Integration of the transmission of additional parameters for targeting

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.

Tasks:

1. Increase the number of reviews on Yandex about the project;
2. Increase the rating of reviews. Task implementation:
3. I thought over the mechanics of sending letters to loyal users (more than 3 orders) after placing an order with a request to leave a review on Yandex and receive a gift from partners for it;
4. Discussed and agreed on the mechanics with a partner on the project side;
5. Received the html layout of the letter;
6. I set a task for the layout team - to make up a letter;
7. After the layout of the letter, I set the task to the support team to conduct checking on all possible mailboxes and browsers;
8. After checking the widget, I sent a detailed plan for the implementation of mechanics to colleagues on the project side;
9. Agreed on the implementation of mechanics on the project. Result: For the period from 2020 to November 2022 (when the mechanics were not implemented):

• there were 186 ratings and a rating of 4.6 stars For the period from November 2022 to February 2023 (when the mechanics were implemented):
• 179 ratings were left and the rating of the project on the Yandex resource is now 5 stars

The purpose of the task:

1. Simplifying the user path
2. Increase the conversion rate on the site" "The process of task implementation:
3. Requested a layout from the project designers;
4. I set a task for the layout team - to make widgets according to layouts from designers;
5. After making up the layouts, I set the task to the support team to conduct checking on all possible devices and browsers;
6. After checking the widget, I sent a detailed plan for implementing the mechanics to colleagues on the project side;
7. After receiving confirmation from colleagues on the project side, the mechanics were implemented. " "On average, about 150 users placed an order a day through the "Buy in 1 click" button" Result:
8. Increase order conversion by 24%;
9. Collect about 10 thousand phone numbers for further communication via SMS channel. After conducting A/B testing, the mechanics were launched at 100% of the traffic on the project. "

• 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.

Tackled the learning issue by implementing various personalized learning styles and improved the product checkout process by decreasing the clicks required for payment from 4 to 2 through A/B testing. This streamlined the checkout process, making it more efficient and user-friendly.