Marketing Analytics & Automation at Megamarket

• Developed detailed customer personas segmented by traffic channel to inform campaign strategy.
• Analysed user behaviour by building funnels and identifying anomalies across website events.
• Created monthly reports evaluating the performance of marketing campaigns, influencing strategic decisions.
• Built data marts in Google BigQuery and Greenplum to support reporting and ad-hoc requests.
• Designed reports from scratch in Looker Studio and Visiology, including migrating dashboards between BI platforms.
• Implemented a Telegram bot with Airflow scheduling and error logging to notify analysts about issues in delayed queries.

It was necessary to learn how to target the display of the widget on the site depending on the information about the user filling in the "Information about children" block Since the information about filling in the "Information about children" block is stored on the site side, it was necessary to configure the transmission of this information via dataLayer. The implementation of this mechanics would allow the project to personalize communication with the user depending on the information about the children and offer the most relevant suggestions. Task implementation:

1. Set the task on the back-end side of the project team to implement parameter triggers in datalayer;
2. After the implementation of the parameter triggering, I set the task to the support team to conduct checking;
3. After the correct implementation of the parameter triggering, a widget was implemented with the announcement of filling in the "Information about Children" block. Result:
4. Got information about children from more than a thousand users;
5. Increased the conversion to the rest of the information about children by 174%;
6. Built personalized communication with the user depending on the information about the children.

The business struggled to receive insights from customer reviews to improve product quality because they lacked the necessary details. I released a feature that allowed customers to select tags by category when evaluating a product (For example: Taste -> Sugary, Sour, Oversalted). This provided businesses with systematic customers feedback, which they used to make targeted improvements that resulted in the average goods rating increase by 20%.

Identified the challenge of effectively merging two different platforms to provide a seamless user experience. To address this, I worked closely with the development teams (Yandex.Eats and Yandex.Go) to streamline the integration process and ensure a smooth transition for users. Additionally, I collaborated with the UX team to implement design changes that enhanced the overall user experience. By coordinating with the marketing team, we were able to create a successful launch campaign that effectively promoted the new features to our users. Overall, my strategic approach and cross-functional collaboration allowed us to successfully integrate the services and enhance the user experience.

• managed a team of over 150 people as a cross-domain coordinator.
• built a new client path between applications from scratch
• moved the range of more than 1 million products.
• set up integration between personal accounts of applications for seamless purchase of goods in one and reading in another
• built a new client path between applications from scratch