Council Post: Retail Business through Generative AI
In the last decade, retailers have started to leverage the power of AI and ML in unique ways to rethink customer experience. Areas such as search, pricing, personalization, and many others have greatly benefited from the various applications of AI and ML. It has empowered businesses with high-level data and information that has helped in improving retail operations and discovering new business opportunities. Moving ahead, it is safe to say that AI will continue to play a significant role in reimagining omni-channel retail. Specifically, I see great potential in Generative AI to be the next wave of AI technology that will unlock newer possibilities in retail. Generative AI Generative artificial intelligence (AI) is a subset of AI that creates novel, original results in accordance with the data it is trained on. Generative AI produces new content in the forms of text, images, videos, audio, and more, in contrast to standard AI systems that are built to identify patterns and make predictions. Technologies like ChatGPT, DALL-E, Stability.ai, Bard, and copy.ai have raptured the entire world with their originality and efficiency. While still at a nascent stage, many retailers have started exploring the applications of generative AI and how it can fit into their larger omnichannel and digital transformation strategies. Let’s take a look at a few use cases in retail to improve customer journey and provide competitive advantage. Personalized information and search According to a Nostro survey, 69% of those who go to online merchants use the search function first. This makes the search function one of the first points of meeting a customer’s expectation in terms of providing personalized recommendations and meaningful material that they are looking for – many times, even unknowingly. The results customers see have the potential to shape and guide their thinking and with generative AI, this experience can be magnified and more accurate. For instance, in home improvement retail, generative AI can be used to provide DIY customers with curated information needed to work on their home improvement projects. It can include products needed for their project, information regarding product, sequencing of the execution steps and much more. Generative AI can stay as co-pilot with customers as they execute their projects. Additionally, generative AI leverages large language models for training; it is therefore trained on large datasets and leverages machine learning and natural language processing to provide customer-specific responses. This brings a paradigm shift in terms of all the information in forms of text, audio and video available to customers. This can also help increase customer base, increase sales and improve customer loyalty. AI adoption in marketing and content A survey by McKinsey in 2022 shows that AI adoption has more than doubled over the past five years and investment in AI is a simultaneous incline. It is clear that image generative AI tools such as Midjourney and DALL-E have the potential to change how a range of jobs are performed. One of the areas where it can make a huge impact in retail is in marketing and campaign content (text/image/video) creation. It is a tool that encourages experimentation and will lead to a significant change in how rapidly we can produce content, from conception to delivery. Content can be produced using diffusion-based methods which have been popular but also, GANs (Generative Adversarial Networks) which has attracted much focus in the last few years owing to its quality of output. It can serve as co-pilots for teams tasked with meeting creative demands. By speeding up initiatives, the time needed to market the demands and by allowing retailers’ human personnel to concentrate on high-end work, this technology can help raise the bar for content development. The unending aisle of the digital shelf requires more than high-quality goods or recognizable brands to rank. With minimal human involvement, generative AI can quickly produce, optimize, and update the product page copies and descriptions. It may be used to enhance product listing ranks, add SEO keywords that aid in ranking on SERP, generate and optimize images for PDP, and curate product descriptions that appeal to customers. Chatbot for customer interactions and resolving queries Generative AI can take the chatbot experience to an entirely new level with the capability to provide human-like responses leveraging NLP and large language models. It can help provide instant customer service to shoppers, resolve issues, provide solutions and reduce workload on the customer service desk. Quick and improved customer service can help build brand loyalty along with customer retention and satisfaction. At this point generative AI seems to be an influential technology and the Global Generative AI market size is expected to reach $53.9 billion by 2028, rising at a market growth of 32.2% CAGR during the forecast period. Retailers live in an ever-changing world of customer needs and expectations, product price sensitivity, shopping patterns and more. Generative AI can be leveraged to help stay ahead of competition and provide curated experiences for customers. It can also help reduce expenditure on mundane tasks and redirect human efforts towards strategic and high value efforts. Today, retail technology is developing at a fast pace – whether it is business transformation or even exploring emerging tech (AR/VR and metaverse etc.) to give customers a more experiential journey. Businesses are innovating not only to remain relevant, but also, ahead. Some are really shaping the future of omni-channel retail by predicting customer expectations and market trends. Generative AI has the potential to play an important role in all of this however, like every technology, generative AI will also come with its own challenges and hence, it will need due governance. For instance, generative AI can result in biased and insensitive content based on the data it gets trained on. It will be crucial for businesses to use it with caution. This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here.
Today, retail technology is developing at a fast pace – whether it is business transformation or even exploring emerging tech (AR/VR and metaverse etc.) to give customers a more experiential journey. Businesses are innovating not only to remain relevant, but also, ahead. Some are really shaping the future of omni-channel retail by predicting customer expectations and market trends.
Today, retail technology is developing at a fast pace – whether it is business transformation or even exploring emerging tech (AR/VR and metaverse etc.) to give customers a more experiential journey. Businesses are innovating not only to remain relevant, but also, ahead.
["AI Chatbot", "ChatGPT"]
["data science", "ChatGPT", "machine learning", "artificial intelligence", "AI", "AI Chatbot", "ML", "NLP", "Aim", "analytics", "generative AI"]
["AI", "artificial intelligence", "machine learning", "ML", "NLP", "data science", "analytics", "generative AI", "ChatGPT", "Aim"]
Amit Kapur is the Vice President of Data Analytics and Insights, Platforms at Lowe’s. As a part of the global technology leadership team, Amit is responsible for strategizing &amp; building data platform tools at scale for Lowe’s on data analytics, data science, &amp; computer vision. He is a seasoned technology industry leader with extensive experience in retail, consulting and IT services. He pursued his Bachelor of Engineering from the National Institute of Technology, Surathkal and MBA from IMT Ghaziabad.