How Companies Are Turning AI/ML Research For Building A Product Pipeline
For every company to launch new products in the market, there is something called a product pipeline. A product pipeline is basically a series of products, either in a state of development, preparation, or production developed and sold by a company. The complete process is like a funnel and consists of different phases or stages. For example, there is a company that conducts a brainstorming session to launch new products in the market and they come up with 20 ideas. Now, the ideas go the researchers or scientists and they filter out the ideas which the team thinks may not work in the market well. Therefore, like this, there would be other bodies in an organisation too who would play a vital part and finally, in the end, there are possibilities that out of all the 20 ideas, more than 10 gets rejected and only 5 goes out in the market. This how a product pipeline works. There are many businesses across the world that are facing problems turning ideas into business growth and are looking for new technologies and innovative ideas charged with bringing new products to new markets. Adobe’s AI and ML-Based Approach to Product Pipeline AI and ML have evolved tremendously over the past few years and have marked its territory in several verticals. Be it a recommendation engine of a shopping website or a dating app, ML and AI are everywhere. In today’s tech-driven era, if you don’t have a system or the latest technologies to turn raw technology into experiences that make a difference for businesses and consumers, there are chances that you would be left out. With so much happening already, experts from the industry believe that these sought after technologies can also solve the pain-points in the product pipeline. Talking about leveraging the superpowers of AI and ML in the product pipeline, Adobe is a great example. According to a source, last years, Adobe revealed how it approaches the product pipeline using ML and AI. And from that, few vital things have come onto the surface and have the capability to reduce the challenges in the product pipeline. When we talk about the product pipeline — from product suggestion to product launch — the question that revolves around is “Is this product good enough to bring value to the customers?” So, Adobe came up with some new AI-driven technologies that collaborate across functions. Intelligent Forecasting: It is a conceptual feature that allows customers to address business metric shortfalls from real-time data. Also, it aims to crunch billions of data points to optimize operations for online retailers, companies looking to improve conversion rates, and manage seasonal slowdowns Predictive Pathing: It allows customers to spot things such as app installs and emerging problem areas. It also analyzes the paths a customer takes across screens Automated segmentation: This feature is about managing audiences and customer bases across ages and demographics. Here, AI and machine learning automatically segment audiences Analysis Workspace Assistant: Last but not the least, it is an AI tool that takes a question and spreads across historical queries in order to make sure that work doesn’t get replicated. The assistant is designed to improve over time Outlook It is obviously going to be time-consuming when a process depends on multiple bodies. But with the emergence of  AI and ML in the product pipeline, things might transform. Also, time and again, these two sought after technologies have proved that they are here to stay and make an impact, but not to fade. Therefore, in order to reduce the time frame of the process of product-suggestion-to-product-launch, try to find ways to identify and surface data that is collected but not seen. However, if the data is huge, it would require an ML and AI to surface data that wouldn’t be seen with the naked eye and then humans can optimize. This will not only give a clear view of what the customer wants or what they are interested in but will also help in the very first phase of product pipeline — brainstorming. So, use the latest technologies to understand the customers and the challenges they are facing. This is the ultimate solution for any business.
For every company to launch new products in the market, there is something called a product pipeline. A product pipeline is basically a series of products, either in a state of development, preparation, or production developed and sold by a company. The complete process is like a funnel and consists of different phases or stages. For example, there […]
AI and ML have evolved tremendously over the past few years and have marked its territory in several verticals.
["AI (Artificial Intelligence)", "AI Companies", "Machine Learning", "ML"]
["Replicate", "Go", "machine learning", "AI", "ML", "Machine Learning", "RAG", "Aim", "ViT", "AI Companies", "GAN", "R", "AI (Artificial Intelligence)"]
["AI", "machine learning", "ML", "Aim", "RAG", "R", "Go", "GAN", "ViT", "Replicate"]
Harshajit is a writer / blogger / vlogger. A passionate music lover whose talents range from dance to video making to cooking. Football runs in his blood. Like literally!
He is also a self-proclaimed technician and likes repairing and fixing stuff. When he is not writing or making videos, you can find him reading books/blogs or watching videos that motivate him or teaches him new things.