Personalization in retail: Trends, technologies, and tips

Personalization in retail has become a new marketing norm. The trend of receiving and providing tailored shopping experiences is here to stay. On the one hand, it’s driven by increasing customer demand and, on the other, by companies' growing interest in personalization tools and retail software development. And while improving personalization will cost companies extra money, there are a few reasons why this investment is worth it.

This article reviews the benefits, trends, technologies, and tips on effective personalization in retail. It also shows how software development companies like N-iX can help you succeed in this journey. 

Retail personalization trends of 2024

The rise of new personalization technologies, restrictions on how to use them, and changes in customers’ preferences formed trends the retailers should consider. These are the few ones to watch in 2024.

• Hyper-personalization. The global hyper-personalization market is expected to nearly quadruple over the next decade—from $18.9B in 2023 to $74.82B in 2033, marking the rise of this trend. Progressive businesses already use advanced AI algorithms that process historical and new data to create highly customized experiences. This hyper-personalization in retail enables more detailed and context-aware recommendations tailored to individual preferences, behavior, and immediate needs.
• Social media personalization. Ecommerce personalization software now seamlessly integrates with social media platforms, utilizing social data to build tailored experiences aligned with individual social interactions, interests, and connections.
• Personalization beyond product recommendations. The businesses offer not only basic product recommendations but also personalized pricing, customized content, targeted promotions, individualized search results, and personalized messaging to deliver a comprehensive and tailored shopping experience.
• Ethical and transparent personalization. Amid rising concerns about data privacy and algorithmic biases, businesses prioritize data usage transparency, offering opt-out options and ensuring fairness and inclusivity in personalization algorithms to establish trust with customers.

These trends indicate that strategies for personalization in retail are evolving to provide companies with increased value and revenue generation opportunities. Let’s see what you can achieve when double down on personalizing customer experiences.

Read more: Retail technology trends in 2024 

Benefits of personalization in retail

When done right, personalization in retail offers numerous benefits that can elevate the customer experience and drive business growth. Here’s what you can expect when upgrading personalization efforts.

Increased revenue and conversions

According to the Cuker Agency Report, personalization in retail can increase sales by 20%. These trends indicate that personalization strategies are evolving to provide companies with increased value and revenue generation opportunities.

Improved customer loyalty

People purchase from and stay with the brands that offer them what they want and need at a specific time. Personalizing your services and products based on the customers’ preferences and buying patterns will make the clients stick with you longer.

Reduced customer churn

According to a McKinsey study, 71% of customers expect businesses to deliver personalized interactions, and 76% get upset when this doesn’t happen. This frustration can be a reason customers abandon their shopping carts and your business. So, tailoring the shopping experience based on shopper interactions helps you offer them relevant experiences and more reasons to stay.

Better experience and higher customer satisfaction

Customers expect a great shopping experience, and you can only deliver it if you know your clients well. And there’s a good reason to know what experience they want.

As the Cuker Agency Report states, 81% of business buyers and 79% of consumers say the company's experience is as important as its products/services. So, by personalizing it, you can win over most potential clients.

Stronger customer relationships and engagement

CM’s research on personalization in retail indicates that 35% of respondents feel that companies fail to meet their personalization expectations and 57% state they still get irrelevant messages from retailers. As a result, these consumers don’t engage in further interactions.    

Personalization across the customer journey can help brands better connect with their clients, create relevant messaging, and build stronger, lasting customer relationships.

Data-driven insights

Personalization generates valuable data on customer behavior, preferences, and interactions with the brand. Businesses can leverage this data to gain insights into market trends, customer segments, and product performance for more informed decision-making and strategic planning.

Competitive edge

According to Statista, the global personalization software market is expected to grow from $0,94B in 2022 to $5.16B in 2030. Adopting retail personalization solutions now will help you remain competitive and keep your customers engaged in your business.

These benefits are too good to pass up, and you can achieve them all by adopting technologies that enable personalization. Here are our top six technologies whose strategic implementation can bring tangible results.

Technologies that enable personalization in retail

From our 21 years of building custom solutions for global leaders and Fortune 500 enterprises (including retail and ecommerce), we know what technologies will help you reach your personalization goals if appropriately implemented. Regardless of your products or services, these technologies should be on your list if you want to improve personalization.

Artificial Intelligence, Machine Learning, and Generative AI

AI, ML, and Generative AI in retail allow businesses to deliver hyper-personalized experiences by leveraging advanced data analytics, predictive modeling, and content generation capabilities.

AI algorithms can help you:

• Analyze customer data (e.g., browsing history, purchase behavior, demographic information) to identify patterns and preferences;
• Suggest relevant products, content, and promotions to each user in real-time.

Machine Learning is a great technology to maximize engagement and conversion by: 

• Analyzing historical data to understand customer behavior, predict future actions, and segment them into distinct groups based on similarities;
• Customizing product recommendations;
• Optimizing pricing strategies; 
• Tailoring marketing messages.

Generative AI is a great tool to automate personalization by:

• Creating personalized content, product descriptions, and visual assets tailored to individual preferences and tastes;
• Generating dynamic and engaging content in real-time.

However, you should make sure the use of such technologies doesn’t violate any respective laws, such as the Artificial Intelligence Act or similar laws that regulate the use of artificial intelligence.

More on the topic: A fresh look at Machine Learning in retail: Top 10 applications 

Big Data and data analytics

Personalization is only possible if you have a lot of information about customers, including preferences, habits, previous interactions with the brand, lifestyle, and so on. The problem is that this data comes through different channels and is rarely ready to be processed right away.

Here’s how Big Data and data analytics solutions can help you personalize the customer experience across various touchpoints:

• Collect and store data from multiple sources, including online and offline transactions, website interactions, social media activity, customer surveys, and more to help you build comprehensive customer profiles that encompass demographic information, purchase history, browsing behavior, and preferences;
• Cleanse, normalize, transform, and manage large volumes of structured and unstructured data to prepare it for further analytics or model training;  
• Uncover meaningful patterns, correlations, and insights from the data;
• Identify hidden trends, segment customers into distinct groups, and predict future behaviors and preferences;
• Deliver relevant and timely offers, content, and experiences tailored to each customer's preferences, interests, and needs.

More on the topic: Big Data in retail: Use cases that bring the most value 

Cloud solutions

Cloud solutions are essential for handling large volumes of customer data, performing real-time analytics, and enabling AI, ML, and other technologies. But that’s not all the use cases of this technology. They help you personalize shopping experience by allowing you to:

• Scale dynamically based on fluctuations in data volume and processing demands with cloud platforms (AWS, Microsoft Azure, Google Cloud Platform);
• Maintain optimal performance and responsiveness while minimizing infrastructure costs;
• Safely store vast amounts of user data, including transaction histories, browsing behavior, and preferences;
• Centralize access to customer data for seamless integration with personalization algorithms and applications;
• Personalize data processing tasks in response to events or triggers; 
• Connect disparate data sources, applications, and systems across your organization to create a unified view of the customer and deliver consistent and personalized experiences across different channels.

Augmented Reality and Virtual Reality (AR/VR)

AR and VR elevate personalization through immersive, interactive experiences tailored to individual preferences. With AR and VR, the companies can enhance personalization in retail by:

• Enhancing product visualization (show how products would look on customers or fit in their spaces) and increasing their confidence in purchasing decisions;
• Creating custom try-on experiences for fashion, cosmetics, and accessories, like virtual fitting rooms and makeup simulators that capture and analyze users’ biometric data and recommend personalized product suggestions that match individual and style preferences;
• Empowering clients to customize products by selecting colors, materials, sizes, and features according to their preferences and specifications;
• Creating personalized virtual shopping assistants to provide personalized product recommendations;
• Developing branded AR filters, interactive VR experiences, and gamified shopping environments for immersive brand experiences.

Computer vision

Computer vision (CV) enables retailers to analyze and interpret visual data to better understand customer preferences and behavior. Here’s what you can achieve by adopting this solution:

• Introduce visual search to identify similar products from the inventory and help your clients find items that match their preferences more accurately;
• Generate personalized product recommendations based on style, preferences, and past purchase history, increasing the likelihood of conversion and driving sales;
• Improve try-on experiences;
• Analyze shoppers’ behavior and interactions with products in real-time to create better merchandising decisions, product placements, and marketing strategies that optimize the in-store experience and increase sales;
• Analyze user-generated content, such as images posted on social media or product reviews, to tailor marketing messages, product offerings, and brand imagery that align with customer expectations, driving engagement and brand loyalty.

More on the topic: Use cases of computer vision in retail 

Internet of Things (IoT)

IoT devices can collect data about users’ buying habits and preferences, allow retailers to send targeted marketing messages, and offer relevant merchandise to shoppers in brick-and-mortar stores and online. Tags can send personalized promotions and offers directly to customers’ smartphones when they are close or in the store, increasing their engagement and widening sales opportunities. When connected to CRMs, martech platforms, and other systems, IoT can help businesses:

• Enable sensor-based cashierless systems to track items placed in a cart and automatically charge the customer's account; 
• Use IoT-enabled mirrors that suggest complementary items, such as accessories, as customers try on clothing;
• Send tailored offers and promotions to customers' smartphones when they are near specific products or departments thanks to beacon technology (devices connecting to mobile phones within the building that allow merchants to send personalized notifications in real time based on visitor's location);
• Manage stock and personalize product recommendations based on inventory availability and offer alternative options;
• Deliver product recommendations and offers tailored to customers' lifestyle and fitness goals based on the data retrieved from their wearable devices;
• Offer personalized content and product information based on customers' demographics, interests, and browsing behavior through in-store interactive displays and digital signage.

The choice of technologies would depend on your specific business goals and tech landscape. However, there are a few working tips that would benefit any business case.

Best 6 industry-agnostic tips to ensure retail personalization

The personalization approach should reflect business goals and consider the enterprise's tech capabilities. We’ve chosen six tips that would help any business with personalization in retail.

Utilize the right data

Invest in robust data collection tools and analytics platforms to gather comprehensive customer data from various touchpoints, including online interactions, in-store transactions, and social media engagement. The more quality data you have, the more detailed insights you’ll have into customer’s preferences, behaviors, and tastes to build your marketing strategies around. 

Offer dynamic pricing and promotions

AI optimizes pricing and promotions by analyzing shoppers’ data, demand patterns, and competitor insights. Its algorithms identify optimal price points, maximize revenue, and adapt to market changes in real time, ensuring competitiveness and profitability. Through dynamic price adjustments and personalized discounts, retailers enhance inclusivity and tailor pricing strategies to individual customers.

N-iX expertise: N-iX specializes in developing competitive pricing intelligence solutions that enable businesses to gather, analyze, and leverage pricing data from competitors to make informed pricing decisions. Leveraging Data Analytics, AI, Business Intelligence, RPA, and other tech domains, alongside a deep knowledge of retail and commerce algorithms, N-iX helps companies optimize their pricing strategies, maximize profitability, and maintain a competitive edge in the market.

Deploy predictive analytics

AI-based predictive analytics helps retailers forecast customer behavior and preferences by analyzing historical and real time data. It also allows businesses to identify buying patterns and customer attrition risks, personalize marketing campaigns, and build proactive retention strategies.

N-iX expertise: We have extensive expertise in building ML-based demand-planning solutions for purchasing prediction, promo modeling and prediction, and automated replenishment. Our demand planning solution helps clients predict demand with 96% accuracy, optimize their conservative stocks by 60% and dynamic ones by 10-20%, and reduce up to 30% of inventory costs. In addition, it allows companies to set up dynamic, personalized promotions based on the customer’s behavior and past purchasing history.

For example, N-iX enhanced a fintech ecommerce client's platform by integrating machine learning models, predicting churn rates, and automating personalized marketing campaigns. Together with tailored marketing interventions, this led to improved retention, efficiency, and revenue growth.

Arrange product pages based on real-time search data

This approach helps retailers adapt quickly to changing customer preferences and behaviors, ensuring popular items are prominently featured for increased conversion rates. Leveraging real-time search data for personalization also helps retailers stay competitive and optimize product offerings and marketing strategies.

N-iX expertise: N-iX has developed a highly accurate and intuitive search engine for a luxury store chain that allows the client’s customers to browse and find the right products on the website easily. Our intuitive UI for the configuration service helped the client increase sales and boosted the client’s revenue significantly.

Embrace omnichannel

Implement an omnichannel retail strategy that integrates online and offline channels seamlessly. Ensure consistency across all touchpoints, including websites, mobile apps, social media, email, and in-store experiences. Use customer data to personalize interactions and provide a cohesive shopping experience across channels.

N-iX expertise: We build omnichannel solutions that enable businesses to capture, store, process, and aggregate customer data and inventory information updates, delivering seamless, contextual, and meaningful user experiences. For example, we helped a Germany-based company migrate its desktop solution to the web and enhance its UX design, which allowed it to expand its market reach and improve retention.

Make personalization ethical

Since personalization means using a lot of data, companies should develop data collection and processing guardrails to help businesses:

1. Making the data processing transparent;
2. Build trust with customers by demonstrating respect for their privacy and data rights;
3. Prevent potential harm from biased algorithms or invasive data collection practices;
4. Align with regulatory requirements and industry standards, reducing legal and reputational risks for businesses.

Always consider the target markets’ data privacy and processing requirements. For example, if your solutions serve European residents, you should abide by GDPR requirements. If you’re personalizing healthcare applications for USA clients, it should align with HIPAA policies. 

These are just a few techniques to help you level up your personalization game. However, to develop a personalization strategy that works for your business specifically, you should partner with an experienced tech company like N-iX. Here’s what makes N-iX a reliable partner to help you integrate the most effective personalization technologies, prepare your infrastructure for continuous digital transformation, and enhance customer experience.

How N-iX helps you build a solid ground for sales-driving personalization 

By leveraging AI, ML, RPA, Big Data, data analytics, cloud solutions, and other advanced technologies, N-iX can help you collect and analyze vast amounts of customer data to enable real-time personalization.

N-iX has a proven track record of helping businesses build a solid foundation for sales-driving personalization. Our 2,200 engineers have helped global retailers, such as Lebara, PrettyLittleThings, and Fortune 500 companies, optimize the underlying infrastructure, ensuring seamless integration and efficient operation of personalization solutions that boost sales. Contact us today to discuss what solutions you can adopt to provide your clients a more ethical and personalized shopping experience!

References:

1. Hyper Personalization Market Size, Trends And Forecast to 2033 | The Brainy Insights
2. 2023-2024 Digital Trends Report  | Cuker Agency
3. Artificial Intelligence Act: MEPs adopt landmark law | News | European Parliament 
4. Research on Personalization: Are Retailers Getting It Right?