Маркет Деливери - Food delivery service

Delivery Club has grown into "Market Delivery": new items have been added to the beloved products. Now, in one place, you will find almost everything that is essential for your everyday needs.

We operate in over 300 cities in Russia: both large and small.

With delivery in as fast as 25 minutes, you can purchase:

• groceries and ready-to-eat meals;

• medication, cosmetics, and pet supplies;

• home appliances, electronics, and gadgets;

• gifts and craft supplies;

• alcoholic beverages and flowers;

• adult products.

FAQs may users are interested in:

How Yandex Eats and Delivery Use Recommendation Technologies

Yandex Eats and Delivery use recommendation algorithms to suggest restaurants, stores, ready meals, and products to users, helping them choose what they need and saving time.

For example, if a user frequently orders pizza through Yandex Eats, the service will recommend pizzerias. If a person prefers ordering the same shampoo from Delivery, the service is likely to recommend that product.

What User Preference Data Is Used and Where It Comes From

To generate recommendations, the services use information about users' actions in Yandex Eats and Delivery, including individual order history and aggregated data from other users' orders.

Additionally, Yandex Eats and Delivery use data obtained from other Yandex services, such as search history from Yandex Maps, Yandex Navigator, Yandex Search, and Yandex Taxi.

When selecting recommendations, key factors include the user's order history, their geographic location, the ratings of available restaurants on Eats or Delivery, and delivery times from these establishments. All these factors help the services understand the user's preferences and suggest the most suitable restaurants, stores, ready meals, and products.

How the Service Analyzes Data and Forms Recommendations

The recommendation algorithms of Yandex Eats and Delivery analyze users' order histories, average checks, restaurant ratings, search history, and other data.

Using statistical and algorithmic methods, the algorithms build factors that are used by ranking models based on machine learning. The algorithms also take situational factors into account.

Recommendations are generated in several stages. First, based on the user's geographic location, the algorithm identifies all available restaurants and stores. Then, it selects ready meals and products from these establishments, considering what the user has ordered before. Finally, the machine learning model ranks the selected stores, restaurants, meals, and products based on a variety of factors.

As a result, a list of restaurants, stores, ready meals, and products that are most relevant to the user is generated.

How Users Can Influence Recommendations

Users influence recommendations through their actions in Yandex Eats and Delivery, such as searching for restaurants or stores or placing orders.

How Yandex Lavka Uses Recommendation Technologies

Yandex Lavka employs recommendation technologies in various sections of its service, such as "You Might Like" and "Maybe You Want Something Else?" on the main page, as well as on product cards, in the shopping cart, and throughout the catalog.

The goal of Lavka's recommendation algorithm is to simplify the search for products and suggest items that are likely to interest the user. For example, if most Lavka customers enjoy pancakes, the algorithm might estimate the likelihood that a specific user will also be interested in them. If the probability is high, the algorithm will recommend pancakes to that user.

What User Preference Data Is Used and Where It Comes From

Lavka's recommendation algorithm uses information about a user's behavior on the service and aggregated data about other users, such as purchase history, clicks, and product views.

To refine recommendations, the algorithm may also consider other factors, such as the time of day or the day of the week. For instance, if a user tends to cook breakfast themselves on weekdays but orders ready-made food on weekends, the algorithm might predict this based on order history and recommend oatmeal or a ham sandwich on Saturday.

Typically, the algorithm uses data from the past three months. However, if a user has not interacted with the service during this period, the algorithm may use data from a longer timeframe.

How the Service Analyzes Data and Forms Recommendations

The algorithm analyzes a user’s order history, clicks, and product views, comparing these with similar data from other users. It then selects products that users with similar behavior on the service tend to order.

The algorithm recommends a ranked list of products that the user is most likely to purchase. To diversify recommendations, the Lavka algorithm filters out products that the user frequently buys themselves.

For example, if soda appears in the recommendations and the user often buys it, the algorithm might suggest trying a different type of soda. Favorite products remain accessible in the "You Bought" section.

The algorithm also considers product similarity. If similar products, such as different types of soda, appear in the top recommendations, the algorithm will select other products that align with the user's preferences (for example, fruit juices).

How Users Can Influence Recommendations

Each shopper influences Lavka’s recommendations through their actions on the service, such as purchases, clicks, and product views.

Recommendations are merely suggestions, and users are not obligated to follow them. They can ignore the recommendations and add any available products to their cart.

If a user does not want their activity information to be used for recommendations, they can delete this information in the "Manage Data" section of Yandex ID.

Saving Your Time

With us, there is no need to visit stores or pick-up points - couriers will deliver your purchases on the same day as ordered. The app allows for convenient comparison of products, prices, and selection of the best deals. We have gathered stores for different occasions so that you can:

• buy groceries from Pyaterochka, Magnit, Perekrestok, VkusVille, or another supermarket;

• stock up for the whole week at Lenta, Auchan, and METRO;

• order personal care products from Ulybka Radugi or Magnet Kosmetika, perfumes, and cosmetics from Riv Gosh;

• choose home appliances, smartphones, and other gadgets at re:Store;

• request delivery of medicines, vitamins, and health products from Doctor Stoletov or another nearby pharmacy;

• purchase pet food, toys, and carriers online from pet stores like Beethoven and Chetyre Lapy.

We Are Here When You Don't Feel Like Cooking

Restaurants offer ready-to-eat food for any occasion:

• breakfast from Shokoladnitsa, pancakes from Teremka for a snack, or something hearty from Kroshka Kartoshka;

• pizza for a picnic from Papa John's or sushi and rolls from Yakitoriya for a romantic dinner;

• a lunchbox from KFC or juicy burgers from Burger King for hanging out with friends.

Choose the right option with the help of filters: by global cuisines, dishes, or delivery time.

Sharing New Promotions and Discounts Every Day

• Discounts on first orders in stores and restaurants

• Regular promotions and gifts on the main screen of the app

• Competitive prices on popular items

• Collections of restaurants and stores with free delivery

• Increased cashback with Plus points for orders

• Discounts on brands you definitely purchase

• Showing on the map where your order is

Track on the map where the courier is with your order.

This way, you will be informed when they arrive to hand over a bag with your favorite food, groceries, cosmetics, or a new smartphone.