A Brand new journey into Data Science

Mahima Kaushiva
Nov 5 · 5 min read

The beginning

My journey with brands and people began about eight years ago, in a small village in India. As a young Management Trainee, I was tasked with helping launch a new brand focused on building vocational training opportunities in Tier 2 and 3 cities and my job was to conduct consumer research to determine market-readiness for the product. So there I was, sipping tea with the local village head, eagerly explaining to him that soft skills training (a concept he had never heard of) was going to drastically boost employability among the young men and women in the area. I walked off quite pleased that evening, more or less convinced with my ability to understand how people so different from me, think, behave and live and this became my first lesson in consumer behaviour.

Since that time and now, I have gone on to work as a Marketing Manager, a Brand Planner and eventually a Strategist, advising brands both big and small on how best to understand their audience, be meaningful and stand for something that goes beyond what they sell. Across New Delhi, Mumbai and now London, I have been instrumental in creating, repositioning and rebranding brands across categories as diverse as Retail, FMCG, Travel, Financial Services, FinTech and Sports. While each role had its own set of thrills, for me the most enjoyable bit was learning about why people do what they do, unearth insights about their behaviour and help build a bridge between consumers and the brands they love.

Hitting a wall

Over time I started to realise that in today’s fast-paced and digital heavy world, insights could exist anywhere and I felt I was not adequately equipped to use data for brand building. I was also starting to reach a point in my life where the ‘What next?’ question made me more and more uncomfortable as I did not have an answer to what ‘new’ knowledge would keep me going for the next 20–30 years of my career. Moreover, the brand consulting industry in London is a very closed space for outsiders such as myself so it was becoming increasingly difficult to do be part of great organisations and do meaningful work. All of these reasons made me question status quo and I realised a new skill and direction were what I needed. And this is how I chanced upon data science.

The breakthrough

We all know that data-driven marketing has changed the way we buy, sell and consume stuff and tracking people’s behaviour has never been easier than it is today. Data science has changed the way campaigns are created, products are marketed and advertised and how the efficacy of each is analysed. However, in my experience of the brand strategy industry so far, data science is still a newbie as its true potential has not yet been understood.

In order to be a successful marketer today, deriving insights from data is a must, but to advise brands on how they should position themselves, what their messaging should be, how to align themselves better to consumer expectations and even track if what they are doing resonates well with consumers is not being done or is happening at a very small scale.

My first steps towards breaking through this were to learn how to code so I could understand what to do with data. I tried to learn HTML, CSS and Python on my own but wasn’t very successful at it. I knew I needed to do it in a more structured way and that’s when I started searching for courses / schools that taught Data Science. I also attended meet-ups and wrote to people on LinkedIn to find out more about this profession. It was during this time that I chanced upon the Flatiron School and digging deeper, I realised it offered the best combination of program type + duration that I was looking for.

During the course of this bootcamp, here are some aspects of data science that I am particularly excited to extend my knowledge to. I hope to be able to implement some or all of these on completion of the program.

  1. Build metrics for brand performance : Use data science models to track, evaluate and improve brand performance. Currently this is happening in silos with individual players using their own models but there are no industry-wide methods in place
  2. Move from Market Research to Big Data Market Research : Use data science to combine consumer, behavioural and attitudinal data to build brands in a more holistic manner
  3. Match brand strategies with consumers : Use data science to build models that can point you to the audience resonating most with what your brand purpose is and vice -versa
  4. Sentiment analysis for brand messaging : Get insights into people’s opinions, aspirations and beliefs to build more relevant brand stories
  5. Explore how predictive analytics and optimization can align brands to future consumer needs

My experience of the data-science community has been wonderful so far. While researching this subject, I attended a lot of meet-ups (PyData London, Business Analytics and Data Science etc.) where I spoke to both well-established and new entrants in this field. Everyone was super encouraging, helpful and eager to pass on what they had learnt to others. I was amazed to see how people share their ideas on how to write better code, where to find solutions so as to not reinvent the wheel each time, and all this was drastically different from other industries I had seen where people hold ideas and information close to their chest, the barriers to entry are very high (driven mostly by perception rather than merit) and the avenues to collaborate are few and far between.

If there is one thing I would love for other industries (in particular brand consulting / advertising in London) to learn is this spirit of collaboration, openness and diversity. I am truly excited about my new journey and can’t wait to start implementing my skills as a Data Scientist!

Mahima Kaushiva

Written by

Brand Strategist | Data Science student. Curious about data, brands and human behaviour.

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