Start by clarifying that as a software engineer, you'd focus on how technical solutions enable revenue growth, then outline a structured approach: assess current revenue streams, identify levers for growth (e.g., ad load, targeting, new formats), and estimate the split between existing and new advertisers based on data. Emphasize collaboration with product, data, and sales teams to validate assumptions and prioritize engineering efforts.
Pro tip: Acknowledge that revenue growth is a cross-functional effort and that engineering plays a key role in building scalable ad systems, improving targeting algorithms, and optimizing user experience to support higher ad load without hurting engagement.
Break down TikTok's current revenue by advertiser type (existing vs. new) and ad products (e.g., feed ads, branded effects, live shopping). Identify which segments have the highest growth potential.
Propose engineering initiatives that can increase revenue from existing advertisers (e.g., improved targeting, dynamic ad insertion, better measurement) and attract new ones (e.g., self-serve ad platform, simplified onboarding, API integrations).
Use data to estimate how much growth can come from existing advertisers (e.g., increasing ad load, upselling) versus new advertisers (e.g., expanding to SMBs, new geographies). Consider diminishing returns and user experience trade-offs.
Prioritize initiatives based on impact, effort, and alignment with company goals. Create a phased roadmap with clear milestones and metrics for success.
Define KPIs (e.g., revenue per user, advertiser retention, fill rate) and set up A/B tests to validate assumptions. Iterate based on results and feedback from sales and advertisers.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.