Situation

Scentbird is a subscription-based fragrance service that allows customers to discover and try new perfumes and colognes monthly in the United States.

Scentbird utilizes the subscription model, and business growth is directly connected to active user base growth. Nevertheless, it's critical for business margins to optimize customer acquisition costs and focus on selling products with higher margins.

In Scentbird, I was responsible for the whole performance marketing stream, the primary source of the company's growth. Also, I was responsible for growth (from the marketing point of view) prediction models.

Task

For growth forecasting and planning, we needed a framework which would let us:

• predict the active user base growth based on the historical data;
• model the revenue growth for each channel based on current LTV and ROI, keeping in mind constant marketing mix shifting;
• plan the advertisement budget;
• keep an eye on meeting the KPI on ROI;
• help to plan and forecast the fulfillment based on user base growth.

Action

The task above can be divided into the following subtasks:

1. LTV calculation and constant updates for each channel in the marketing mix;
2. implementation of weekly reporting on main metrics per ad channel, including media buying costs, customer acquisition costs, and ROI, which will facilitate the plan vs. fact comparison and adjust the monthly strategy if needed;
3. model media buying budget allocation for the next period for each channel based on the channel's ROI;
4. forecast the future growth based on historical data to understand whether the current growth speed is sufficient according to the business goals;
5. growth trajectory communication to the fulfillment and warehouse streams to plan the supply.

I was responsible for areas 2 and 3. The marketing analytics team almost fully automated areas 1, 3, and 4. Thus, they supplied the data weekly.

To accomplish the tasks above, I performed the following:

• built the customer acquisition cost growth depending on the volume curve for each channel;
• took into consideration all the restrictions for each channel;
• built a model, and calculated (using Excel Solver) the optimal budget allocation for each channel in the marketing mix (taking into consideration the nature and all the restrictions of each channel and other significant factors);
• compared plan to the fact on a weekly basis to adjust the user acquisition operations.

I formulated the following fundamental hypothesis: the model mentioned above would let us find the optimal balance between marketing spending (user base growth) and ROI with an accuracy of at least 7%.

Result

• The active user base grew by 20% within a few months of the March 2020 lockdown, with the KPIs met.
• Actual model accuracy was 5%.
• Also, based on this model, I established a transparent communication process with the warehouse, which let them plan the supply.
• All the 5 parts were integrated into the business planning process.

"Maria is a great professional in the performance marketing field. She began working in my team at Scentbird as a Meta Ad Manager and grew to UA Group Head. She has successfully met her KPIs for three consecutive years with a top marketing budget under management of $2M/month. Maria has a solid mathematical and statistical background and a deep understanding of digital marketing channels and Ad Tech. She has a great ability to manage multiple projects and uses a very systematic approach to the team's benefit."

– Oleg Popov, VP of User Acquisition · Scentbird

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