Sumil Mehta

Hi, my name is

Sumil Mehta

I am a professional Digital Analyst


You should meet me first

I am currently working as a Senior Marketing Analytics Specialist at Gartner. I help businesses to implement web analytics solutions for their digital presence and further help them to optimize user journey and business strategy for better performance.

Previously, I was associated with Publicis Sapient where I worked for both B2B and B2C businesses such as Lenovo and Motorola. There, I received the “Best Rookie” award and later finished as the runners up of the Publicis Sapient India Expo.

In general, I like to code and write. My background in computer science and relevant coursework helped me gain proficient skills in Software and Web Development. During my graduation, I got shortlisted for the Google India Scholarship for the Front-End Track, interned for two startups as a full stack web developer, and also worked on projects related to Data Science and Machine Learning. I have also co-authored a couple of research papers and recently presented one at the International Conference on Futuristic Trends in Computational Analysis and Knowledge Management.


What I do the best








Where did I get experience

OCT, 2019 — Present


Sr. Marketing Analytics Specialist

  • Lead the digital analytics activities related to website.
  • Strategize Website and Marketing Analytics implementations related to the website for quality data.
  • Reporting for multiple lines of business for needs such as campaign performance measurement, user behavior on website etc.
  • Visualization and Storytelling via Data Studio, BigQuery and Presentations. 
  • Collaborating with stakeholders to strategize digital marketing on different platforms.
  • Working with Sales team to join digital data with offline sales and lead nurturing data
  • Turn data into insights and recommendations for better user experience, funnel optimization and other quality decisions.

JUN 2018 — OCT 2019

Publicis Sapient

Associate, Marketing Strategy and Analysis

  • Worked closely with the stakeholders of organizations like Lenovo and Motorola for Media Reporting, Analysis and Optimization. Teamed up regularly with media partners and several counterparts from sibling organizations like Digitas, Resultrix and Performics.
  • Monitored and analyzed the performance of various Lines of Business for several digital platforms and helped further in improving the user experience and marketing strategy at Regional and Global Level. Gained experience in both B2B and B2C systems.
  •  Worked on several pro-active pieces including Twitter Sentiment Analysis, Marketing Campaign Creative Analysis and Automating reporting activities, and presented these case studies to In-House as well as onshore teams.
  • Assisted colleagues in projects such as Marriot, Comcast and Dunkin Donuts for reporting, automation as well as analysis

Junior Associate, Marketing Strategy and Analysis

  • Joined as a fresher in Jun’18 and trained rigorously for 5 months.
  • Trained in web analytics implementation and visualization tools such as Google Analytics, Google Tag Manager, Data Studio, Adobe Analytics, Adobe Dynamic Tag Manager and Microsoft Excel. This was followed by Intensive Data Analytics training.
  • Cleared the Google Analytics Individual Qualification Exam and completed the specialization course on Google BigQuery.
  • Shadowed for Ecommerce website TK MAXX for analytics implementation and troubleshooting based on Google Tool stack.

Researches published in Journals

Genetic model for supply chain inventory optimisation

Inventory management is known to be an important aspect in supply chain models. The methodologies used in inventory optimisation intend to reduce the cost of supply chain by controlling the inventory in a desired manner, so that the members of supply chain will not be affected by abundance or shortage of stock. In this paper, an efficient approach based on genetic algorithm (GA) is proposed in order to reduce the total cost of supply chain. A numerical example is used to explain the new approach. The results show that the proposed approach gains an insight into the supply chain models and is applicable for reducing overall supply chain cost.

Effects of imperfect quality items in the asymmetric information structure in supply chain model

Most of the supply chain models have been developed under symmetric information structure i.e. players have complete knowledge of each other’s policies. But in most of the cases, players do not have complete information about the other players i.e. some information regarding their businesses is hidden. This paper studies supply chain model of imperfect quality items under asymmetric information in which unit price taken by the buyer and unit marketing expenditure are influencing product’s demand. This information is hidden to seller. The seller delivers the supply to the buyer.​


Where did I get my skills

August, 2014 — JUN, 2018

GGS, Indraprastha University

New Delhi, India

Bachelor of Technology in Computer Science and Engineering

My Bachelors in Computer Science helped me set up my base for Software Development, Website and Web Application Development and Machine Learning. This helped me land two Internships during my graduation.  In the last two years of my grad, I researched on Optimization and Supply Chains, later the research works were published in a couple of journals.

Apart from college, I actively contributed to Institute of Electrical and Electronics Engineers or IEEE community. The major contributions there were – writing/editing the newsletter and organizing technical sessions and events.