The benefits of building an intelligent customer relationship model based on AI
The socio-economic instability and continuous advancements in technology of the past few years have caused an unprecedented wave of changes in the retail industry with customer habits evolving faster than ever before. And these changes aren’t limited to an increased digitalization. Instead, many retailers have also noticed a significant increase in a preference for a hybrid experience where digital channels such as ecommerce, or social networks, merge with physical stores.
Increasingly demanding and one click away from choosing a competitor, the profile of the new digital and post-pandemic consumer accelerates the need for retailers to have valued insights into the modern consumer.
The solution to not only understand these new behavior patterns but also define products and services that are aligned with the new standards, is incorporating AI-based solutions in phygital. These advanced solutions will allow companies to gather valuable data that will help them adapt better to an unpredictable market and overcome major concerns such as fluctuating in supply and demand, the shortcomings of a physical store, and lowering stock inventory.
In fact, according to the “AI Reinvents the Retail Sector” ebook we developed together with our partner Google Cloud, the AI market will reach over 4.4 billion dollars by 2027, and a large part will go towards understanding the customer better.
So, what are some practical examples of applying AI technology to help understand the customer better?
Identify upcoming tendencies and adapt the offering
With an increasingly hyper-connected consumer that can shop globally and has unlimited access to different products all around the world, retailers need to identify and anticipate which trends will be the most desired in the upcoming seasons so they can adapt their collections.
By incorporating tools powered by AI that are able to analyze the evolution of trends and changing consumption habits, retailers can incorporate this information in the planning phase of upcoming collections, making them more adapted to what’s in demand.
Here at NTT DATA we leverage technological tools such as Google Trends for our clients, to identify which concepts and keywords are searched for in the context of fashion. With Google Correlate we generate information and compare the results obtained in relation to prices, products, catalog and existing promotions at any given time. We then integrate tools with automation capabilities to collect information and select images of sites that are popular for each target audience, preparing competitor reports.
These advanced services provide fashion companies with high-value reports that drive data-driven decision-making insights and help them improve their market positioning and differentiate themselves from their competitors.
Define the types of customer profiles that visit stores
While all customers step into a store through the same place, the route they take through the establishment isn’t always the same. The journey inside the store reflects how varied each customer can be depending on tastes and preferences.
AI technologies allow retailers to both detect the people that visit the brand's physical space, how shoppers are grouped throughout their visit, and also how they move around the commercial space. These advanced solutions help retailers understand whether people shop individually or in groups, which are the hotspots where they stop most often, or which products get the most attention but aren’t bought.
By gathering data and using AI to extract valuable customer behavior insights, companies can identify the weak points of their shops and adapt them accordingly. They can identify hotspots by each client profile, tailor the product selection and optimize the display of the items in-store for key profiles just by knowing the physical path they take, which ultimately increases sales.
So, how exactly can it be done?
By using the existing CCTV cameras and gathering images and videos which are then processed. Afterwards, the data is stored and with the help of ad-hoc machine learning models, retailers can accurately create customer profiles using Data Management solutions. These anonymous client profiles that are defined in compliance with GDPR guidelines, help retailers optimize their spaces and their revenues.
Understand which products customers are most interested in when they’re in a store
Physical shops are a significant investment for retailers so to understand what their visitors like and react to in a store is vital when optimizing the space and increasing the return on investment.
Accurately interpreting the feelings and reactions of customers when they interact with displays is now possible with the help of Facial Biometrics Sentiment Analysis. This revolutionary new technology allows retailers to anonymously analyze customers' gestural reactions to specific displays or products.
By using the cameras that are installed in the store, retailers can anonymously analyze biometric facial features when customers interact with the store displays. This will enable managers to know, almost in real-time, the attractiveness of their products in store and the perception of the catalog for each segment.
The data that is recollected is then processed and used to create a dataset that is linked to each section or product. Attributes such as age or gender are analyzed anonymously and linked to the time spent visiting the section, which helps data analysis create a visitor sentiment map by segment in relation to each physical area. The results then help retailers understand the interest in specific products by each customer segment.
The goal is to understand the potential purchase conversion rate they can achieve by cross analyzing the reactions that are recorded with the store sales. This will help companies draw conclusions about the effectiveness of the existing display and price positioning.
In order to adapt to unforeseen changes in the market, brands are leveraging next-generation technology solutions powered by AI to understand the market and consumer better but also to improve the in-store experience, capture behavioral information in the physical journey and gather other information that enriches the customer experience.
Here at NTT DATA and together with our partners at Google Cloud, we help companies incorporate such advanced technologies into their daily operations and by leveraging them, understand the market and design new products and services that are in line with the modern consumer.