to transparent data practices, and ensure all the right safeguards are in place at your business.