May 2022 - upGrad Campus

Why Google Can Afford To Be Free.

Posted on May 30, 2022April 3, 2023 by kiruthika

What does your mind jump to when I mention the word Google?

It is an indisputable fact that the word ‘Google’ is synonymous with the word ‘search’ or ‘research’. It has become part of the norm to use these words interchangeably. In fact you would be surprised to know that ‘Google’ is officially classified as a verb!

But enough with this lesson on millennial slang. The bit that interests us all is how, despite providing most of their products at no charge, does Google still manage to not only dominate the tech world, but also mint profits in the long run?

Today we’ll sift through the multiple avenues that Google, or rather Alphabet Inc, used and continues to use, to build its commendable stature as a tech giant. But first tell me, do you really believe Google is free?

Advertising is Google’s primary source of income and about 80% of its total revenue – is brought in by Google Ads and AdSense.

It is impossible that you’ve not come across a Google ad at this point, since Google dominates the Search engine space by a margin of roughly 92%. Google ads are often displayed with the word “Ads” near the result shown on the Search Engine Results Page (SERP). Google earns a commission from the advertiser every time these ads are clicked on by users. The results are either displayed at the top of the page or on the sidebar in YouTube or on the SERP itself.

So what’s AdSense you ask?

Google Ads get displayed on the SERP whereas, in the case of Google AdSense, a webmaster can integrate these ads onto a site. Google’s crawler analyses the content on these sites and chooses sites with specific keywords that match with the webmasters site. The type and locations of the ads are customisable according to the webmaster. Every time the ads get clicked the site earns a part of the commission that Google makes.

The Google Cloud service is actually free for a limited amount of data (15GB), beyond which, users are charged a fee. Google Cloud pulled a whopping $19 Billion in 2021, roughly 7.5% of the total revenue. Their prices ultimately vary, according to the amount of space you take up on cloud.

Hardware is another important avenue for Google to increase their overall revenue, from Google Pixel, smartphones, laptops, tablets, Google Nest smart home products to gaming controllers to fitbits. Google has created an extensive catalogue of products, and with the launch of Pixel 6.0 and Pixel 6 pro, Google’s hardware alone was estimated to bring in 19.6 Billion dollars in 2021.

This one is a no brainer really. Now once again a majority of YouTube content is free to watch for all, but the free version displays Ads, at the start of videos and on the side bar. So using Ads, once more, Google and the channel owner displaying the Ad earn a commission.

YouTube Premium on the other hand, offers an Ad-free experience, eliminating the commission earned through Ads, but replacing it with the subscription fee that users have to pay on a monthly or yearly basis.This is a win-win for all parties involved since it keeps the revenue flowing and improves customer experience simultaneously.

YouTube has more under its belt though. YouTube TV, a fairly new venture, is another source via which Google or Alphabet inc. brings in revenue. YouTube TV, hosts live streaming services, on-demand videos and cloud-based DVR connected with more than 85 networks such as Fox, Big three broadcast networks, etc. It is however available only in the US for now.

Google Play Store is an application distribution service, much like AppStore for Apple, which contains games as well as other service based apps. You can buy a Play pass for $ 4.99 on a monthly basis or $29.99 for a year. This pass provides apps and games without Ads that oftentimes hinder customer experience. So the same as in the case of YouTube premium, they, better customer experience, while yielding an alternative source of profit simultaneously. Additionally, for developers, a fee of $25 dollars is charged, upon the launch of their first app.

So far, Alphabet Inc. has expanded far beyond the realm of search engines, we can only predict this trend going forward too. With the talks of Google gaining foot in the automobile industry and already experimenting widely with AI, the future is definitely going to hold much more value for this Tech giant.

Lumosity – A Lesson in Effective Project Management

Posted on May 16, 2022April 3, 2023 by kiruthika

First rule of product management – understand what your product truly aims to accomplish. This may seem simplistic but as your product becomes more complex, it’s a hard rule to follow. In wanting to boost the popularity of their product, product managers often forget this rule and end up compromising on the very factor that made their product helpful.

It is important to understand that every tried and tested product management method is not going to help your product specifically. Let’s take a look at a company that turned the tide and actually used unconventional means to boost meaningful product engagement.

Lumosity has always been about exercising the grey cells

If you were ever interested in “strengthening your brain”, you must’ve definitely come across Lumosity. Lumosity is an app that contains several games that are meant to test and improve your cognitive skills and abilities. They firmly believe that these games can improve cognitive functions such as Memory, Attention, Processing time/ speed and Problem solving.

Now the concept of using interactive games on a mobile app to improve one’s mind was quite a revolutionary concept at the time Lumosity was launched. However we’re not here to discuss or dissect the app or its concept. We’re here to talk about the sign up process that was not traditional, but actually helped them retain long term consumers.

Simpler the sign-up process, more the users, right? Not always.

Product management has always been about making the user journey easy, and it starts with sign-up. The rule has always been that simpler the sign-up process, the more users they’ll eventually get.

Lumosity, in the start, believed this to be a good rule to follow. After all, their games, while fun, are already complicated. Further, they also need to be played on a daily basis in order for the customer to actually reap their benefits. Therefore, they kept the sign-up sheet simple, so as to not drive away more customers.

But that’s not what they ended up following eventually. Once they started complicating the sign-up process by adding survey questions along with questions about the person’s demographic, they learnt that the people that signed up actually wanted to be there, and would most likely stick to the programme and be regular at their daily tasks.

Embracing complexity yielded results.

This admission process wasn’t conducted in vain. With the information Lumosity obtained, they could make the games more personalised and further boost engagement with their consumers.

Their surveys were extremely extensive, detailed oriented and a whopping 5 pages long!

They collected information about the industry the user worked in, what they wanted to improve upon, or what they expected out of the app.

Now their original concept of getting more people to sign up with a simpler admission process did test to be true. But the second process proved to be more useful, since it gave them a chance to explain their brand’s philosophy and science behind training one’s mind. The survey method also saw an increase in subscription rate – i.e the people willing to pay for their services.

Lumosity continues to experiment with their sign-up process, whether it is the flow of their questions or the amount of difficulty they provide in their sign up-sheet. But the core belief of adding friction and complexity to their brand remains undisputed.

And it’s the reason they are still perceived as a product that makes people brainier by the day.

Data Analytics versus Big Data versus Data Science

Posted on May 2, 2022April 3, 2023 by kiruthika

Information is only useful when it’s understood.

This quote has become an emotion in this new era of business, where technology acted as a game-changer. In this day and age where anything can be considered as data and one man’s trash is another man’s gold, how do you navigate your company to higher prospects?

To make data usable it has to first be sifted through and made relevant.

That task is taken up by a talented Analyst.

What is Data Analytics?

Data analytics is an umbrella term that encompasses many different types of analysis. Data can be subjected to various kinds of analytic techniques and tools to refine it and make it useful information. Think of data as crude oil. It’s valuable only because of what it can be converted into. Data analysis is the refinery that separates information from crude data. And just like refineries don’t run themselves, you need specialised people – called data analysts- who are responsible for gaining key insights from the refined information given to them.

Data Analytics can be useful to any industry, it all depends on what the company is looking to improve. Several sectors that have a high turnover, like medical, hospitality, travel, etc, use customer data such as personal information, reviews, complaints, compliments, guest preferences, review forms, etc, to fix or make improvements to existing protocols. Data Analytics in retails helps keep track of the latest trends, bestselling products, and the average spending power of customers, which helps retailers stay afloat in a vastly competitive field. In healthcare, copious amounts of structured and unstructured data, which include past patient records, are refined to make informed and quick decisions.

The goal of Data Analytics in any sector is to make enlightened decisions based on past records, behaviours, patterns, trends, preferences, and any kind of relevant information from the data pool.

So how is Data Analytics any different from Data Science or Big Data?

All three of these terms share certain similarities. They all use the data available around us to improve decision-making and provide key insights for the company.

But the difference emerges in how they derive these insights and what they use to derive them.

To better comprehend how these 3 are different let’s review Big Data and Data science once.

Big Data Analytics: A revolution in data management.

Big Data, just like the name symbolises, deals with data in colossal quantities. Where traditional data sets are mostly in gigabytes or terabytes at most, big data comes in petabytes, zettabytes, or exabytes.

To put this into perspective, if one byte is equal to one metre, then 1GB of data is 1Million kilometres. That is the value traditional datasets work with. 1 petabyte is 1 billion Gigabytes. That is 1000,000,000,000,000,000 metres or bytes. Traditional storage systems are ill-equipped to handle a data set of this size. Big Data is most often stored on the cloud or needs a specialised storage solution depending on where the data is currently residing.

Big Data is differentiated based on these three components:

Volume, as discussed above, means the size of each data set.

Velocity is the speed at which data is derived. The reason Big Data is as big as it is, is because data is constantly generated.

Variety refers to the various sources from which data is collected. Big Data considers data present in texts, comments, likes, etc.

Due to the large volume and various sources of data, Big Data is mostly unstructured in nature and needs a different set of tools to be analysed.

Data Science – A step further from analytics.

Now that we’ve taken cognisance of Big Data and Data Analytics, let’s delve into Data Science. Data science is a multifaceted field, involving extracting information from:

Scientific methods,
Maths and statistics
Programming
Advanced analytics
Machine Learning
Artificial Intelligence
and Deep Learning

Since the scope of Data Science far exceeds its purpose, i.e, to gain meaningful insights, Data Science deals with analysing complex data, creating new analytics algorithms, tools to further distil the data and even building dynamic visualisations.

Ultimately, there is definitely a degree of truth to the saying data is the new oil.

We have yet to determine the true potential of using data and as we continue our discovery of the subject, the value of data is only going to grow exponentially. This in turn implies that the sectors that discern data are going to become integral to the growth of businesses across continents.