In today’s scenario, artificial intelligence is becoming a mandatory part of every domain and industry. Particularly in the Retail domain, we can witness digital transformation advancing the sector for years. Implementing AI-based systems in retail has increased the number of use cases, development speed, efficiency, and accuracy. At the same time, advanced data and predictive analytics models are helping the domain to make smart, data-driven business decisions and future predictions to understand the specific needs of customers.
Thanks to the internet of things(IoT) that helps in generating or gathering more data and increases the opportunity of applying AI in retail industries. Artificial intelligence is a domain that understands the value of every data and can be leveraged to improve operations and new business opportunities. Moreover, a fortune Business Insights report says that the global artificial intelligence in the retail domain is projected to grow up to USD 31.18 Billion by 2018 at a CAGR of 30.5%.
The above statistics represent the competitive environment between the retail businesses, and everyone in the industry will not risk losing their invincible market share to their competitors. So let’s start understanding why AI can make this domain more advanced.
How does AI take Part in the Retail Business?
Undoubtedly, artificial intelligence has found its way into many industries. However, many people don’t understand its meaning. Applying AI to any industry means applying various technologies like machine learning, predictive analytics, and robotics. The main motive of implementation is collecting and processing data and using it to predict, classify and reduce human mistakes so that the industry can work fluently and accurately and humans are able to make data-driven decisions.
When we look back at the recent history of retail businesses, we find that the digital transformation of the industry has started with applying primary IoT devices that are basically data sources. Nowadays, AI is in front of us as advanced technology, and as it finds data in any industry, it finds its use cases. Things have changed a lot in recent scenarios because we can find that giants like Amazon and Reliance are applying behaviour analytics and customer intelligence to extract valuable insights so that touchpoints in the customer service sector can also be improved. Behaviour analytics and customer intelligence are a part of artificial intelligence systems.
What are the advancements?
Nowadays, retail industries are built on top of AI, data-driven decisions and experiences and higher customer expectations. Using AI, we can deliver personalised shopping experiences at scale, which is more relevant and valuable. A simple example of change from traditional retail business is that digital and physical purchasing channels are blended, which helps retailers make their retail channels more advanced and think on the innovation side. As a result, such retailers distinguish themselves from others to become market leaders.
Here are some examples or subdomains of the retail industry where AI plays an important role:
Inventory management
As discussed above, AI is being used to generate a forecast of demand. This use case can be resolved using mined insights of the marketplace, consumer and competitor data. Using the demand forecast, retailers can understand the industry shift and accordingly perform changes in the marketing, merchandise and business strategies.
Adaptive Webpages
Pages of mobile or computer applications can recognise the customers and their shopping patterns even in real-time. That is why we can witness that they are presenting information and product based on our current, previous purchases and shopping behaviour. Also, such systems are designed to evolve constantly so that information can be hyper-relevant to every customer’s marketing and purchasing behaviour.
Dynamic Recommendations
Recommendation systems are also a part of AI that deals with a lot of data analysis and machine learning combining. They can be designed as they can learn and store customer behaviour and preferences through customers’ repetitive interaction or purchasing. All information is saved as a proper profile and utilised for delivering proactive and personalised outbound marketing.
Interactive Chatbots
We can think of this use case of AI as a standard use case for every domain because chatbots are very helpful in improving customer service and engagement. For example, in retail, these bots help retailers to communicate with their customers using the power of AI and machine learning. Trained chatbots can help answer common customer questions and directs them to beneficial outcomes. In turn, these chatbots become more valuable when collecting a customer base that directly leads retailers to make future business decisions.
Visual-based Curation
As we know that there are various algorithms that can translate image, particularly saying image-to-text algorithms helps retailers to represent their new or related products using image-based search or old customer behaviour. Nowadays, these AI-based models can curate recommendations for customers based on aesthetics and similarity.
Guidance in Discovery
In every retail platform, there s always a need to provide confidence to the customer in their purchasing. AI assistance can help narrow down the selection and provide recommendations based on the requirements like preferences and fitting.
Customer insights and personalisation
AI-enabled personalisation systems can recognise the customers and reflect their profile and loyalty to the retailers; based on that, customers can be classified, and some perks like price variations and rewards can be given to them.
Using the stored data AI can tell us what a customer might be interested in using customers’ demographics, social media behaviour, and purchasing patterns. These use cases can work for both online and offline shopping platforms.
Operational Optimisation
Various AI systems help retailer manage their inventory, staffing, product, and delivery systems, even in real-time. Using such systems, retailers create an efficient system or environment that can meet customers’ requirements and expectations immediate and qualitatively high.
Need for AI in the retail industry
In the above points, we have covered some of the major use cases where AI plays an important role in giving solutions in the retail industry.e can understand that digital transformation of the retail industry is a necessity, and also, there are countless benefits of applying AI in this sector. Because this industry is one of the top data-generating industries, there are countless opportunities for AI in the future.
We at DSW | data science wizards have extensive experience in working with retail industry clients. Because of this, we understand the values and business that AI can add to this sector. Here are five primary benefits of AI that retailers can count on.
- Captivate Customers –
A huge number of retail businesses provide immersive shopping experiences to the customers, and here traditional retailers require more customer engagement, and AI is a way to help them in a more personalised and relevant manner.
- Satisfactory Customer Experience
Every retailer can understand the value of customers’ interests. Offering consumers compelling services and experiences is a touchpoint where retailers can differentiate from others. Predictive analytics is a domain of AI that helps retailers to make a difference. A retailer can lead with such innovation rather than just following the traditional way and reacting to the recent changes.
- Finding More Data Insights
There is a huge rush of information in the retail sector. Here retailers need to filter out the important information and transform that into customer-first strategies.
- Blending Offline and Online Retail
Treating offline and online different from each other can be a huge mistake for retailers. Nowadays, these two channels are no more distinct and require a blended way of treatment and operations so that businesses can lead to operational efficiencies from inefficiencies.
- Flexible Logistic Networking
A broad range of customer demands fails the traditional supply chain systems and forces retailers to adapt their supply chain to AI and make a flexible ecosystem that can easily and quickly respond to huge demands and customers’ shifting behaviours.
Making a fully AI-enabled retail system seem overwhelming, but it should not have been. We at DSW aim to make AI available for everyone and create an AI-enabled environment that can be leveraged by any domain. Our flagship platform UnifyAI is made with such capabilities that every industry and sub-industry can utilise it to build a data and use-case-centric system to make data-driven decisions. Click here to check out the similar use cases of AI in different domains or industries.