Product Based Vs Service Based Companies

-

All the Job Seekers in the tech industry are always curious to know the difference between Product Based and Service-Based Companies.

I have made some pointers which represent the difference in these do segments of industries
  • What are service-based and product-based companies
  • Work and Exposure
  • Technologies
  • Culture
  • On Client Exposure
  • Salaries
  • Annual Increments
  • Growth with respect to position Vs Growth in terms of money
If you are not a good reader have a look at this video on the same topic:

Service-Based Companies

Service-based firms are the organizations that take projects from the external entities and work towards delivering the projects. These companies are generally large companies and are mass recruiters in multiple domains. They prefer people who have a wide array of tech stack in there profiles.
Examples of such companies in India are;
  • TCS
  • NIIT
  • Infosys
  • Genpact

Product Based Companies

Product-based firms are the organizations that have their own line of products and work towards building, improving, and maintaining these products. These companies have a limited number of vacancies and generally prefer people who have in-depth knowledge of the tech stack that they work on and are willing to work on a new stack if the need arises. Some Product-Based companies are:
  • Facebook
  • Google
  • Microsoft
  • Flipkart
  • Amazon

Work and Experience

The type of work that you do ina firm completely depends on the firm you are working at and the post that you hired for. But there are some differences which we will discuss:

In service-based firms, you will be working on multiple projects throughout your time in the organization with every project spanning from 4months to 1 year in the development phase and ongoing maintenance.
Now, the work you will get, depends on, if you have joined the team when the project is in the development phase or in the maintenance phase.
In the maintenance phase, the work usually involves writing some database scripts, some modifications and resolving bugs if found in the project.
The development phase can be pretty exciting for the coder.

On the other hand, in a product-based firm, there is ongoing development going on in the product and teams are working on maintaining the product, adding new features, improving user experience, and creating a new line of products. Most teams will be working on the same tech stack and there will be very little deviation in the stack.

Technologies

As explained previously in many points, in service-based firms you will work on multiple projects and there are good chances that every project is on the different stack as per the requirements.
So, this means that you might get a chance to work on multiple technologies but you might become the master in any stack.

On the other hand, the product-based firm has a defined stack and chances are that you will be learning a stack in-depth and become some in that stack.

Culture

Disclaimer: Culture of an organization widely depends on the company, but I would like to highlight some key points;
  • Timings
    Service-based firms generally have a fixed time that you have to spend in the office which is around 8-9 hours and on the other hand, product-based firms are flexible with the timings, your time in office can vary from 4 hours to 13 hour
  • Dress Code
    Service-based firms generally have a dress code which has to be strictly followed by everyone and on the other hand, product-based firms don't have any dress code, you can go in whichever way you are comfortable.

On Client Exposure

The service-based companies tend to provide you more exposure to the clients as you are more closely working with clients. There can be cases where you are working in client offices.
On the other hand,  in product-based companies, you don't get that much exposure to interact with clients and there are specialized sales and marketing teams that take care of clients.

Salaries

Service-based companies are generally mass recruiters and tend to pay less money as salaries to the employees. The salary for freshers starts from around 3-4 LPA.
On the other hand, product-based companies can pay you hefty amounts along with stock options(Want to know about stock options, do leave a comment). The salary for freshers starts from around 6LPA in small companies and 12-15 in some big companies like Amazon, Google, and Flipkart.

Annual Increments and Growth

Annual Increments in a service-based firm are generally restricted to a single-digit number and some are lucky(1%) to get increments in two-digits.
On the other hand, product-based companies offer you an average hike of 10-15% which might go up to 25-30%.
In terms of growth, a service-based firm can offer you a good growth in terms of positions, you can become a Manager really soon as compared to product-based firm but the product-based firm can help you grow financially with good increments every year and carve you as a tech guy.



This is purely my opinion of the industry as per my experience of 5 Years, which I think describes the general trend.
If you still have any question do let me know in comments.
Also, have a look at other Industry Insights

Comments

Post a Comment

Popular posts from this blog

Word Vectorization

-
Image
Introduction Machine Learning has become the hottest topic in Data Industry with increasing demand for professionals who can work in this domain. There is large amount of textual data present in internet and giant servers around the world. Just for some facts 1,209,600 new data producing social media users each day. 656 million tweets per day! More than 4 million hours of content uploaded to Youtube every day, with users watching 5.97 billion hours of Youtube videos each day. 67,305,600 Instagram posts uploaded each day There are over 2 billion monthly active Facebook users, compared to 1.44 billion at the start of 2015 and 1.65 at the start of 2016. Facebook has 1.32 billion daily active users on average as of June 2017 4.3 BILLION Facebook messages posted daily! 5.75 BILLION Facebook likes every day. 22 billion texts sent every day. 5.2 BILLION daily Google Searches in 2017. Need for Vectorization The amount of textual data is massive, and the problem with textual dat
Read more

Spidering the web with Python

-
Image
Introduction We will be talking about  Spidering/Scraping How to do it elegantly in python Limitations and restriction  In the previous posts, I shared some of the methods of text mining and analytics but one of the major and most important tasks before analytics is getting the data which we want to analyze. Text data is present all over in forms of blogs, articles, news, social feeds, posts etc and most of it is distributed to users in the form of API's, RSS feeds, Bulk downloads and Subscriptions. Some sites do not provide any means of pulling the data programmatically, this is where scrapping comes into the picture. Note: Scraping information from the sites which are not free or is not publically available can have serious consequences. Web Scraping is a technique of getting a web page in the form of HTML and parsing it to get the desired information. HTML is very complex in itself due to loose rules and a large number of attributes. Inform
Read more

Machine Learning -Solution or Problem

-
Image
The article will be divided into different sections as follows: Introduction to Machine Learning Types of Solutions Classification using Naive Bayes A brief about Machine Learning According to the definition by Wikipedia,  Machine learning  is the subfield of  computer science  that, according to  Arthur Samuel  in 1959, gives "computers the ability to learn without being explicitly programmed."  Machine Learning defines a set of problems that have to be evolved through the data by implying some algorithm. One factor that has to be kept in mind while defining a solution through ML is accuracy. Accuracy is very critical in case you are developing a solution in medical domain(cancer detection).There should be a threshold set for every solution which can be based on risk %age that is acceptable. A useful cheatsheet from Microsoft's site to sum up the use of different ML algorithms for the different type of problems. Types of solution Machine Lear
Read more