What are the areas of UX

parvej64

What will your customer give you his data for? Learn the golden rules for creating lead magnets that generate subscriptions! Second: Quantity of Analysis Does Not Equal Quality Unfortunately, the quantity of data does not always match its quality. It's great to collect a lot of information and analyze it based on it, but everything must have a meaning and purpose. Not all prepared analyzes are equally useful, and some may even interfere with correct conclusions, and this is normal. It all depends on the purpose of their preparation and their ability to analyze and interpret this data. Without advanced analytical capabilities and proper analytical preparation, it can be difficult to draw correct conclusions. Of course, some strategies assume that we have a lot of data, so we can do a lot of analysis based on that data.But a better solution is to prepare your analysis for specific actions. Therefore, we selected data according to the specific purpose of the analysis.

For example: To draw conclusions about the effectiveness of a marketing campaign, we need to analyze sales during the campaign, online advertising and customer analysis (which customers bought which items). However, to predict the number of orders for new goods arriving in the warehouse, we need to analyze the sales dynamics of the same period last year, analyze photo retouching the sales of competitors, and weather analysis to tell us whether it will be warm, whether it will rain, etc. In this case, we do not need Customer and shipment analysis to order the right goods. Therefore, it is worth considering whether it makes sense to waste time and prepare the analysis with exaggeration because we have the time or the idea, or to simply prepare the analysis once we know the goal. Thirdata Cleansing Once we know which data forms the basis for us to consider further business steps and which data is additional and ultimately needs to be treated as secondary data or excluded from the database entirely, strict enforcement measures should be taken. It's like a closet full of clothes:those that don't fit (ie the image we have set for ourselves) need to be removed to make room for those that do (ie those that are useful).



Data Cleansing Once we know which data forms the basis for us to consider further business steps and which data is additional and ultimately needs to be treated as secondary data or excluded from the database entirely, strict enforcement measures should be taken. It's like a closet full of clothes:those that don't fit (ie the image we have set for ourselves) need to be removed to make room for those that do (ie those that are useful).Data Cleansing Once we know which data forms the basis for us to consider further business steps and which data is additional and ultimately needs to be treated as secondary data or excluded from the database entirely, strict enforcement measures should be taken. It's like a closet full of clothes: those that don't fit (ie the image we have set for ourselves) need to be removed to make room for those that do (ie those that are useful).strict enforcement measures should be taken. It's like a closet full of clothes: those that don't fit (ie the image we have set for ourselves) need to be removed to make room for those that do (ie those that are useful).strict enforcement measures should be taken. It's like a closet full of clothes: those that don't fit (ie the image we have set for ourselves) need to be removed to make room for those that do (ie those that are useful).