Filters are of great importance for online stores, the more closely the demand can be filtered by the consumer, the more likely he is to come across a product that interests him. Adding filters to products is often a time-consuming and tedious process, so store employees may not spend enough time on it or simply may not have it. In many stores the products are added quickly and there are no filters. My customer with a custom online store created by me with over 50,000 items is needed to add more filters so that users could better refine their searches and find products that interested them more easily. For this purpose, I developed with the help of machine learning keyword extraction from product descriptions in Bulgarian. These keywords were later used to automatically create filters. Site administrators have the option to remove filters from appearing if the filter does not seem appropriate to them or is duplicated by another. It took 15 minutes to generate the filters for 50,000 products. It would take the site staff an awful lot of time to do it by hand.
A common problem in large online stores is the need for a product to be present in several categories. With staff turnover, it takes a long time for new employees to study the entire category structure of hundreds of categories. The lack of a product in the right categories reduces the likelihood that it will be noticed by the consumer and purchased. My client's site has over 450 categories and often employees do not add products where they should or do not add them in enough categories. That's why I developed an automatic categorization of products for his online store with the help of machine learning. The system is self-learning, training a model loading the descriptions of all products of all categories and is easy to integrate. When an employee writes the product description, he is automatically offered categories in which to add it. He can remove one or add more. The categories have a written probability of coincidence - the higher the higher the categorization. If you are interested, I can send a link to test the automatic categorization.
Kristiyana Arsova was in my studio in Varna for a photo shoot. We created some very nice photos.
We photographed Raya for model agency Ivet Fashion at our photo studio in Varna
We photographed amazing model Tatiana Sevchenko for model agency Ivet Fashion
We photographed handmade swimwear with lovely model Monika on the rocks in Black sea
We photographed for one of our clients lookbook of clothes for his ecommerce website.
We played in our studio to photograph composite image of coffee with milk. Such images are suitable for interesting presentation of cocktails with many layers for advertisement banners, instagram, facebook and so on. For grabbing user attention in the first seconds.
I took pictures of soap bubles for materials in advertisement backgrounds, banners website headers and so on. They always look good with interesting shapes and reflections.
Photoshoot in our studio for ecommerse catalogue. Luxury Italian clothes for new online store.
I tried to take an interesting photo of this deodorant. Using lights and shadows for more pleasant looking image.
In our photostudio in Varna we created catching eye photos of watch. Suitable for hero website header or advertisement banners. Here are some color variations based on complimentary and harmonic color schemes.
We created pictures of perfume BOOS suitable for advertisement. We tried to create filling for something luxury and mysterious, with interesting lighting and bold colors.
Photographing a product for advertisement can be difficult process when things come to falling into liquid objects. This is the result of our last studio shoots. The picture of the splashing milk is composite of 14 photos it took us 3hr and 165 frames shooting and 4hr retouching work.