The year 2021 is still a year battling with COVID-19. Thanks to the vaccination, our life gradually returns to normal, we started to back to the office more frequently and had the chance to travel as before. This year I continue to go deeper on how to apply data science to the retailing domain and do some data analysis with open-source data as well. In this blog, I’ll resume my year of 2021 with the following points:
- Working in retailing (In The Memory)
- COVID-19 analysis
Working in retailing (In The Memory)
In The Memory is a retail-tech company that helps retail players to make the best use of the different internal and external data sources to meet their strategic and operational business challenges. Our products allow distributors and brands to accelerate their decision-making to attract more customers and make the best assortment, merchandising, pricing, and promotional choices, in their various physical and online sales channels. We build tailored Augmented Intelligence solutions to meet clients’ priority challenges and serve their strategies by supporting their teams in change management, defining together the best KPIs to meet clients’ challenges and adapt our solutions to the client’s needs, constraints and processes. Moreover, this year, we have won the “Pépite du Retail 2020” trophy, voted for by LSA Live participants and was elected best Microsoft 2021 partner in the “France Action Startup Award” category; we have nearly 50 colleagues vs. 25 in 2020.
What did I do during working?
This year I accomplished about twenty CRM (Customer Relationship Management) projects, some are for the distributors, some are for the industrialists. With our analysis, we help them to have 10% more turnover per client. I also developed new features for a module that can extract about 50 KPIs for 1 year for different levels, such as per product/store, per product category/store group, or temporal levels x product/store, like month x product or day x store, etc. The SLA (Service-Level Agreement) of this module is about 2-5 min, and during 2 weeks after the release, the module has already been used around 1500 times. Moreover, with my colleague, we created a model for estimating the product’s turnover and recommend products for different promotion operations, which will be applied in a new module. Since it’s confidential, I won’t talk about the details here ;)
Furthermore, as the company expands, we updated our information on Welcome to the Jungle. I participated in a video shooting for presenting what the data team does in daily work and how we cooperate with other teams like consulting team and dev team.
What did I learn during working?
Working in different projects of retailing, I gained more knowledge of different indicactors. Thanks to the CRM projects, I understand what should we focus on according to clients’ needs and how to segment customers with their purchases. During the daily work, I learned how to cut a project and accomplish different parts of the project with colleagues. The biggest gain is that when I did the sales promotion project, I enriched my knowledge of promotion, I understood different promotions operate different mechanics and generosities; to define the products for each promotion, we need to reach various objectives, such as the turnover objective, product number, brand type distribution, generosity distribution, etc. Thanks to this project, I have closer contact with the people of business (category managers, purchase, promotion, etc.), which let me better understand their needs/pain points, so that we can develop the right product to satisfy the needs or solve the pain points.
COVID-19 vaccine analysis
Since the beginning of 2020, people from all over the world have struggled with the COVID-19 virus, and scientists are also actively looking for solutions. To achieve herd immunity, the most effective method at the moment can be said to be vaccination. Various voices about the vaccine have also been on the cusp of social public opinion, and the praise or controversy about it has never stopped. And a vaccine from theoretical design to clinical trials requires too much wisdom and effort of scientists.
With open-source datasets, I analyzed the adverse reactions of Pfizer vaccine, Coronavac vaccine, AstraZeneca vaccine and Modena vaccine in different blogs:
- Do you know the reactions of Pfizer vaccine?
- Do you know the reactions of Coronavac vaccine?
- Do you know the reactions of Oxford/AstraZeneca vaccine?
- Do you know the reactions of Modena vaccine?
- Do you know which COVID-19 vaccine brings the most obvious reactions?
Whether it is a local reaction or a systemic reaction, the reaction is most obvious after the injection of Modena. 86% of people have local reactions, such as pain, swelling, and redness at the injection site, and nearly 67% have a systemic reaction. Such as fatigue, chills, joint pain, muscle pain, etc. Followed by the Kexing vaccine, 62% of people had a local reaction after injection, and 58% had a systemic reaction. Among the four vaccines, the Pfizer-Biotech vaccine caused the least adverse reactions. The probability of local and systemic reactions after vaccination was 29.5% and 22.4%, respectively.
This year I wrote 22 blogs (including this one), they talk about various topics: retailing, COVID-19, population and employee. Moreover, the traffic of my blog increased by 21.4% concerning 2020. I’m pretty glad if my blogs can help you and solve the problems for you.
Besides, I opened a Wechat Official Account, which is likely a personal blog based on Wechat. On this platform, I translated some of my English blogs into Chinese ones and shared them with my Chinese friends. I’ve written 11 blogs and they’ve been read for 8500 times.
Don’t hesitate if you want to ask questions or write comments, it’s welcome!!
Hope to see you in 2022!
- Tumisu, “New year 2021 moon New year’s eve”, pixabay.com. [Online]. Available: https://pixabay.com/photos/new-year-2021-moon-new-year-s-eve-5678207/