Customers want personalization, and they want it now. More SMBs and startups are competing in an already saturated marketplace. Generic messages, cold responses, and untargeted recommendations cannot help you stand out amongst the competition. Instead, the market shifts towards personalization, or specifically, AI personalization, to attract and retain customers.
If you haven't developed a personalization strategy yet, you're missing out on both market share and revenue growth. According to McKinsey, companies that make personalization part of their product strategy witness 40% increases in revenue. More importantly, more than 80% of customers who have experienced personalization seek brands that offer such experiences.
So, if you want to incorporate personalization in your business, the best time is now. The question is, how do you do that? Well, generative AI has made personalizing customer experience much easier. That said, you’ll still need AI experts to guide you through the efforts.
This guide is authored by Oleh Komenchuk, an AI&ML expert at Uptech, and Aliona Nikolaieva, the Project Manager lead. Since AI became mainstream, we’ve been bringing apps like Angler AI, Dyvo AI, and Plai to the market. These apps prove successful in engaging users. More importantly, they solve real problems the target audience faces.
So we thought our experience would be helpful to you, specifically on discovering the possibilities that AI personalization offers.
Here’s How AI Personalization Transforms The Market
Before generative AI came into the picture, businesses relied on traditional marketing strategies that limit the way they engage with customers. The result — a one-size-fits-all approach brings limited results. With AI-powered personalization, you can change the way customers experience, interact, and respond to your brand. Let's see how.
Offer targeted product suggestions
Instead of showing the same product catalog to different demographics, you can display those that an individual will likely find relevant. Amazon, for example, excels in AI-driven personalization, recommending products to shoppers.
Imagine a shopper bought a frying pan. The next time they shop again, they see aprons, ovens, and other kitchen cooking utensils in their product feed. Basically, the e-commerce giant offers personalized shopping experiences by analyzing information like:
- Purchase history
- Preferences
- Feedback
- Real-time activities
Previously, such capabilities were limited to giant retailers. But generative AI has leveled the playing fields for startups and SMBs. With AI models, we can help you build software algorithms that analyze customer data at scale and use them to recommend products that will likely result in sales. To get a better idea of how AI can help e-commerce companies, check out this article.
Financial benefits, though welcomed, are not the only outcome of personalized recommendations. Customers will feel more engaged, satisfied, and loyal when they’re treated as unique individuals instead of other random visitors.
Besides product recommendations, you can also apply the same technology to deliver dynamic content and promotions in real time. Let’s say a customer has been browsing mostly golfing products. If you target them with golfing tips or discounts, they’re likely to make a purchase.
Provide predictive insights
Generative AI brings along another transformative capability, which is making highly accurate predictions based on large volumes of data. The great thing is, it’s quick. And this gives e-commerce businesses the power to anticipate what their customers want.
Let’s say a SaaS managed to get visitors to sign up for their free product trial. From the act itself, they know that the subscribers have a certain degree of interest in their offer. But AI, or specifically predictive analytics, goes beyond that. Unlike simpler machine learning technologies, GenAI can predict further into the future and also take way more factors into consideration.
For example, generative AI can predict the likelihood of the sign-up converting into a paid subscriber based on:
- demographic
- user behavior
- individual preference
- market trend
- and other data.
When you can predict accurately, you can adjust your strategies promptly. In this case, the SaaS provider can divert subscribers to different funnels to increase their likelihood of purchasing. We covered this topic, along with the step-by-step process of creating an AI SaaS in this guide.
Enable personalized communication
Customers want to be spoken to like the unique individual they are. And if you do that, they’re likely to stay for long, eventually becoming lifelong fans. On the other hand, customers feel disillusioned when they receive generic messages from a brand. In fact, customers expect brands to deliver customized messages, and 76% of them became frustrated by generic messages.
Whether communicating through emails, notifications, web content, or chatbots, AI has taken personalization to a greater level. With AI content personalization, brands can connect with their customers at a deeper level to create memorable experiences.
Imagine a patient was recently discharged after undergoing treatment in the hospital. Rather than following up with a generic thank you message, you can automate it with a conversational AI chatbot. The chatbot can be fine-tuned to converse empathically, provide self-care tips and reminders for follow-ups, and encourage them to ask questions.
That said, integrating chatbots with existing healthcare systems isn’t easy. There are many considerations, legal risks, and data concerns you need to address. Check out this guide to help you build a safe and purposeful AI chatbot.
Simplify information delivery
Less is often more when it comes to creating an engaging customer experience. For the past decades, businesses have ramped up content production to the point that they overwhelm customers. And that led to negative results, where would-be customers simply tune off from future messages.
Let’s take Spotify for example. It doesn’t overwhelm users with tons of generic messages. Instead, it provides summaries of the user’s listening experience, with Spotify Wrapped, which ends up going viral because of the user’s engagement.
Generative AI, on the other hand, allows you to control the type and volume of information costumes should see. Large language models like ChatGPT are exceptionally good at simplifying and summarizing information for customers. More importantly, AI can determine the type, format, and style that different customers relate to in their respective buying journeys.
The problem is, not many SMBs have the capability and expertise to integrate ChatGPT into their apps. Doing so requires access to OpenAI’s API, and modifying existing apps. We wrote the whole guide where we explain how to integrate ChatGPT into an app. You're welcome to check it out!
Allow micro-personalization
Whether you’re in retail, healthcare, real estate, or other industries, consumer trends and behaviors have changed. The days when brands flood the market with products and hope for quick wins are over. Rather, the key to long-lasting brands is addressing micro-moments.
Micro-moments, as Google defines it, are short, critical periods where consumers want something from a brand. Any brand that can address these micro-moments will influence their customer’s decisions. Micro-personalization, or hyper-personalization, in this case, is extremely helpful in addressing these key moments.
Personalized content is one way to capitalize on micro-moments. The idea is to help potential customers answer their questions and guide them along their buyer journey. And with generative AI, the response gap is eliminated, which promises a hyper-personalized customer experience.
AI-Powered Personalization: How It Benefits Your Business
In business, success goes beyond merely creating brand awareness. Rather, it’s about leaving a lasting impression long after a customer first interacts with your product.
GenAI, with data-driven insight, reasoning capabilities, and automation, makes such an effort easier. Let's say your retention rate is low, and you don’t know what’s causing that. With generative AI, you can collect engagement data, analyze them, and use the results to revise your app.
But this is only one of several benefits of the AI-powered apps we work with. Below, we’ll share how your business will improve when you power your product with AI.
Improved customer loyalty
If your brand looks and sounds the same as any other companies offering the same service, you don’t have a brand. Instead, you have a commodity, which doesn’t exactly inspire loyalty. As a result, customers wouldn’t hesitate to switch to a cheaper product when they have the opportunity.
To turn customers into loyal fans, personalization is one of several methods. Coupled with AI, you can analyze and anticipate customers' needs. By incorporating consistent messaging, personalized communication, and responsive engagement, you leave a special impression on customers.
For example, you can deploy the same conversational AI technology across different platforms to continue previous conversations. Eventually, customers know that your brand will be there for them and develop lasting trust.
Higher conversion rates
Even if you have the best product, it might not convert if not paired with a specific and relevant need. Also, sometimes, customers don’t buy because the messages are targeted to a different segment.
Whatever the reason is, a low conversion rate is demoralizing for business owners, and AI can help remediate that. With AI personalization, it’s possible to anticipate what users want and send tailored offers to them. By doing so, you reduce the risks of drop-off, especially when they’re so close to buying.
We’re not making hypothetical claims. Apparently, Unilever, a consumer goods business, found success in personalizing marketing copies and email responses using the GPT model. Their effort leads to an increase in conversion by 15%.
Enhanced customer retention
It’s more cost-effective to retain customers than to acquire new ones. But to do that, you need to analyze existing customer data to figure out pressing issues, encourage repeat sales, and improve their brand experience. With generative AI, such efforts become more seamless.
Applying AI personalization in marketing, for example, can reduce churn rates. For example, you can analyze customers' behaviors using machine learning and NLP. This would let you know their tendency to switch to a competitor or abandon the sale cycle. From the insights, you can segment customers into different groups and channel them through targeted experiences to retain them.
Efficient resource allocation
AI, particularly generative AI, can automate mundane tasks like data entry, sending emails, report generation, and summarization. Traditionally, businesses hire people to take up roles that spend hours performing them.
The time, effort, and resources it takes to personalize marketing strategies can stretch an SMB’s resources to the limit. But when you use AI for personalization and related activities, you can reduce redundancy in business operations.
For example, instead of manually extracting insights from customer data, AI can do so in minutes and with greater accuracy. This way, you can reduce expenses and channel the budget to more valuable hires for strategic activities.
Competitive advantage
Ask any business owners about their struggles, and a common answer is the stiff competition they face. As more products crowd the market, standing out becomes increasingly harder. But with AI and personalization, you have a brighter chance of success.
AI-based personalization implementations, such as
- personalized recommendations
- dynamic content
- conversational chatbots
It all will differentiate your business from your competitors. Just look at how Starbucks, which personalizes customer experience through its apps, builds a strong customer base around the world. Starbucks collects customer data through its apps and sends personalized offers, such as dairy-free beverages, to those customers.
Features for Boosting Brand Engagement Using AI
We’ve explored various ways to improve customer engagement and brand loyalty in the previous section. Now, the big question is, what do you need to get the ball rolling? AI, or specifically, generative AI, is still unfamiliar territory to many companies.
Uptech, being a leading generative AI development company, is in a position to help. We know the exact tech stack or AI features you need to meet specific business goals in your product.
Predictive analytics
One of the greatest advantages of generative AI is its ability to analyze complex patterns in massive data. This, in turn, allows AI to predict possible outcomes with great precision. For brands, predictive analytics can be the difference between profitable or loss-making decisions.
Instead of reacting to market trends and customer preferences, you can apply predictive analytics to anticipate future outcomes. For example, a fintech startup can adjust the lending rate accordingly if it can predict the applicant’s future earning and spending behavior.
How Uptech can help
Uptech is experienced in training deep learning models to identify complex patterns and make reasonably accurate forecasts. We’re aware that prediction accuracy lies in the model and dataset. Therefore, we’re very meticulous in preparing data, selecting the right predictive analytics model, and training it. For example, Angler AI, an AI SaaS we built, uses AI to predict the outcomes of marketing campaigns.
Adaptive learning
If you run a business in the education space, adaptive learning can help you create tailored learning experiences for students and learners. Basically, adaptive learning is a method that lets software analyze engagement data and fine-tune the teaching approach.
Instead of providing the same learning material, the software adapts the content, layout, and deliveries according to the individual’s progress, preference, and level of understanding. Also, learners are more likely to retain the knowledge they picked up when in an adaptable environment.
Live personalization
Before generative became popular, personalization was very limited, and slow. Previously, businesses would collect the data, analyze them separately, and manually personalize the buyer’s journey. By the time they rolled out the personalization, the customer might have lost interest.
With generative AI, personalization is so much faster and more accurate. Let’s say you’re browsing movies on Netflix. The genre, time spent watching, and other data will be processed in real time. From there, Netflix will recommend other TV shows that you might be interested in.
Now, imagine having this gapless personalization in your app. Wouldn’t it make your customers stay, engage, and buy more? Of course, you’ll need to know where to start, the AI model to use, and so on.
How Uptech can help
Uptech has successfully built apps that offer seamless end-to-end customer experience, leading to positive engagement. We integrate AI in areas that will deliver maximum business value and in ways that help users solve their problems. Plai, for example, is an OKR and HR management app we built. We introduced an AI consultant that helps managers create future OKRs based on existing feedback.
Chatbots and virtual assistants
These need little introduction. ChatGPT itself is a chatbot capable of carrying out human-like conversations. When integrated into your app, AI chatbot can engage with customers and help them seek the solutions they need. While many chatbots are text-based, some are capable of using verbal conversations. You can learn more about making an AI voice assistant here.
With chatbots or conversational virtual assistants, you can
- Provide 24/7 support
- Answer questions promptly and precisely
- Be omnipresent on multiple channels
- Identify question gaps that customers might not be aware of
The possibilities are endless. For example, we built a PoC medical chatbot that improves patient care by retrieving relevant information from medical records. Conventionally, medical staff spend a lot of precious time going through extensive patient records just to find the relevant parts. Our medical chatbot significantly reduces the time taken, which allows medical staff to spend more time on patient care.
How Uptech can help
Uptech’s expertise in AI chatbot development helps you build chatbots that improve customer experience. Whether you want to build an LLM-powered chatbot, customer service chatbots, or simpler voice assistants, we’re ready to help. Just like how we built Tired Banker, a GPT-powered solution, we can do the same for you.
Real-time feedback analysis
If you don’t know how your customers feel, you won’t be able to improve their experience. Generative AI has somehow made feedback analysis easier. With deep learning models and natural language processing (NLP), you can conduct sentiment analysis on the feedback your customers leave.
From there, you will know how each customer feels about their experience engaging with your brand. The great thing is, AI can provide such feedback in real time, allowing your business to address any issues that arise.
How Uptech can help
We can help you integrate AI with your app, so you can deliver personalized content and responses without delay. Our broad expertise in NLP, machine learning, and sentiment analysis helps you understand your customers more accurately and quickly. Naturally, users will become more engaged, which results in higher conversion and sales.
Automated response generation
Businesses used to spend precious time and resources responding to customers' emails, feedback, and complaints. Generative AI can remove such manual tasks from the picture and replace them with consistent, accurate, automated processes.
With AI, customers no longer need to wait to be attended to. Large language models can understand customer queries and craft responses they find helpful. Of course, to do that, you’ll need to fine-tune the AI model with your company’s product knowledge.
How Uptech can help
We know how to replace resource-intense, low-value manual tasks with automated ones with AI technologies. With deep expertise spanning several projects, we can help you integrate the right generative AI model that will reduce inefficiencies and accelerate your business workflows. Your marketers no longer have to spend time on repetitive tasks and can be more strategic in their job.
AI Personalization Benefits All Industries – Here's How
Regardless of which industry you’re in, AI personalization can transform how you operate. In fact, market leaders, SMBs, and startups alike have already embraced AI to personalize their customer journeys.
E-commerce
The e-commerce industry is one of the early adopters of AI tech. E-commerce businesses can improve customer retention, reduce cart abandonment, and optimize marketing campaigns with artificial intelligence personalization. One AI personalization e-commerce example is how Amazon keeps shoppers on its page with relevant, targeted recommendations. But that’s not all.
AI personalization e-commerce applications extend beyond that, with features like.
- AI-powered chatbots that help customers answer product queries, track order status, and resolve complaints.
- Dynamic pricing allows retailers to price their products competitively based on real-time market supply and demand.
- Customized search results show products based on the customer’s interests and historical purchases instead of a generic result list.
Healthcare
Healthcare is another major industry that will greatly benefit from integrating AI throughout multiple user touchpoints. They can improve brand experience, patient care, and treatment, subsequently leading to trust and loyalty if they innovate existing systems with AI.
These are AI-driven features that will shape the future of healthcare.
- Personalized treatment plans are created based on the medical profiles of respective patients.
- AI-powered predictive analytics that allows doctors to pre-diagnose potential complications.
- AI medical chatbots are capable of making appointments, providing reminders, answering healthcare questions, and more.
If you want to learn more about how AI affects healthcare industry, we have a comprehensive guide devoted to this topic.
Fintech
Fintech companies operate in tightly regulated space. They need to make decisions fast, and each is bounded by legal and financial risks. Bringing AI personalization into the fold helps them navigate complex decision-making with more clarity. Zest AI, for example, offers AI-powered lending intelligence that helps lenders adjust their policies based on gathered data.
If you’re running a fintech business, these features will be helpful.
- AI credit scoring, which analyzes the financial profile of each applicant to assess their credit risks.
- A personalized financial plan allows fintech to offer tailored financial products that suit a customer's needs, risk appetite, and financial goals.
- Fraud alerting – AI can analyze the transaction patterns of individuals and send personalized alerts if it finds any anomalies.
We also have gathered more benefits of implementing AI in banking industry in our blogpost. Check it out!
Real estate
In real estate, agents grapple with long sales cycles, which means keeping prospects consistently engaged is pivotal. And that’s where AI-powered personalization comes in. Earlier, we made a list of the top software trends in real estate, and implementing AI and ML was one of the key points. From the first touch point, AI can guide house buyers, investors, and agents towards reaching a mutually beneficial decision.
Consider adding these features if you’re building a proptech app.
- Personalized property recommendations that suggest real estate based on the customer’s preference, budget, and needs.
- Virtual assistant capable of guiding buyers through property information and scheduling appointments.
- Mortgage recommendations, which match buyers with mortgage options based on their risk factors, earnings, and other criteria.
Logistics
Logistics companies prioritize timely delivery, resource allocation, and operational efficiency. They’re highly dependent on fleet management systems and delivery personnel to ensure customers receive their goods on time. With AI, businesses operating in the space can reduce operational expenses while coordinating complex delivery routes.
A good example here is DHL. The global logistic giant applies AI to analyze delivery points, predict last-mile delivery challenges, and improve fuel efficiency.
These features allow logistic firms to remain competitive.
- Dynamic route planning helps drivers adapt their routes based on real-time signals, such as weather and traffic conditions.
- Personalized delivery options, allowing customers to schedule pick-up times and updates in real time.
- Predictive maintenance, which prevents disruptions to deliveries and upholds customers’ confidence.
The Ethical Considerations of Using AI-Powered Personalization
Personalized AI is indeed helpful and beneficial to SMBs that adopt them strategically. That said, incorporating AI personalization features isn’t without risks. Generative AI, at the moment of writing, is still evolving rapidly. And it’s not perfect.
So, if you plan to use personalized AI in your products, you’ll need to address these concerns.
Data privacy
To train and operate a generative AI model, you need to feed it with a large amount of data. These data might contain sensitive information, which, if leaked, can compromise user’s privacy. Moreover, companies are compelled by data privacy acts like GDPR, CCPA, and HIPAA to secure data from possible exposure.
Solution: To ensure data privacy, we apply data security measures such as encryption, authentication, and multi-factor authentication when developing AI solutions.
Transparency
Users want to know how their data are collected, stored, and used in the AI software they signed up to. The responsibility lies on the solution provider, in this context, SMEs providing AI-powered services. Furthermore, companies operating in the EU region must comply with the EU AI Act, which seeks to protect user’s rights.
Solution: Be aware of users' sensitivity to how their data is used. Throughout the development, we work closely with clients to inform users of their rights, including creating data privacy policies, disclosures, and disclaimers at appropriate touch points.
Bias and fairness
AI models make decisions based on their underlying algorithm and the dataset they learn from. Thus, they might produce inaccurate results if any of the underlying components are flawed. A biased AI model can lead to SMEs making unfair decisions, negatively affecting customers subscribing to their services.
Solution: To reduce biased results, ensure you collect data that fairly represents your audience and audit the model for risks of bias. Our AI experts have assessed various machine learning models, and we can advise appropriate ways to mitigate such issues in your app.
Conclusion
AI personalization is the catalyst for better brand engagement. Whether you want to offer personalized recommendations or automate communication, AI integration can help. SMBs and startups stand to benefit from the benefits that generative AI offers. But that’s not all.
When you personalize digital solutions with AI, customers, in particular, will enjoy their experience throughout the entire journey with brands. Be it predictive analytics, adaptive learnings, or other AI personalized features, we anticipate a wider adoption across major industries.
That said, you’ll need a balance of technical expertise, legal knowledge, and business acumen to integrate AI seamlessly into your products. Uptech has spent 3+ years building and delivering AI-based solutions. To date, our team has successfully delivered 25+ AI-powered apps.
Our team is no stranger to generative AI. We’ve been following, experimenting, and developing with the technology ever since it became mainstream. Many startups and SMBs have benefited from our experience in boosting their brands. And we’re ready to help with yours.
Talk to our team about personalizing brand engagement with AI and we'll be happy to help you.