The jury is very concerned about this kind of question, because it can directly reflect the value you create for the company and indirectly reflect your email list personal ability. The questions of the judges are generally concentrated in three categories: indicator questions, data questions and review questions.
The indicator problem refers to what indicator or indicator system will be used to scientifically evaluate the results. There are two problems that easily arise in this. One is to confuse the individual results with the team results, and the other is that there is no resource constraint indicator.
Let’s talk about the first one, for example, to improve the conversion rate as an example. Suppose a team is in charge, and you are only one member of the team responsible for one of the strategies (such as subsidies).
Assuming that the overall conversion rate has increased by 5 points, you need to make it clear that the team as a whole increased the conversion rate by 5 points, and you contributed 1 point in it, rather than saying that you increased the conversion rate by 5 points. That is to say, you and the team carry the conversion rate together, and you carry the conversion rate that can be improved through subsidies alone.
If there is a confusion between individual results and team results, it is easy to be challenged and dismantled by the judges at the scene, and there is a high probability that they will not pass. This situation is actually quite common.
The second lack of resource constraint indicators is that it only talks about results but not resource input. For example, to improve the conversion rate, we only talk about how much the conversion rate is improved, but if the improvement of the conversion rate is achieved by relying on some operating activities and subsidies, corresponding operating costs will be incurred, and cost indicators need to be reflected, such as how much subsidy efficiency is in the case. How much has the conversion rate increased.
Data questions are relatively diffuse. They may ask about the data in the promotion materials, or they may ask about some data that are not in the materials but the judges care about. There are two key points.
One is that you can clearly quantify the result data, and you can understand it clearly, and you can clearly answer factual questions. Better performance is that you have an understanding of the industry and competitors’ data in this area.
The other is to fully interpret “what is in the physical world” behind the data, not just at the level of data cognition. For example, if the DAU increases by 50%, 50% is just a number. It is necessary to find out who is behind more than before, whether it is a new customer or an old customer, whether it is a male or a female, whether it is from Beijing or Shanghai, and so on.
Review questions are generally "how to look at this result", "which are good and which are not good" are open-ended questions. If you have done a good review in actual work, you will answer more profound and specific answers. .