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What is AI analytics, and why should you use it for your business?

AI analytics

Marketers and entrepreneurs often tout the expression, “Data is King.” It is—and it’s an oppressive king at that. With so much data at our fingertips, it can be difficult and tedious to navigate and interpret.

You may be asking yourself, “What does this all really mean for my business? Am I looking at it the wrong way?” Enough people have these questions, that, these days, we’ve got AI doing the work. Artificial intelligence analytics (a.k.a., AI analytics) tools have become the go-to solution for a wide range of tasks, from figuring out how to make a website meet its goals to wrapping your head around your customer behavior data.

But the concept of AI analytics is still nebulous enough that it can be difficult to grasp. In this article, we're going to demystify AI analytics. We'll break down what it is, how you can put it to work for your business and the best AI data analytics tools available in the market right now. So, get ready to dive into the world of AI analytics and see how it can be a game-changer for your business.

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What is AI analytics?

AI analytics is a type of business intelligence that blends the power of artificial intelligence and machine learning to extract insights from data that can help businesses make better decisions. It can help you see your operations, customers, competitors and market dynamics in a whole new light.

AI analytics automates many of the tasks that data analysts traditionally perform, such as data cleaning, feature engineering and model building. This frees up data analysts to focus on more strategic tasks, such as developing new insights and using AI analytics to drive business decisions.

AI in analytics can also help to streamline data analysis by funneling all data into one solution. This gives you a single view of your data, which makes it easier to identify patterns, trends and anomalies.

How is AI analytics different from traditional analytics?

Business tools that collect, summarize and visualize data have been on the market for years now, but until recently, the ability to pull insights from this information has depended on human analysis. Because AI analytics are machine-led, they deliver insights at a speed, accuracy and scale beyond what is possible with traditional methods. Other key differences between AI analytics and traditional analytics include:

  • Data types: Whereas traditional analytic methods are limited in that they require structured data such as spreadsheets and databases, AI analytics can interpret semi-structured and unstructured data as well.

  • Automation: Traditional analytics involve a significant amount of work, much of which is repetitive and tedious. AI analytics differ in that they automate data analysis tasks—like data cleaning, feature engineering and model building—and so require less manpower.

  • Insights: Because traditional data analytics tools rely on human interpretation, they’re susceptible to guesswork, error and bias. AI analytics tools, on the other hand, rely on machine learning algorithms that are designed to process data objectively and consistently.

While traditional analytics relies on structured data, involves significant manual work and is susceptible to human error, AI analytics can parse unstructured data, automates tasks like data cleaning and uses machine learning to process data consistently.

How can AI analytics help my business?

AI analytics provides actionable insights that can help you optimize operations, enhance customer experiences, reduce costs and ultimately drive growth and profitability. Let’s discuss a few common AI analytics use cases to give you a sense of how it can support your business.

Customer insights

Leveraging AI for customer analytics offers a comprehensive understanding of your customer base. This means it can unveil what products pique their interest, the timing of their purchasing tendencies and even their willingness to spend. Moreover, AI can expertly segment customers based on demographics and purchase history, giving you an intricate map of your clientele.

But the power of AI analytics doesn't stop there. It can also detect potential customer churn by recognizing behavioral patterns. For example, AI may pick up on the fact that a customer is engaging less frequently, letting you know that you should take proactive steps to re-engage them, such as offering personalized incentives or targeted communication.

Website management

When it comes to website management, AI takes on the role of a vigilant overseer. It delves into behavioral analytics, tracking user actions on your site. From tracking bounce rates to time spent on pages to interactions with ads and CTAs, it leaves no stone unturned. This data can pinpoint structural issues like speed optimization problems that deter user engagement.

Inventory management

In retail and eCommerce, AI analytics can quickly and accurately interpret historical sales data, the seasonality of your business and market trends. With this information, you can better predict demand and avoid over- or understocking.

Cost reduction

In the cost-reduction vein, AI analytics can function like a team of financial experts that works tirelessly to ensure that your business operates efficiently and cost-effectively. It can help you identify areas where you can cut expenses, predict maintenance needs to prevent costly breakdowns, optimize your supply chain to reduce carrying costs and safeguard your financial transactions from potential fraud.

Marketing campaign optimization

AI analytics excels in real-time campaign performance analysis. It can meticulously track crucial metrics like click-through rates, conversion rates and customer engagement to keep your marketing campaigns on the right track.

Moreover, AI brings a smart approach to resource allocation. It can identify the channels, platforms or ad types that deliver the best return on investment (ROI). This insight is like a compass, guiding you to distribute your budget effectively, maximizing the impact of your campaigns.

But AI goes beyond conventional analysis; it’s a driver of innovation. Through A/B testing, it empowers you to experiment with different campaign elements. Subsequently, AI evaluates the results, highlighting which variations are outperforming the rest.

4 best AI tools for data analytics

Take a look at four AI tools that are transforming data analysis and decision-making across industries.

01. Wix’s benchmarking tool

Wix Analytics tracks things like website traffic, sales data and visitor behavior to help you identify opportunities to improve your website and achieve your business goals.

One of the most powerful features of Wix Analytics is the AI-powered Benchmarks report. This tool compares your website's performance to other websites in your industry and of similar size. It synthesizes the information into digestible graphs and charts to help you understand your essential web analytics. It also provides tips for improving on areas in which your site is underperforming.

Wix's AI analytics

02. RapidMiner

RapidMiner is a data analysis tool that can read many forms of data, including texts, photos and audio files. Insights and predictive models help you understand and solve your business issues. RapidMiner offers an intuitive user experience with a drag-and-drop framework, making it an accessible AI option for users of any skill set.

RapidMiner AI analytics

03. Tableau

Tableau is an analytics and data visualization platform that helps you easily see and understand your data. Tableau’s Ask Data feature allows you to ask questions and receive answers in the form of quick graphic responses. Tableau doesn’t require any knowledge of coding and makes it easy to create reports and share desktop and mobile analytics.

Tableau AI analytics

04. Qlik Sense

Qlik Sense is an associative data model with a user-friendly drag-and-drop interface, ensuring that even beginners can effortlessly establish connections among vast sets of data. Leveraging machine learning, it continuously enhances visualizations and analytics, tailoring them to your specific requirements. Qlik Sense acts as a data-indexing wizard, comprehensively mapping out relationships within your data, facilitating seamless exploration and search capabilities. With smart data preparation, you're equipped to establish an array of data connections from multiple sources with limitless possibilities.

Qlik Sense AI analytics

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