ChatGPT & Consumer Goods

Since ChatGPT’s launch in November 2022, it has become the subject of mass appeal. People have used it to converse, entertain, teach, cheat, explain and analyse. Much has been written about how it can be used by companies improve their business; this only becomes more relevant with the release of GPT4.0, an impressive upgrade that makes the former product (GPT3.0) look trivial by comparison. While certain aspects of ChatGPT’s use within the corporate world have already been covered extensively, there are a few unique ways in which the tool can be used, specifically within the consumer goods industry. This article will look at how an fmcg brand might use ChatGPT to optimise its supply chain and improve its new product development function.

ChatGPT is merely a language simulator – it isn’t a calculator, researcher, or some form of intelligent being. It uses Natural Language Processing (NLP) and Deep Learning to interpret an input of text and transform it to generate responses that are contextually appropriate. To John Doe then, it might seem like little more than an incredibly advanced version of Siri or Alexa (minus the voice recognition). In reality, ChatGPT is far more sophisticated; it has the ability to understand and analyse vast amounts of data and transform it into very simple, clear reasoning. This allows it to be leveraged to improve the efficiency of a brand’s supply chain function by forecasting demand, thereby optimising inventory management and improving logistics.

In terms of demand forecasting, an fmcg company could feed ChatGPT all the standard information used in demand planning, for example past sales data and trends, news articles, social media engagement figures and survey responses. ChatGPT can interpret, analyse and transform this data to provide accurate and reliable demand forecasts. This in turn can be used to optimise production and distribution schedules and reduce waste (especially where perishable goods are concerned). In addition, GPT4.0’s even more advanced algorithm is able to take into account external factors such as seasonality, promotions, and consumer behaviour, making demand forecasting even more accurate. Outsourcing the NPD team to ChatGPT probably isn’t a good idea. AI can only base outputs on its training – it cannot think for itself. By virtue of this, ChatGPT can only ever come up with answers which it has already encountered somewhere in the past. This means that any new products or ideas put forward by ChatGPT will not be original; a widespread outsourcing of NPD to AI would completely stall global innovation. However, ChatGPT is excellent for discovering what types of products would satisfy consumers, and for providing some degree of creative inspiration.

It does this in a similar way to how it assists with demand forecasting. By analysing customer reviews, social media posts, news articles and other sources of consumer feedback, ChatGPT can identify patterns and trends in customer preferences. This information can then be used to generate new product ideas that are more likely to resonate with consumers. Its role extends as far as the user wishes – ChatGPT can be instructed to simply analyse consumer trends and report back with an written overview of what it believes consumers want, or it can provide a list of new product ideas based on this feedback. It could go as far as developing marketing plans if so instructed.

In the latter stage of the NPD process, ChatGPT has the ability to boost creativity by offering ideas for brand names, taglines and ad campigns based on its analysis of the features and benefits of the product. It can come up with branding and packaging designs by analysing market trends within the design industry to ensure its outputs are on trend and fashionable (note that if a business really wants to capitalise on AI, it can cut and paste ChatGPT’s branding instructions into DALL·E 2 to receive the finished product!). Finally, by using data such as competitor pricing, consumer behaviour trends, and demand forecasting as above, it can assist with pricing strategy. While none of the above should be seen as a way to completely replace current methods of NPD, ChatGPT can serve as a useful starting point, allowing the team to become more efficient.

Using ChatGPT in the ways described is not as simple as going to chat.openai.com and asking it nicely. To access the full plethora of ChatGPT’s abilities in a commercial context, a business must incorporate AI into its own systems. In February 2023, Bain announced an international services alliance with OpenAI. The partnership will allow Bain to offer its clients access to OpenAI’s tools and platforms, including GPT. These can be used to automate tasks, improve efficiency, generate new ideas and improve decision-making. Bain will also provide clients with strategic guidance and digital implementation capabilities to help them integrate AI into their business processes.

Needless to say, this short article doesn’t scratch the surface of ChatGPT’s (and wider AI’s) potential. A friend reading Machine Learning at Imperial laughed when I told him I’d be trying to cover the application of ChatGPT to the corporate world in 1000 words – he’s attempting to do the same in a 30,000 word dissertation. Rather, the aim of this article is merely to act as a taster of how future shareholders might benefit from AI in ways we can’t yet imagine. The war between Microsoft and Google is beginning to disrupt and advance the world of artificial intelligence. The possibilities within this field are endless and truly exciting.