We got an overwhelming response to our last post and a lot of our readers were curious to know how FMCG companies are leveraging their business through AI. Taking a cue, in this post we talk about how FMCG companies are increasingly utilizing AI in their work, the ‘hows’ of it are equally interesting. Easily available big data aids in reduction of computing power costs, and hence AI proves beneficial for the FMCG industry. There are a lot of arenas in which AI comes handy such as personalization of interaction with customers, recommendations and assistance in shopping, managing the supply chain or logistics, churn and demand prediction, price optimization, promotions, and many more.
How the above stated results are achieved depends on the organization using them. Organizations have the option of staffing a data scientist full-time. This is not a cheap option as really good data scientists are hard to come by and also comes with a big price tag (fee). Moreover, a great AI-model is not built overnight but takes time and patience. The other option is to use AI algorithm tools from the retail industry which can also be applied to the FMCG industry. This is easier said than done and this model may be a letdown, as small mistakes by the AI model can lead to big problems. But fret not as there is another option which calls for use of tech that is specific for the FMCG industry.
Personalize customer experience and enhance sales: The role of salespeople of a company requires them to build relationships with customers as well as do quite a bit of the planning and paperwork. Much of the paperwork and analysis-based work is repetitive in nature. On the other level, they also need to build a strong relationship with the customers who like to be heard and this is what helps in meeting the actual sales goals for these salespeople and for the company. AI-powered tools can thus come handy in sales forecasting as well as targeting while the actual sales performance can also be enhanced by automating those jobs that are repetitive. Personalized recommendations on e-commerce portals or newsletters etc can also help increase the sales. To optimize operations, an automated recommendation system can help salespeople in targeting specific customers and that too in the right manner. This combination of sales skills along with automation helps retain customers and drive up sales in an unprecedented manner.
Supply Chain management: Managing the supply chain efficiently is again an area where AI is immensely helpful. The whole process involves taking the product from the supplier and delivering it to the customer using tech, people, information, logistics etc. All such decisions are made on the basis of information shared across all outlets of the organization using real-time data. Errors in sharing such information cause issues such as stock unavailability, delays, wastage, etc resulting in severe losses. AI also considers historical data which includes the buying/behaviour patterns of the customer during months or days of the year along with real-time data such as changing weather. When historical and current data are combined, AI systems predict demand quite accurately. These predictions help FMCG businesses in reducing errors in the supply chain and also help in inventory management. Loss of saltes due to the product being ‘out-of-stock’ can be avoided.
Price optimization: The price-competitive FMCG industry sees similar products which can be availed from different brands at different prices. The prices of these products vary due to the quality of ingredients the products are made of. Not all customers choose a product according to the ingredient quality but many look at and decide on the price the product is offered at. Optimal pricing is arrived at by evaluating the demand, the available stocks, and trends of the market. AI can help arrive at optimal pricing. ML collects pricing of other such products available in the market currently, and their availability, demand etc. All this data is analyzed to arrive at a viable pricing strategy.
How do you ensure repeat customers and what strategies do you apply to expand your consumer base? What are some interesting facts and trends about your customers that you have observed through your work?
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It’s most obvious in the digital media space, from click buys to personalized web experiences. For marketing, the AI journey has just kick-started, while in the tech sector it has been applied for a while now. We are still at an early stage where inroads are being made into AI content via chatbots and even some explanatory content creation but what will make anyone jump up and embrace it is when we will start seeing a lot of mainstream content being created by AI.
Prior to joining Infinite Analytics, Richard served as the CFO of CrowdFlower, COO and CFO of Phoenix Technologies, as a member of the board of directors and chairman of the Audit Committee at Intellisync, and previously as CFO and executive vice president strategy and corporate development at Charles Schwab.
Pravin Gandhi has over 50 years of entrepreneurial operational and investing experience in the IT industry in India. He was a founding partner of the first early stage fund India - INFINITY. Subsequently a founding partner in Seedfund I & II. With over 18 years of investing experience, he is extensively well networked in investment and entrepreneurial scene and is an active early stage angel investor in tech & impact space. Pravin holds a BS in Industrial Engineering from Cornell University, and serves on the board of several private corporations in India. He is on the board of SINE, IIT Mumbai Incubator.
Puru has his Masters in Engineering and Management from MIT. Prior to MIT, he worked with Fidelity Investments building electronic trading products and high volume market data processing applications. He has completed his BE from VJTI, Mumbai.
Deb Roy is Professor of Media Arts and Sciences at MIT where he directs the MIT Center for Constructive Communication, and a Visiting Professor at Harvard Law School. He leads research in applied machine learning and human-machine interaction with applications in designing systems for learning and constructive dialogue, and for mapping and analyzing large scale media ecosystems. Deb is also co-founder and Chair of Cortico, a nonprofit social technology company that develops and operates the Local Voices Network to surface underheard voices and bridge divides.
Roy served as Executive Director of the MIT Media Lab from 2019-2021. He was co-founder and CEO of Bluefin Labs, a media analytics company that analyzed the interactions between television and social media at scale. Bluefin was acquired by Twitter in 2013, Twitter’s largest acquisition of the time. From 2013-2017 Roy served as Twitter’s Chief Media Scientist.
Erik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI (HAI), and Director of the Stanford Digital Economy Lab. He also is the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR), Professor by Courtesy at the Stanford Graduate School of Business and Stanford Department of Economics, and a Research Associate at the National Bureau of Economic Research (NBER).
Akash co-founded IA while studying for his MBA from MIT. Prior to MIT Sloan, he co-founded Zoonga. Before this, Akash was an engineer with Oracle in Silicon Valley. He has completed his M.S from University of Cincinnati and B.E from the College of Engineering, Pune.