1. out of the high rate of
The status quo of
2. combines the above three points, to determine the optimal target
1. problem (data, user feedback) / user survey (questionnaire and interview content, try to combine the data) / competitive analysis
User Survey (below:
4. users on the list and the relevant recommendation, lukewarm
currently selling health products website, but the vertical fields do not much good. >
analysis: from the above we can see that health care users are relatively rational, to buy more clear (by Mito very little possibility to attract target users). At present, the irregular arrangement of goods is not suitable for the target user, and is more suitable for clothing, cosmetics products. The other is the commodity effect is not prominent, is not enough to attract people.
2. the most important product attributes respectively, has no side effects, efficacy, price, brand, reputation for the crowd, and other components.
2. is the first screen click on the following position is very small (more popular search, the first screen in the brand effect, click on the number of
recently optimized home health care NetEase as an example, to talk about how to do page optimization.
optimization is different from the revision. The revision is major changes in the original basis; and optimization is to make some small adjustments, fast lifting effect. But whether or revision optimization, need to consider the following steps:
3. purpose is to purchase health care prevention, enhanced physique
analysis: according to click and transformation can be judged, the main problem lies in the two or three screen commodity recommendation module. As can be seen from the figure, the region has given people the feeling is very dull, it is difficult to arouse the desire to buy. In addition high bounce rate also implies that: in addition to the first screen and brand effect, whether we need to provide some other important content to the user? Let us from the user analysis and competitive analysis to find out the answer.
3. according to the target design plan (
4. test results (data, user feedback index)
1. male user side, good educational background, partial mature, middle income
3. low conversion rate (but the purchase of commodity categories more concentrated)