Projection vs Actual
Source of Difference
~ Operation Metrics ~
 Conversion rate defined as LTM Active Buyer / Avg. MAU decreased (an improvement for me) significantly by around 10 percentage points.
 Actual LTM average rate per active buyer is higher then projected
 Overestimation of adoption rate based on Wechat MAU
 Underestimation of monetization rate
~ Resulting Financial Results ~
[Revenue] Slightly overestimated by 1.9%, after factor in all top-line related operation metric estimation difference
[Gross Profit] Underestimated Gross Profit Margin by 1.5 percentage points. The absolute amount is luckily inline.
[Sales & Marketing Expense] Slightly overestimated by 1.4% which means the my LTM CAC approach and parameter estimation were both fine in 3Q18.
[General & Administrative Expense] Underestimate a lot due to noise of one-off share-based compensation in 2Q18. Now we have a clearer ratio (and hopefully more stable) to project going forward.
[Research and Development Expense] Underestimated the R&D exp ratio by 2.8%. Basically it’s at management’s discretion so if the company thinks it’s too early to provide guidance, what we can do is guessing based on historical data or other information.
[Operating Loss] Taking into above deviation, operating loss was underestimated by 33%.
[Interest income] Will start model the line item based on beginning all cash position + short-term investment
~ Implications ~
- User engagement gauged by LTM Active Buyer / MAU is improving. The characteristic of metric indicates further decrease in metric for next few quarters before stabilization.
- The characteristic mentioned above might show in the monetization rate as well.
- While unit economics further deteriorated this quarter, the cash burn is very likely to be covered the cashflow PDD extracted from the marketplace (changes in net working capital). This is very favorable for platform to scale up. In addition, the marketplace finance might a major source of profit contribution in the future.