Business Intelligence

Guide to conducting an in-depth customer behavior analysis using AI

by
Craig Wisneski
,
March 19, 2022

Want to know what makes your customers tick? Turns out, artificial intelligence can help.

Behavioral analytics is one of the most important and complex aspects of customer experience management. It’s also one of the areas where AI can have the most impact. By analyzing customer behavior, you can gain insights that can help you improve your product, marketing, and sales strategies. 

In this article, we’ll look at how machine learning can be used to analyze customer behavior and what benefits this can bring.

What is customer behavior analysis? 

Before the age of the Internet, business owners and marketers could only roughly guess what customers wanted and how they behaved. With the advent of customer behavior analytics, these guesses can now be replaced with hard data.

So, what is customer behavior analytics? Simply put, it’s the process of tracking and analyzing customer behavior throughout the customer journey in order to better understand what they want and need. This information can then be used to improve customer engagement, increase conversions, and boost sales.

Some of the primary methods used for gathering customer behavior data include website analytics, surveys, focus groups, and interviews. Once this data has been collected from demographic data to buying habits, it is then analyzed to identify trends and customer behavior patterns. This analysis can reveal a great deal about what motivates customers and how they make purchasing decisions.

Customer behavior analytics offers a number of benefits for businesses. Perhaps the most obvious benefit is the ability to better understand customer needs and wants. Armed with this knowledge, businesses can create targeted marketing campaigns that speak directly to customers’ needs. Additionally, businesses can use customer behavior data to improve the user experience on their websites and create products that are more likely to appeal to customers.

Customer behavior analytics can also help businesses identify potential problems before they become major issues. For example, if a significant number of customers are abandoning their shopping carts at a certain point in the checkout process, this could be an indication that there is a problem with the checkout process that needs to be fixed.

Overall, customer behavior analytics provides businesses with an invaluable tool for understanding their customers better. Armed with this information, businesses can create more effective marketing campaigns, improve the user experience on their websites, and create products that are more likely to appeal to customers.

What are the benefits of customer behavior analysis?

Customer behavior analysis isn't just about predicting what people are going to do next. It's about understanding what motivates them and how they interact with your company. That understanding can lead to all sorts of benefits, both for the customers and for the business.

One of the most obvious benefits is customer retention. If you know what makes your customers happy, you can work to keep them happy. You can also identify any potential problems before they become serious issues.

Customer behavior analysis can also help you to develop more effective marketing campaigns. You can target your ads and promotions more accurately, and you can test different approaches to see what works best.

And finally, customer behavior analysis can help you to improve your products and services. You can see what features are most popular, and you can learn which ones need improvement. You can also find out what kinds of pricing strategies work best for your products.

In short, customer behavior analysis is a powerful tool that can help you to improve your business in many ways. If you're not already using it, you should seriously consider doing so.

How does AI factor into conducting customer behavior analysis?

Artificial intelligence has become an increasingly important factor in conducting customer behavior analysis. It allows businesses to process large amounts of data in order to make informed decisions about their customers. This is done by using algorithms to identify patterns in customer data, and then using these patterns to predict future customer behavior.

There are many benefits to using AI for customer behavior analysis. First, it allows businesses to get a better understanding of who their customers are and what they want. AI can help businesses target their marketing efforts more effectively, and it can also help them create more personalized customer experiences. Additionally, AI can be used to identify potential problems before they become too serious. For example, if a business notices that a particular product is not selling well, AI can be used to determine the reason why.

While AI offers many benefits, there are also some potential drawbacks. One potential issue is that AI can sometimes be inaccurate when predicting customer behavior. Additionally, businesses need to be careful not to rely too heavily on AI, as this could lead to decision-making based on faulty data.

Overall, AI is a powerful tool that can be used to improve customer behavior analysis. It allows businesses to gain a deeper understanding of their customers, and it can help them identify and solve problems before they become too serious. While there are some potential drawbacks to using AI, these can largely be avoided by taking the time to properly train AI algorithms and by ensuring that data is accurate.

Additional use cases of using AI for custom behavior analysis

While the examples above cover some general applications of AI for customer behavior analysis, there are many other use cases that can be explored.

One common use case for AI in customer behavior analysis is predicting churn. AI can be used to identify customers who are at risk of leaving, and businesses can then use this information to create targeted campaigns aimed at preventing churn.

Another common use case for AI is predicting average order value (AOV) and lifetime value (LTV). AI can be used to identify customers who are likely to spend more money in the future, and businesses can then use this information to make more informed decisions about their product offerings.

Finally, AI can also be used to predict cross-sell and up-sell opportunities. This can be done by identifying customers who are likely to be interested in certain products, and businesses can then use this information to create targeted marketing campaigns.

How do I conduct an in-depth customer behavior analysis using AI?

It’s no secret that businesses need to understand their customers in order to succeed. However, many businesses rely on expensive and complex legacy AI tools or programming in order to accomplish this task. This can be slow and difficult, and it can be hard to get a comprehensive view of customer behavior.

A better way to do this is with Akkio’s no-code AI. Akkio is a platform that enables you to build predictive models without any programming. It uses a library of algorithms that have been pre-tuned for performance, so you don’t need to be an expert in machine learning in order to use it.

Akkio can help you quickly and easily build models that analyze customer behavior. You can use it to discover important insights, such as who your best customers are, what they buy, and what drives their buying behavior. You can also use it to identify potential areas for improvement, such as which products are underperforming or which marketing campaigns are not resonating with your target audience.

From there, you can modify your marketing strategy, improving your funnel based on hard quantitative data, whether it’s improving customer acquisition or improving retention of your customer base.

Akkio makes it easy to get started with consumer behavior analysis. All you need is a data set of customer actions (either from your own business or from a public source) and you can be up and running in minutes. You can then use the Akkio interface to connect your dataset into an AI workflow, and the platform will automatically optimize a model for you.

Once your model is built, you can export predictions to other applications or simply keep it on Akkio for future reference. You can also view customer segments, share your models with other team members, and understand purchase behavior and KPIs from one interface. Unlike legacy analytics platforms and dashboards, Akkio makes it possible to gain insights in real-time and bring automation to your sales and marketing initiatives, from lead scoring to churn prediction.

Akkio is the perfect tool for businesses that want to take a data-driven approach to understanding customer behavior. With its easy-to-use interface and powerful algorithms, it makes it easy for anyone to build predictive models that provide valuable insights into how customers behave.

Steps to use Akkio to conduct in-depth customer behavior analysis

Building a customer behavior analytics pipeline from scratch can be daunting. There are many moving pieces, and getting it wrong can be costly. Legacy tools can be inflexible and difficult to use, which can lead to inaccurate results.

Akkio is a tool that can help you overcome these challenges. It automates the process of building predictive models, so you can focus on getting the most accurate results. And it’s easy to use - you can deploy your models in just a few clicks.

To get started, you first need to connect your data sources. Akkio can work with a wide range of data formats, including SQL, Excel, and JSON. You then select the columns you want to analyze, and Akkio automatically builds a predictive model. You can then deploy your model anywhere you need it - including on your website, in your mobile app, or in tools like Salesforce and Snowflake.

Akkio can be used for a variety of applications, including churn reduction, LTV prediction, lead scoring, and much more. By using Akkio, you can make better decisions about how to treat your customers and increase your profits.

For instance, suppose your business was facing the ignominious problem of customer churn. You could use Akkio to build a predictive model that identifies which customers are most likely to churn. This would allow you to focus your efforts on retaining those customers, and increase your chances of keeping them.

Or suppose you want to increase your customer Lifetime Value (LTV). You could use Akkio to build a model that predicts how much a customer is worth to your company over the course of their lifetime. Armed with this information, you can make decisions about how best to invest in customer retention efforts.

Akkio can also be used for lead scoring. By predicting which leads are most likely to convert into customers, you can focus your sales efforts on the most promising leads. This can result in more closed deals and increased profits.

The possibilities are endless. Akkio can help you analyze your customer data and gain insights that will lead to better decisions and increased profits. Try it today and see the difference it makes.

AI pro-tips

AI has become easier to use than ever before, but that doesn't mean you can just dive in without doing your homework. You need to use the right data sources and tools to get the most accurate results.

For example, if you want to know what parts of your website are most popular with visitors, you should use web analytics data. This data is collected from a variety of sources, including browsers, cookies, and servers, and it can give you a detailed breakdown of which pages are most popular and why.

If you're looking for social media data, Buffer or CrowdTangle are great tools to use. They both collect data from various social media platforms, and they both have built-in analytics tools that make it easy to see which posts are performing the best.

Google Analytics is another great tool for collecting data. It can give you detailed information about how people are finding and using your website, as well as insights into conversion rates and other key metrics.

Meanwhile, Salesforce and Zoho CRM are also great options for collecting sales data. They both offer comprehensive data collection features for sales pipeline, leads, and closed deals, among other things.

Conclusion

There's a lot of customer data out there, and businesses are constantly looking for ways to make sense of it all and figure out what to do with it. But customer behavior analysis is a complex process, and it can be tough to know where to start.

That's where Akkio comes in. Akkio is a no-code AI platform that makes it easy to analyze customer data and figure out what to do with it. With Akkio, you can quickly and easily create models that will help you understand customer behavior and figure out what to do next.

‍Sign up for a free trial today and see for yourself how easy it is to use Akkio for customer behavior analysis.

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