Published on

November 24, 2023


6 Ways That No-Code AI Can Uncover Valuable Customer Insights In 2022

In this article, we look at how no-code AI can be used to uncover valuable customer insights. 
Craig Wisneski
Co-Founder & Head of G&A, Akkio

Implementing AI used to require a team of data scientists and engineers to constantly monitor and adjust algorithms. But as no-code AI platforms have matured, they’ve become much easier to use—putting valuable customer insights within reach of any business, regardless of size.

In particular, customer experience (CX) can make or break your business, and Harvard research shows that the most widely used CX measures fail to adequately tell companies what customers really think and feel. 

With customer insights AI, businesses can tap into a goldmine of data to better uncover CX patterns and trends. This includes CRM systems, emails, social media, call center nodes, chatbots, and more. Given that, it’s no wonder that 93% of market researchers describe AI as an industry opportunity.

While this may seem like a daunting prospect, the truth is that no-code tools make machine learning remarkably easy to use. All you need to do is upload your data to the cloud platform and let the tool do its job. As a result, even small businesses can take advantage of these powerful tools to gain valuable insights into their customers’ behavior and preferences.

In this article, we'll look at how no-code AI can be used to uncover valuable customer insights.

AI Is a Game Changer

The number of businesses adopting AI has grown by 270% in the last few years, and now over 90% of top businesses report having an ongoing investment in AI.

It's no wonder, then, that AI spending is expected to reach half a trillion dollars by 2023. With such massive growth, it's clear that AI is here to stay.

 A chart showing the growth of the machine learning market from 2021 to 2030.
Source: Precedence Research

If you’re not using AI, you’re already behind the curve. There are countless ways businesses can use AI to increase efficiency and output. In some cases, AI can even automate human tasks.

Sales and marketing teams, for example, can use customer insights AI to reduce churn, optimize the sales funnel, predict customer lifetime value (LTV), and more. Let’s explore a few of these applications.

1. Understanding churn

Churn is the rate at which customers leave a company, and it can be costly for businesses. In fact, it’s often said that acquiring a new customer is five times more expensive than retaining an existing one.

AI can help sales and marketing teams reduce churn by providing insights into why customers leave. For example, if you’re using AI to predict customer LTV, you can identify which customers are most likely to churn and take action to prevent it.

Like a leaky faucet, a little bit of churn can be costly over time. Consider the example of then-incumvent Blockbuster slowly losing customers to the upstart Netflix. Over a decade, that small amount of customer churn compounded, and Blockbuster ultimately went bankrupt while Netflix became one of the most successful companies in the world.

That said, Netflix can't afford to rest on its laurels. With the likes of Disney+ and HBO Max all entering the streaming wars, Netflix will need to use AI to find ways to keep its customer base loyal. Recent events have highlighted this fact, as Netflix is set to lose millions of subscribers in the wake of rising competition.

AI is helping companies reduce churn rates across the board by providing insights into customer behavior. For example, some companies are using AI to monitor social media for early signs of customer dissatisfaction. Others are using predictive analytics to identify which customers are at risk of leaving and taking action to prevent it. By reducing churn, AI is helping companies save money and stay competitive.

2. Sales funnel optimization

The sales funnel is the process that leads customers from being aware of a product or service to becoming a paying customer. Optimizing the sales funnel can be tricky, but AI can help.

For example, AI can be used to predict which leads are most likely to convert into customers. This can help sales teams focus their efforts on the most promising leads, resulting in a more efficient sales process.

Consider an e-commerce company that is using AI to monitor customer behavior on their website. By tracking which pages customers visit, how long they spend on each page, and what products they purchase, the company can build a detailed profile of each customer. This information can then be used to target each customer with personalized ads and recommendations, increasing the likelihood of conversion.

3. Predicting customer LTV

The amount of data businesses have today is staggering. From customer data to operational data, there’s a treasure trove of untapped insights just waiting to be uncovered. However, traditional customer analytics techniques often aren’t enough to reveal all the insights hiding in your data.

That’s where artificial intelligence comes in. Customer insights AI can uncover patterns that are difficult or impossible to find using traditional methods. For example, by using AI to predict customer lifetime value, you can identify which customers are most valuable to your business and focus your efforts on retaining them.

To predict LTV with AI, you first need to gather data on customers’ past spending behavior. This data can include anything from how much a customer has spent in the past to what products they’ve bought. Once you have this data, you can use machine learning algorithms to build a model that predicts how much each customer is likely to spend in the future.

This model can then be used to identify which customers are most likely to be high value, and you can focus your efforts on retaining them. For example, you might offer them exclusive discounts or personalized service to keep them coming back.

You may also want to focus on acquiring new customers who have similar characteristics to your current high-value customers. By using this model, you can target your marketing and sales efforts to reach these individuals.

4. Predicting deal size

Deal size is important for businesses of all sizes, but it’s especially critical for small businesses that are trying to grow. AI can be used to predict deal size by analyzing past sales data.

This information can be used to develop targeted marketing campaigns. Knowing which customers are most likely to make a large purchase can help firms focus their efforts on these individuals.

After all, in the most extreme cases, small deals combined with needy customers can result in losing money on a sale. However, by using AI to predict deal size, small businesses can avoid these costly mistakes.

5. Personalized marketing

One of the benefits of using AI is that it allows you to personalize your marketing messages based on the individual needs and preferences of your customers. This can lead to a better customer experience and increased sales.

AI is revolutionizing the way sales and marketing teams do business. By using AI, teams can uncover customer insights that can help them reduce churn, optimize the sales funnel, predict customer LTV, and more.

6. Product feedback classification

In today's digital age, it's easier than ever for customers to share their opinions about products and services. Social media, review sites, and product feedback forums offer disgruntled customers a public platform to voice their complaints, and companies are taking notice. In order to improve customer satisfaction and loyalty, many businesses are turning to artificial intelligence to automatically classify customer feedback based on sentiment.

An AI system that is trained to identify the sentiment of customer feedback can provide valuable insights into what aspects of a product or service are causing dissatisfaction and need improvement. For example, if a high percentage of negative feedback is being posted about a certain feature of a product, the AI system can flag this as an issue that needs attention. Armed with this data, business owners can make changes to the product or service in an effort to improve customer satisfaction.

Customer feedback classified by sentiment can also be used to track trends over time. If customer sentiment around a particular feature starts to decline, this could be an early indication that there is a problem with the product that needs to be addressed.

4 Types of Insights AI Provides

Insight is often thought of as the ability to see things that others cannot. And while this may be true in its most literal sense, in business, insight is about understanding customer behavior and having the ability to use this knowledge to make better decisions.

Artificial intelligence can provide a wide range of insights that can be used to improve business performance. It can help you understand what products are selling well, identify the factors that influence customer behavior, and predict customer trends. AI can also help you personalize your marketing efforts, optimize your sales process, and troubleshoot customer issues.

In order to get the most out of AI-generated insights, it’s important to understand the different types of insights that AI can provide.

1. Product insights

AI can help you understand which of your products and apps are successful and which ones are not selling well. It can also identify the factors that influence customer behavior with respect to your products. This information can help you focus on the products that are most profitable and make changes to those that are not performing as well.

2. Customer behavior insights

AI can help you understand why customers behave the way they do with respect to your products and services. It can identify the factors that influence customer choice, purchase behavior, and brand loyalty. This information can help you personalize your marketing efforts, optimize your sales process, and troubleshoot customer issues.

3. Trends insights

AI can help you understand the current trends among your customers. This information can help you understand how your product can cater to the needs of your customers and stay ahead of the competition.

4. Causal insights

AI can help you identify the causes of customer behavior. This information can help you understand why customers choose to buy or not buy your product, stop using your service, or abandon their cart. This information can be used to improve customer retention and increase sales.

3 Top Benefits of AI 

There’s no doubt that artificial intelligence is changing the way we do business. With its ability to analyze vast amounts of data and make predictions in real time, AI is helping businesses grow sales faster, optimize marketing campaigns, and predict revenue growth and demand rates.

Let’s take a closer look at some of the benefits of AI for businesses.

1. Using more data to grow sales faster

One of the biggest advantages of AI is its ability to use more data from all online touchpoints to make predictions. This includes data from social media, website visits, email interactions, and more. With this data, businesses can develop a more detailed understanding of customer behavior and needs. This leads to more relevant and effective marketing campaigns that generate better results.

In addition, AI can help businesses identify potential leads and convert them into customers more quickly. By analyzing data about customer behavior and preferences, AI can identify potential customers who are most likely to buy a product or service. This allows businesses to focus their efforts on leads that have the best chance of conversion, resulting in increased sales.

2. Predicting revenue growth and demand rates

AI can also help businesses predict revenue growth and demand rates. By analyzing past data about customer behavior and preferences, AI can develop models that predict how much revenue a business can expect to generate in the future. 

In addition, AI can help businesses plan their inventory more effectively by predicting how much demand there will be for a particular product or service. This ensures that businesses have the right amount of inventory on hand, preventing them from overstocking or understocking products.

3. Saving time and energy with predictive analytics

Another advantage of using AI for business is that it can help save time and energy. With predictive analytics, businesses can automate the process of analyzing data and making predictions. This allows businesses to focus their time and energy on tasks that are more important, such as developing new products or services, expanding into new markets, and customer service.

The benefits of using AI for businesses are clear. By taking advantage of AI’s ability to use more data, grow sales faster, predict revenue growth and demand rates, and save time and energy, businesses can improve their performance and compete more effectively in today’s economy.

How Can You Apply AI to Your Business?

In the age of big data, businesses that can effectively harness the power of artificial intelligence have a clear competitive advantage. But for many companies, these initiatives have been out of reach because traditional methods of AI require technical and coding expertise.

Companies like Amazon and Microsoft can afford large data science teams to build custom machine learning models. But for everyone else, this has been a major obstacle. Until now.

Akkio is a no-code AI platform that enables anyone to build predictive models without any coding or technical expertise. Powered by the latest advances in artificial intelligence, Akkio automates the entire modeling process, from data preparation to model selection and deployment.

This means that even companies without dedicated data science teams can now use customer insights AI to make better business decisions throughout the entire customer journey. From surfacing consumer insights with social listening to revealing customer needs and market trends, AI models can generate actionable insights that go far beyond traditional dashboards, analytics tools, and focus groups.

To see how Akkio works, let's take a look at an example.

Suppose you are a retailer looking to increase sales during the holiday season. You could use Akkio to build a classification model that predicts which customers are most likely to buy from you.

A graphic depicting classification, or predicting an outcome from finite categories.

First, you would load your data into Akkio. This data collection step could include pulling in past purchases, demographics, and other relevant information. Bigger, higher-quality data sets generally yield higher quality and more robust models.

Next, you would select the column you want to predict. Akkio will automatically try out a wide range of algorithms, including linear regression, decision trees, and deep learning. It would automatically prepare your data, optimize the selected algorithms, and build a final predictive model.

You can then use this model to make predictions about which customers are most likely to buy from you during the holiday season. You can then use this information to target these customers with marketing campaigns and increase your sales.


No-code AI presents an incredibly powerful way to become a more customer-centric business. Through the power of automation, companies of all sizes can rapidly undergo digital transformation and augment decision-making across a variety of use-cases, from pricing optimization to smarter marketing strategies.

Whether you’re looking to improve customer segmentation, identify new opportunities, or predict churn, customer insights AI can help. Try a free trial of Akkio to get up and running in minutes.

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