How we envisioned AI and NLP to bring Foresight to Product Planning for Food and Beverage Industry?
Our latest blog on how AI can help you overcome the challenges in 2021 planning and demand forecasting proved to be a flashback of sorts for Himanshu (my co-founder at AI Palette) and me.
While discussing the unique challenges of our world that changed so drastically when 2020 happened to all of us, Himanshu and I ended up having our ‘back-to-the-roots’ conversation yet again. 😊
This conversation reaffirmed our firm belief that the foresight about emerging consumer trends and preferences is bound to accelerate and optimize the innovation funnel for FMCG/CPG, food and beverage, and Retail companies.
We believe that this will hold not only during such trying times but also in the long-term.
But isn’t foresight already built into the systems based on the insights derived from traditional, tried, and tested market research, consumer surveys, and business analyst reports?
Well, that brings us to the foresight that is powered by Artificial Intelligence and leveraged by Human Intelligence.
And to discuss this, let’s start from the beginning!
A decade long journey in the Food Industry and the Eureka Moment
This thought process dates to 2011–12 and is relevant to today.
Discussing pain-points with the key stakeholders from the food and flavor industry, I always felt that there was a common thread to their challenges irrespective of their product portfolio and even geographies.
I tried to categorize these common challenges and put them into three different buckets:
1.) Smoke before the fire: Brands desire for early discovery of an emerging consumer trend
2.) Staying ahead of the curve: Brands desire to be Agile in their response to rapidly evolving consumer preferences and emerging trends.
3.) Innovation Funnel Success Ratio: Brands desire to ensure a greater probability of success for new product concepts and launches.
While I had already begun my quest for solutions to the above-mentioned common challenges, I also found myself hearing a lot about the emergence of data in volume, at velocity, and in variety around food, from rather unconventional sources.
I was getting closer to my Eureka Moment!
The abundance of Big Data and the need for a technology stack
All of us in the food industry had started realizing that the universe of the Internet not only has an abundance of data but also continues to make more data available in real-time!
We were staring at this unstructured and raw but highly contextual data, which the consumers were (and are) making available, as they went (and go) about
- searching food, flavor, recipes, ingredients on Google, Bing, Naver, Baidu, and other search engines
- sharing reviews, posts, their feelings (and hence experiences), likes/dislikes, videos, photographs across social media platforms
- ordering food from restaurant aggregators and food-delivery platforms.
- shopping food, beverages, and other grocery products from e-commerce websites
This trail of data, unlike the traditional market research and customer survey data, is devoid of any in-built human biases of the researchers and response biases of the consumers.
But on the other hand, it was not humanely possible to fathom this data in its raw and unstructured form and derive context and insights with the help of legacy analytics tools and systems.
I realized that to overcome this zero-sum situation, food and beverage companies needed a technology stack that could capture, process, filter, derive, and predict based on the historical and real-time data from search, social, retail product, and other such sources.
But which tech stack could offer such capabilities?
Artificial Intelligence to assist Human Intelligence
Eureka Moment finally occurred when Himanshu and I found synergies in our vision for technology solutions for the food industry.
Himanshu’s in-depth expertise in Big Data Analytics and AI gave us the confidence to unearth the potential of NLP and ML technology in overcoming the three common challenges of the food industry that had led us on this quest.
Fast-forward to June 2018 — we successfully launched our Foresight Engine solution. It captures big data from web-search, social media platforms, retail product data, restaurant data, and food recipes.
Foresight Engine is built on a Natural Language Processing (NLP) stack, ensuring that brands are not merely listening but deriving context and insights from this data.
Foresight Engine is language agnostic and hence can understand and unearth context in non-English/local languages. It reads and understands images too!
Watching Foresight Engine, an AI solution, complement and assist the Human Intelligence of Brand Managers in their journey to achieve organization goals serves as a source of motivation and a great honor for Team Ai Palette.
Our Foresight for Foresight Engine solution
Foresight Engine has been launched with the vision to enable brands in the food industry to:
- Take the guesswork out of the prediction of emerging consumer trends and their future trajectory.
- Be Agile in their response to the rapidly evolving and changing consumer needs and preferences.
- Increase RoI with the help of an Innovation Funnel pivoted for success.
Our teams at AI Palette are working tirelessly to walk the talk! We are partnering with the key stakeholders of the food and beverage industry to realize this vision, this foresight.
AI Palette helps the FMCG companies with their product innovation.We use Artificial Intelligence & Machine Learning to help FMCG companies create consumer winning products.This post was first published here.
