Reading Time: 3 minutesOpenAI, an American artificial intelligence research laboratory, released ChatGPT on 30 November 2022, and there has been an uptick in interest around the world on AI-generated text, AI-generated images, and AI-generated video ever since. This interest has gained traction over time, fueled by the potential for it to change our lives forever – professional and personal alike.
Few advancements in technology have created such an immediate, overnight disruption to the status quo, as have these latest advancements in AI & ML. ChatGPT for instance, amassed over a 100 million clients in under three months (as seen in Figure 1 below), while in contrast, Instagram, the popular image-based social media platform, saw a whole year before it had 10 million users.
Figure 1 :Interest of ChatGPT over time
The phenomenon of GPT
ChatGPT, which is an AI-based interactive bot, has prompted an overall increase in AI adoption according to a Gartner poll of more than 2500 executive business leaders. With Microsoft already committing a $10 billion investment, OpenAI is presently on top of every AI enthusiast’s mind.
Generative AI, on which bots like ChatGPT are built, is technology that offers computerized reasoning to effectively create completely or partially fictional videos, pictures,and text from simple textual prompts.These multimedia elements are generated by sifting through immense measures of information from the web and utilizing profound learning calculations to create these assets.
Despite all the excitement and buzz around ChatGPT and Generative AI, I wanted to understand what value it brings now, even though Generative AI is not new in the market, especially for Retailers. Is this technology a friend or foe to creatives and marketeers in the Retail industry?
GPT in the Retail and CPG industries
For Retail and CPG companies, GPT-enabled futuristic chatbots can assist with customer service, product recommendations, and even online ordering. They can offer 24/7 accessibility and propose customized suggestions to customers based on past buys and browsing history.
For an analyst in the Retail/CPG space though, there may be multiple other use cases, which need critical decisions to be taken. Here are a few:
- What is the monthly growth in average ticket size?
- Share of sales by customer segments in EOSS.
- Why has the revenue decreased in POS, this year vs last year?
- What are the key drivers for change in basket size? What if marketing spends increase by 10%, or there is a discount of 20% across all or some products?
- What will be the volume sold in XYZ category in the next 3 months? – What will be the impact, if EOSS discount is a flat 50%?
- Comparison of ABC category share of sales across manufacturers.
- What is the share of aisle for XYZ subcategory across Retailers?
There are multiple such scenarios in the retail and CPG verticals that would need to be addressed on a continuous basis with analytics. This would involve analysing customer data, panel data, financial data, planogram data, and inventory data to name a few.
However, ChatGPT, in my honest opinion, is currently not designed to analyze such data, as it must undergo a complex process of implementing a custom API layer tailored to extract different insights from data, an orchestration layer to chain API requests to filter, and subsequently sort the data and run security checks to be fully sure of data confidentiality.
ChatGPT can, however, aid the analysts at multiple stages of the process. There are a few products in the market that have been working with Generative AI for some time now to help companies on critical decision making, but none have seen great success, so far.
