The technology of personalised customer experiences, interactive store furniture and electronic labels that trigger a desire to buy. Smart checkouts, service based on customer preferences and condition-based store maintenance! Take a closer look at retail trends in 2024, because the future has already started.
A higher level of customer experience, i.e. personalisation of in store customer experiences
Positive experiences largely determine a store’s sales potential and influence the positioning of the brand image in the minds of customers. This is a well-known fact. However, shaping Customer Experience will reach a higher level thanks to the personalization of individual customer experiences.
What is personalisation of customer experiences in stores?
Personalisation of customer experiences in stores involves adapting the offer, communication and services to the individual needs, preferences and behavior of customers.
The key elements of this strategy are:
- data collection: stores collect data about their customers using various tools, such as loyalty programs, shopping analytics, online behavior (e.g. products viewed), surveys and demographic data,
- data analysis: The collected data is analysed to understand customer preferences, habits and needs. Advanced analytical tools and technologies are used for this purpose, such as Big Data, artificial intelligence (AI) and machine learning (ML),
- customer segmentation: based on data analysis, customers are grouped into segments with similar characteristics and preferences. Thanks to this, stores can better adapt their offer to different target groups,
- personalised offers and recommendations: based on segmentation and data analysis, stores can offer customers personalised product recommendations, discounts and promotions that correspond to their individual preferences. For example, a customer who frequently purchases skin care products may receive offers on new cosmetics,
- personalised communication: stores can adjust the way they communicate with customers, using their preferred channels (e.g. e-mail, SMS, mobile applications) and creating content that is interesting and valuable to them,
- personalised in-store experiences: In physical stores, personalisation may include individual advice, special services (e.g. the ability to reserve products online and pick them up in store), as well as adapting the design and layout of the store to customer preferences. An example would be a system that recognises regular customers and automatically suggests their favorite products,
- omnichannel: integration of various sales channels (online and offline) allows for a smooth and consistent shopping experience. Customers can start shopping online and finish it in a stationary store, or vice versa,
- interactivity and technology: The use of modern technologies such as interactive kiosks, mobile applications, VR (Virtual Reality) and AR (Augmented Reality), which allow customers to have a more engaging and interactive shopping experience,
- feedback and continuous optimisation: stores regularly collect opinions from customers and, based on them, make continuous improvements in their offer and services to better meet their expectations.
How does artificial intelligence (AI) affect shopping in stationary stores? And how does it optimize store maintenance activities?
Artificial intelligence (AI) has an increasing impact not only on e-commerce, but also on shopping in stationary stores, designing store furniture and store maintenance services. And the specifics? Here you go!
AI and shopping in stationary stores
1. Personalisation of shopping
- Product recommendations: AI analyses data about customer preferences and behavior to offer personalized product recommendations.
- Dynamic pricing: AI can adjust product prices in real time based on demand, supply, competition and customer profile and display them on electronic labels on the shelves of physical stores.
2. Customer service
- Chatbots and virtual assistants: in physical stores, AI can be used to support customer service through interactive kiosks or mobile applications that help customers find products, answer questions and offer recommendations.
- Emotion analysis: AI can analyse customers’ facial expressions and body language to better tailor service to their mood and needs.
3. Optimisation of the assortment and store layout
- Customer movement analysis: Using cameras and sensors, AI monitors how customers move around the store, allowing you to optimise the store layout and product placement.
- Smart shelves: shelves equipped with sensors and AI can monitor inventory levels, alerting staff when out-of-stock items need to be replenished.
Smart store fixtures supported by artificial intelligence
Here are two examples that perfectly illustrate the use of AI in furniture stores:
- Interactive furniture: tables and shelves equipped with touch screens and AI can offer interactive product presentations, additional information and recommendations based on the behavior of customers from a specific target group.
- Integrated sensors: furniture with built-in sensors can monitor customer interactions with products and provide real-time data on purchasing preferences.
Retail trends in 2024: AI and Store Maintenance
How to use AI in store maintenance and servicing? Here are some concrete examples.
1. Predictive Maintenance
- Failure prediction: AI analyses data from various devices and systems in the store to predict failures and plan preventive maintenance, which minimises downtime and repair costs.
- Resource optimisation: AI helps manage resources and work schedules for maintenance teams to maintain high levels of operational efficiency.
2. Energy monitoring and management
- Intelligent energy management systems: AI optimises the energy consumption of lighting, air conditioning and heating systems, which lowers operating costs and reduces environmental impact.
- Process automation: AI automates the management of lighting, temperature and other store systems based on sensor data, improving the comfort of customers and employees.
3. Security
- Video monitoring and behavior analysis: AI supports video monitoring systems by analysing customer and staff behavior. And helps prevent theft as well as increases store security.
- Incident management: AI can automatically detect and report incidents such as property damage, equipment downtime and security threats.
The future of the retail has already begun. The trends in the retail industry are not limited to individual changes but undergo a systemic revolution. It’s critical to follow them closely to be able to adjust to evolving customer expectations with the use of the newest technologies. This then will impact your stores performance and brand image to let you continue to grow in more and more demanding retail environment.
