Shulou(Shulou.com)06/03 Report--

2018 is the year when the new retail industry broke out. I'm sure everyone feels the same way. There are more convenience stores than before. They can be seen almost everywhere. They still think they haven't been to the supermarket for a month or two. Sometimes they see new retail models on the street.

For retail enterprises, their core competitiveness is to "increase sales and control costs", that is, to open source and cut expenditure. The development of new retail enterprises benefits from the application of more and more new technologies, as well as the continuous application of new technologies in the field of open source and cost-saving. Here are some of the main application directions of big data and artificial intelligence in the new retail industry.

I. Operation

1. Member management

Membership management is an important work of new retail enterprises. the premise of doing a good job of membership management is to effectively understand members, and membership management is based on member labels.

Membership tags have basic tags and advanced tags. Through the establishment of the algorithm model, the high-level label is calculated. The main algorithm models used are:

Member grouping, including value grouping, behavior grouping, life cycle grouping, etc. Early warning of the loss of members, screening out lost or sleeping members from the results, and activating these members through loss recovery, sleep awakening and other activities; member preference evaluation, including shopping preference, category preference, brand preference, price preference, purchase time preference and so on. Predicting the purchase trend and predicting the possibility of members buying a single product or category in the future can be used to screen potential target customers for specific products. Predict the arrival time of the member and the next arrival or purchase time. Can be used for VIP to remind members to come to the store. The repeat purchase forecast is used to analyze whether a member buys a single item or category on a regular basis, and then determines when the member will come to the store next time and what is likely to be purchased. Members with high loyalty and high loyalty are the high-quality members that need to be maintained in the enterprise. The stability of members reflects the stability of members' consumption behavior, and it is necessary to keep members unstable. The purchasing power of members includes overall purchasing power and a single category of purchasing power (that is, the price at which they tend to buy)

2. The event attracts fans

When carrying out promotional activities, in addition to carefully designing the activities, we also need to identify the target audience. At this time, it is necessary to combine internal and external data to accurately describe components and form a multi-dimensional, deep and fine labeling system.

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3. Online operation mode

One of the features of the new retail is online and offline integration, online customer access, offline shopping experience, online coupons, offline store discounts, online orders, and offline extraction. Online and new retailers generally have Wechat official accounts, WeChat groups (such as emerging community marketing), online malls (Mini Program, APP, self-built malls, etc.), third-party life service platforms (such as Meituan, ele.me) and other channels and tools.

4. Commodity recommendation mechanism

According to members' basic attributes, consumption, browsing, search, activity participation and other information, analyze users' consumption preferences, and recommend appropriate products to members in different scenes and times.

For example, when members browse the details page of Christmas hats, they can recommend Christmas trees, Christmas stockings, Christmas apples and other Christmas-related products to them. When members enter the shopping cart page and there is already baby milk powder in the shopping cart, they can recommend baby products (such as pacifiers, bottles, etc.) to them.

5. Website optimization

For online shopping malls, we can get the detailed page browsing data of each member / visitor through the burial site. Based on this data, we can know which page members / visitors enter from, which pages they see in the middle, when they stay, browse, click, or collect, and from which page they finally jump out. Based on these data, funnel analysis or browsing trajectory analysis can be carried out to analyze the conversion rate of some key paths in the website, determine whether the design of the whole process is reasonable, the advantages and disadvantages of each step, whether there is room for optimization, and constantly optimize the page. E designed to enhance the user experience.

II. Commodity selection / procurement

1. Wise choice

In the new retail era, choice is very important! Because the new retail stores basically achieve the same price online and offline, we can use crawler technology to obtain competitive information in the same industry circle where the store is located, including commodity name, brand, origin, attribute, price, sales volume, activities and so on. Based on this information, we can know:

What is the current category structure and distribution of competitive products? How many kinds of goods are sold? Which goods sell well and what are their characteristics? (the profile reflects the shopping preferences of people in the business circle. (what is "I have him, too"? Find the most similar competitors and the goods sold in the store. See if the current prices of these goods are lower than their own prices, and how much lower? Which products have just been put on the market and which have been removed from the shelves?

At the same time, combined with the attributes of passenger flow in the business circle and the changing characteristics of the interests of the crowd, intelligent selection can provide effective category suggestions, single product suggestions and dynamic pricing support to help goods or purchasing departments decide what to sell and what not to sell. Sell how much, sell how much.

2. Accurate pricing

According to big data and algorithm, the dynamic pricing strategy is to price goods intelligently. Take the price as the axis, take the commodity price elasticity as the foundation, combine the market competition environment, customize the most suitable competitive dynamic pricing strategy for the commodity.

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