The importance of a product manager is paramount in our times. More than ever the demands and requirements of entire populations are changing rapidly. Thus, a product of our times needs to be upgraded regularly. A commercial entity depending on a product for most of its business can not afford to lose the relevance of the product. Thus a dedicated team is expected to be at work for the development and periodic up-gradation of a product. In order to be a product manager and get placed at the helm of a remarkable product, a team is not easy and requires a lot of hands-on, industry-ready experiences. A good product management certification, followed by training with a reputed organization is often enough to land dream employment in India. The Indian markets are proliferating, and the changes in demands and requirements are just a byproduct. The relevance and requirement of a product manager are fueled by this constant change. And the role is expected to retain its relevance for a fairly long time to come. This article will try to shed light on the general protocol a product manager is expected to follow for the betterment of a product or service.
While developing a product
While developing a product the needs of an entire population are considered. The genre of a product is determined by the calculation of a plethora of aspects, that include geopolitics, climate, health, and finances. An adept product team is expected to analyze the data from all the similar products that have emerged in the past and come up with ideas to mitigate problems they faced. Even before the onset of any commerce, a good data-dependent product team can figure out what an entire population needs. And design a product from scratch keeping the needs of a population in mind. A product developed like this can never fail and is most likely to remain relevant for a long time.
Accumulation of data
The data related to a product’s performance can be gained from user forums and rating websites. Even from the review sections of e-commerce websites, a product team can get an idea regarding the expectations and state of mind of the customers. The end-user data can be ethically obtained with the consent of free and commercial sources. Alongside end-user data, the sales data and all the relevant data from competitor products can be accumulated by any ethical available means. And put to good use for the preservation of relevance of a product.
Structuring the data
The data a product team utilizes for the betterment of a product can be from huge data sets. Data sets can not be handled by humans alone. These humanly unhandled data sets demand special attention and automation for effective utilization. These machine learning or AI-powered tools can only work with specific formats and data structures. A product team thus arranges the data in a format that can be utilized by machine learning and AI-powered analysis tools.
Analysis of product data
The analysis of product data is initiated after the data is gathered and struictured. The goal is usually making sense of seemingly unrelated data for the purpose of generating predictions and prescriptions for the future. The analysis is mostly done by machine learning and artificial intelligence tools. And can be divided into a few distinct phases.
- Descriptive
This phase is concerned with describing and perceiving the data structure and the data itself. And also find out the interrelationships between different units and hidden patterns underlying the contents.
- Predictive
The next phase is concerned with utilizing the detected patterns into predicting the future. More precisely, the probable future. The future is predicted while considering all the relevant internal and external factors related to a product.
- Prescriptive
The prescription stage is concerned with the utilization of these predictions. Based on the deduced probable future prescriptions are made. And the information is communicated to all interested and relevant parties. This communication must be crystal clear and be understood properly by even the ones that are devoid of any knowledge regarding the language and communications in data science.
Implementation of upgrades
After the analysis is complete a company knows what to do and which traits to manipulate for the sustenance of a product’s relevance. The changes are mostly done, based on the internal and external circumstances. The very goal of these upgrades should be pleasing and satisfy a consumer and make the product serve the exact purpose it is expected and designed to serve. Different customers can have different needs and a company is expected to find a perfect balance of service so that most of the potential buyers can be made happy.