Using AI to Boost User Engagement and Retention Rates

Keeping users engaged and coming back is one of the biggest challenges for any digital product. As competition grows, traditional strategies like push notifications and discounts aren’t always enough. 

This is where AI can make a real difference. By analysing user behaviour, predicting preferences, and delivering personalised experiences, AI can help you boost engagement and improve retention rates. 

In this blog, we’ll share how AI-driven solutions can be applied to your product to keep your users active, satisfied, and loyal.

What is customer retention?

Customer retention is about keeping your users happy and loyal over time. It is making sure that once someone signs up, they don’t just disappear a week later or delete the app after a while.

Where short-term success may be about how many customers have visited your website or downloaded your app, long-term success is defined by how many people stay and continue using your service.

Retention is usually measured by metrics like:

• Repeat purchases: When existing customers return to buy your product or service again.
• Monthly active users (MAU): The number of unique users who engage with your product or platform within a month.
• Customer lifetime value (CLV): The total revenue a business can expect from a customer over the entire time that they remain a customer of that business.
• Churn rate: The percentage of customers who stop using your product or service over a specific time period.

There can be other metrics as well to measure retention, based on your business goals and criteria.

Why customer retention matters

Fact 1: Studies show that acquiring a new customer can cost five times more than retaining an existing one. That is why retention is so important. Because why waste your resources and time to gain new customers when you can make greater profits through existing ones with lower costs?

Loyal customers don’t just stick around. They also:

• Spend more over time
• Are more likely to refer others
• Leave better reviews

Fact 2: Increasing retention by just 5% can boost profits by anywhere from 25% to 95%. This shows that with less effort, you can gain more. Add artificial intelligence into the mix, and you are practically making profits without having to do anything yourself.

AI for customer retention: the game-changer

Many believe that artificial intelligence can only help in making self-driving cars or futuristic robots. But it is changing the business landscape just as fast. In terms of retaining customers, it can help you personalise customer experiences, understand user behaviour, spot problems, and boost customer lifetime value (CLV).

If you are new to AI and want to explore what it is all about and its benefits, you can check out our quick guide: What does artificial intelligence mean?

Challenges of traditional retention methods

Most traditional retention strategies are reactive, meaning that businesses only notice a user is leaving when:

• They stop logging in to the website or app
• Cancel their subscription
• Leave a negative review

By that point, the damage is already done, and it becomes very difficult to retain these customers. And that is the biggest challenge posed by using a traditional retention method, because they rely solely on surface-level data or gut feelings, and can’t detect the subtle early indicators, like:

• Fewer interactions
• Slower response times
• Reduced session duration
• A drop in feature usage
• Negative sentiment in feedback (like complaints or mentioning competitors in their reviews)

How AI transforms customer retention

Artificial Intelligence is rapidly changing the way businesses approach customer retention. Here are some advantages that AI provides: 

1. Proactive risk detection

Unlike traditional strategies, AI can analyse huge volumes of customer data at any given time (for example, interactions, usage patterns, behaviour history, etc.) and predict with surprising accuracy who is likely to leave and why. This is what is called predictive analytics in AI terms. 

By identifying these patterns early on and making strategies beforehand, you can take action before the user even considers leaving.

For example, let’s say a user who normally browses your app every evening suddenly disappears for six days. An AI model might flag this as unusual behaviour and trigger an email or a bundle offer for an in-app purchase to retain them.

2. Personalised customer experiences

The one-size-fits-all strategy has become too outdated now. Here is the secret: sometimes customers know what they want; most of the time, customers don’t know what they want.

That is why, rather than waiting for your users to search for a specific product or service, you can prompt them to click on a potential purchase, based on their past behaviour and preferences. You don’t show them what everyone else sees – you show them what they want to see.     

Here are a few ways AI can help businesses personalise through:

In-app messages

AI can trigger timely messages while users are actively using your app, like a tip for a feature they haven’t tried yet, a reminder about un-bought products in the cart, or a nudge towards a limited-time deal.

Push notifications

Rather than blasting the same alert to everyone, AI can analyse each user’s behaviour, like what time they are most active or which products they have recently browsed, and send tailored notifications that are far more likely to prompt them to purchase.

Product recommendations

AI can track a user’s preferences and behaviour (e.g., browsing history, past purchases, wishlist items) to suggest to them products that they would be most likely to be interested in, just like how Netflix recommends ‘your next watch’, or how Amazon suggests products that you often end up putting in your cart.

3. Automated customer support

AI-powered chatbots and virtual assistants have become a growing trend among businesses, especially those that are customer-centric, like e-commerce websites and other customer support services.

Automating your customer support service can really help you save up big on costs and time. For instance, let’s suppose you get 2000 queries in a day and you have a hundred customer support staff, each dealing with 200 queries per day. But now you can answer these 2000 queries with just one chatbot or virtual assistant – and they will work 24/7! This level of speed and availability improves customer experience, which in turn leads to better retention.

However, having said that, AI cannot answer complex questions or think of new answers itself (except what it has already been trained and tested on). That is where humans can come in and take over.  

Key AI technologies & use cases

So, we know how AI can help us increase customer engagement and retention. But let’s look at some of the AI technologies that make businesses more efficient and productive.

Machine learning (ML)

This is the engine behind most AI tools. Machine learning allows systems to learn from data (for example, user clicks, purchases, page views) and continuously improve over time.

Instead of being explicitly programmed for every single task, ML algorithms get smarter the more data they process. That is how your app learns to recommend better products, detect patterns, or spot customers who are likely to leave, without you having to manually code it every single time.

Predictive and prescriptive analytics

As we mentioned above, predictive analytics helps you predict what is likely to happen next. By analysing past behaviours, like which users stopped logging in after 30 days, what time of year people tend to unsubscribe, or what trends and patterns have been prominent in the industry, this AI tool allows you to stay a step ahead of your competitors.

Read also: What is predictive analytics and how it is used in business?

On the other hand, prescriptive analysis gives you strategies and new insights on how you should tackle a problem or opportunity that is likely to happen, as forecasted by predictive analytics.

Natural language processing (NLP)

NLP works like a behind-the-scenes staff that enables AI to understand and respond to human language. This is what powers smart chatbots, voice assistants, and auto-responses that make you feel like you are chatting with a human rather than a robot. This can greatly help in enhancing customer engagement and experience, especially in the customer support service industry.  

Sentiment analysis

This is a specific type of NLP that is focused on detecting emotions in text. Whether it is a product review, a live chat message, or a tweet, sentiment analysis can tell if the user is happy, frustrated, or disappointed. Businesses use this to flag unhappy customers early and monitor brand reputation.

Use cases of customer retention AI technologies

We have already discussed how AI can help businesses engage their customers better and retain them. Here is a short sum up of all the use cases of these AI technologies:

Real-world brand examples 

So, we know about some basic AI tools and their use cases. Now let’s see a few real-world examples, where AI has revolutionised customer engagement and retention strategies. 

• Netflix: Recommends ‘your next watch’ based on all the shows or movies you have watched.
• Spotify: Curates custom playlists (like Discover Weekly), so you keep coming back.
• Amazon: Suggests products based on your browsing, purchase history, wishlist and added items in the cart.

What’s in it for you?

You might be thinking, “This all sounds great in theory, but we are not Netflix or Amazon.”

True. But remember, there is a reason why companies like Netflix and Amazon have built such a huge customer base now, despite starting off small. It is because they prioritised their efforts on who they were selling rather than what they were selling.

Building an AI customer retention model might sound expensive and a lot of work, but with today’s cloud-based platforms and tools, you don’t need a huge data science team to get started. Even small businesses can now:

• Use AI-powered CRM tools to personalise customer journeys
• Set up automatic reminders and follow-ups
• Catch early signs when a customer might leave, and take action before it’s too late

Enhance your customer experience with AI

Whether you are a startup looking to boost customer engagement or an SME wanting to scale your business, investing in AI for retention can give you the competitive edge.

If you want something custom that fits your specific business needs, our team at GoodCore can help you build it. Explore our AI consulting services and see how we can turn your data into actionable insights.

FAQs

Does my business need a huge amount of data to use AI for retention?

Not necessarily. While more data helps, you can start with basic user activity, feedback, and behavioural trends and scale as your business grows. 

Can AI help with customer retention in B2B businesses?

Absolutely. B2B companies can use AI for account health monitoring, personalised content delivery, and proactive support.

Can AI be used to improve onboarding and first-time user experiences?

Yes! AI can analyse early user actions to personalise onboarding flows—like which tutorials to show, what features to highlight, or when to offer help—making sure users see value right from the start.