Just in the past week, more than 200 stores have experienced the new functions of Alibaba’s official Omni channel, Omni link, one-stop data platform, including self-service analysis.
As the first attempt of business staff and quick Bi, “self service analysis” provides self-service analysis solutions for stores, supports the production of personalized data reports for stores, supports long-term data storage and analysis, and forms exclusive data monitoring and analysis Kanban for stores, so as to help improve the operation efficiency of stores.
“The self-service analysis function makes the data statistics and analysis of the store easier,” Song Fuxiang, the head of the operation of the alfen tmall flagship store in the kitchen, told the reporter. “The data statistics and analysis work that used to take one hour to complete, now it can be easily done in one minute.”
New business advisor function “self service analysis” can be customized to build multi-dimensional data reports
Referentialism corrected by data
In June this year, song Fuxiang’s tmall flagship store “ah Fen in the kitchen” turned its focus from seasoning to convenient fast food market. At present, it is still in the stage of “everything is difficult at the beginning”.
“In the past, the store could have more than a million sales a month, but now it has to start from 0.” When talking about the sales after the transformation of the store, song Fuxiang brought some self mockery, but he was not very worried about the “pain” at this stage.
According to song Fuxiang and his team, all kinds of instant food products have entered a new stage of product redefinition and consumption upgrading. In particular, in the self hot food segment, the online market has begun to take shape, with obvious head effect. “For new brands entering the track, if they want to start quickly, they need to have more different grasp and promotion strategies.” Song Fuxiang introduced.
However, steamed rice dishes are rich in Chinese style food and are not available for data collection. They can only rely on brand positioning, competition analysis and offline food taste recommendation. Song Fuxiang said, “we target the market in white collar workers in a second tier city, distinguish the main flavors of the hardcore rice products, and hope to concentrate on the” salty “essence. The quality of the characteristics of Laofan to market segmentation, open up the situation. “
During this year’s tmall 618 consumption season, a total of four kinds of flavor rice products including “table stewed meat”, “spicy beef” catering to the taste of the mass market, and innovative tastes of “abalone” and “pepper chicken” were officially launched.
Not long after the first batch of products came out, the business staff brought surprise product data feedback to the team. Song Fuxiang told reporters, “the data shows that in June, although the unit price of abalone and fried chicken rice was relatively high, the re purchase was also higher in the first round of trial. The two products were also asked to return in several live broadcasts in the form of single taste.”
Through the business staff, the operation team can view the overall business data of the store in real time. At the same time, the multi-dimensional data of the whole life cycle, including flow, exposure, consultation, transaction and after-sales, can be used for each commodity in real time. Based on these data, at present, ah Fen in the kitchen has begun to reorganize the store SKU strategy, and is about to launch the seasonal new product “crab flavor self heating rice” ”For the second half of the store to continue to make full preparation.
Business consultant data insight boosts new product “crab flavor self heating rice”
Self help analysis helps store management to complete data analysis in one minute
The successful transformation of the alfen tmall flagship store in the kitchen has made song Fuxiang more aware of the importance of data for commodities and even the whole store operation.
In the seventh year of contact with e-commerce, song Fuxiang has long known how to adjust the store’s business strategy by relying on data, and has formed the habit of checking the store’s data through business advisors every day, “from store flow to commodity promotion, to trading end and customer experience review Through the different modules of the business advisor to view and count the data of each port, the whole set of analysis often takes more than an hour. “
Not long ago, the “self-help analysis” function of the business staff was officially launched, as one of the core products of the business staff and alicloud data center quick Bi’s first attempt, the “self-service analysis” function gathers the multi-dimensional data of the business staff about the store at the present stage. In the visual operation interface, the store operators can synchronously view more than 100 data indicators, including store traffic, commodity traffic, jump rate, etc., and can immediately call them to form data reports that meet their own needs.
Song Fuxiang said that in the past, it was necessary to view and count the corresponding data in different modules of business staff, but now it is possible to select user-defined generation in “self-service analysis” with one click. “For our store operators, the workload that used to take one hour to complete is now basically completed in about one minute, and the statistical results are more accurate and clear.”
At the same time, for the novice store operators who first contact with report building, “self service analysis” also provides multiple report templates for selection.
According to Pu Zhengyang, the person in charge of the flagship store of cream Mantang tmall, the two report types currently provided by “self-service analysis” have been able to meet most of the data analysis demands of the store. “The data template brought by the business advisor focuses on presenting the core data of the whole store, but if you focus on the operation scenarios, such as commodity dimension and keyword dimension, you still need the store operator According to the actual needs of the staff to carry out data dimension screening and independent report building, and then according to the final analysis results data to carry out product link promotion and SKU distribution adjustment
In addition, in addition to customized reports needed to build stores, “self-service analysis” also provides long-term data storage capacity.
“For example, it’s the peak season for our store to sell hairy crabs. This year’s main family sharing hairy crabs package needs the data of similar products in the same period of last year as a reference. Then there are various promotion scenarios such as double 11, double 12 and new year’s day. The long-term data storage capacity provided by the self-service analysis module complements our data comparison in the same period Appeal. ” Pu Zhengyang said.
Song Fuxiang, who has just set up a new team to complete the transformation of the store, has more considerations. The mobility of the store operation post is relatively large, and the data handover work is usually more complex. “A lot of data is actually difficult to save, so self-help analysis can now store the core data of nearly a year and a half for the store, which actually provides a great guarantee for the operation of our whole store.”
In the view of Yike, a senior expert on data products on Alibaba platform, the new online “self-help analysis” function can, to a certain extent, flatten the data analysis and store operation ability of different volume stores. “Stores with large volume often start to guide store operation through data very early, and at the same time pay attention to data personnel training and organization construction; relatively, small and medium-sized businesses are more competitive because of the lack of data Due to the lack of professional data and post setting, it is not particularly able to conduct centralized statistical analysis on the complex and multidimensional store data. We hope that by continuously enriching and improving the functions of business advisors, and introducing more professional lecturers and analysis talents, we can help more stores to make up for this ability and improve the operational efficiency of stores. “
In the future, “self-service analysis” will gradually launch more dimensional data, realize “one click” all-round store operation data statistics and analysis, and benefit more than 20 million cumulative users.
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