Are we investing our efforts in building things that actually matter? Is the new feature that we rolled out adding value to the customer? Is the new release doing better than the previous releases? How do we get answers to these questions and more? Analytics is our answer!

Analytics information helps not just the business teams but also QAs, Devs, PMs and other members of the project in multiple different ways. It could help us uncover some critical issues, it could help us understand customer sentiments better, it could help us get a broader picture of how the customer actually uses the product and whether it was how we intended it to be, it can help us get ideas about what small or large changes the customers are looking for without them having to explicitly tell us.

Analytics is important information to us. So, it is also critical that the information is correct. That means analytics information produced also needs to be tested and validated.

This talk is intended to understand the testing of analytics events and why they are important to us.

In this talk, we will cover our experience of how analytics information helped us understand our customers better and invest our time in building the right things. We will also cover how we validated it to ensure that the data that we were seeing was actually correct. In addition to this, we will also briefly cover some details about other sources of information that can be looked at if we are working in a mobile world.

Please note: We’re open to tune the proposal based on feedback

When we witness or experience some situations, we learn a lot more from them.

Games are a great way of learning something new and also for making common but often overlooked things more obvious.

In this session, we propose to play a game which will help us understand the impact of win-lose situations. This game involves multiple teams that have to make quick decisions within the team as well as across teams in order to win as many points as possible. It involves negotiation and competition with other teams but at the same time co-operation too.

We will also have a discussion about learnings from the game.

The idea of the game and more details about it are here:

• https://www.trainingcoursematerial.com/free-games-activities/conflict-resolution-influencing-and-negotiation-activities/win-as-much-as-you-can
• http://intranet.umanitoba.ca/academic_support/catl/media/resource_files/Win_as_much_as_you_can.pdf

Why would you want to build your own mobile device lab for test automation? Isn’t it difficult to maintain and expensive? Yes it is! But we (Anand Bagmar, Priyank Shah and Lavanya Mohan) still had to. And this one time setup activity had a huge ROI.

From our experience in working for an OTT (over the top entertainment) content rich product that has presence in various regions with a large customer base, we have had learnings of how to build quality in-house and making testing repeatable.

We will cover the reason we chose to build the Mobile Automation Devices lab (MAD Lab) in-house, how we chose the devices and OS combinations, our experiments and learnings, etc.

More details about MAD-LAB can be found in blogposts by Anand:
https://essenceoftesting.blogspot.com/search/label/madlab

Many good product and project teams try to understand the “whys” when they’re asked to build a new feature. But, how do we know whether our reasons are actually good enough?

Are we tracking customer behaviour and feedback to get more insights into building the “right product”?

Do we have analytics? Are we monitoring issues/crashes and user suggestions? Are we automating these processes?

In this talk, we will share how we did our analysis in order to get better insights for building the right product and adding more value to our customers. We will share our experience, challenges, etc. We will also talk about a small utility (Sentiment Analyser) we developed which helps us to generate meaningful reports from user's feedback on daily basis.

We will also cover how we’ve automated analytics and understanding the sentiments of our customers.

There will be a demo for Analytics Automation and Sentiment Analyser.

How do we figure experiences and happiness factor of users who use your product? Are the users happy with the current release in production or are they facing issues/problems with the various different functionalities you offer? Are they suggesting/requesting some more features that would solve their use-case? Sentiment Analyzer is an answer to all these questions.

Sentiment Analyser can be used to automatically by anyone to analyse the sentiments (positive, negative and neutral) of users based on the reviews / feedback they write on various platforms. We can categorise sentiments based on the functionalities that our product supports. We can understand in-depth what the users like, dislike and want. We can take actions based on the report to greatly improve impacted areas and our product. And, we can do all this without even having to contact the user directly!