In the first step to analyze users and their tastes and views regarding the Zara brand, we need to ask questions that, based on the results and analysis of their answers, we can divide users into different groups:
Groups such as: people who don't care about the price of the product and will buy it if they like it
Groups based on the same age range/occupation/taste as the rest of the group/gender, etc.
We group these people based on the common characteristics they have,Because these people are the most similar to each other, the decisions we make regarding them will most likely be accepted by the majority of them... For example: introducing and showcasing specific products that we know will be welcomed by this group.

Review of tastes and most popular in the Q group

Zara's most popular categories in Group Q and an analysis of each of them

 The most important feature of the Mazzaneh section in the clothing category is the analysis of user tastes. We do this in the first stage and show each user different images of different types of clothing and ask questions about it to determine their tastes. These analyses are collected from people whose tastes are more than 80% the same as your products.
 First analysis: What are the characteristics of the groups whose taste and choice is this product

Note: All reports and analyses are presented in the form of graphs, but due to the length of the proposal, we only display a portion of them in graphs.

 What are the uses of this  information and analysis in different cases
 From the analysis and data that Mazzaneh provides you, there are an unlimited number of ways to present, advertise, and sell your products, all of which you can control with the dashboard that is available to you... For example, you can choose based on the dashboard filters which bodybuilding enthusiasts like the most which brand of clothing from my brand... and with this data you can find out which clubs or pages Or which bodybuilding-related pages and sites to show your products on, or sponsor competitions, and a whole host of other things... such as filtering based on jobs, hobbies, entertainment, and many more, each of which targets the exact right audience.
 Here, we have reports and data for each product, both in general and individually, and from this data and analysis, we can get many different signals that the app itself acts precisely based on this information and displays each product to each user based on what exactly they like, which will make those users ten times more likely to buy than a user with different tastes and characteristics...In addition to audience information, we also provide suggestions for the type of advertising and campaign, such as the best method, location, and type of advertising for each group of products... For example, with this information, you can accurately calculate where and in what style to advertise each product, to whom.

In this section, we suggest that you read the files related to user monetization and the Mazzaneh board option, which is the most important option for analyzing and presenting advertisements, so that you fully understand how we obtain this information from users with their full consent without violating privacy and using features that were used for the first time in the world.

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