How To Make Use Of Big Data "Horse Racing" In Original Women'S Clothing?

Originality of the new 300 quarter per quarter

How to make quick selection in shops in a short time

It is also reflected in the operation and supply chain. The data provided by the staff of the Tmall flagship store, using fireworks, set up a scientific "horse racing" mechanism.

After the implementation of the double 11 system in 2015, sales in 2016 increased by more than 100% in the 1-5 months of 2016.

Fireworks and Tmall's flagship store has about 300 new products per quarter. We have to evaluate the performance of these 300 products in a short time, and make corresponding adjustments in operation and supply side in time.

The selection criteria for "excellent and medium difference" are especially important, which can not be judged by feeling, nor can it be sold simply by sales volume.

Using the data provided by our business staff, we have established a scientific "horse racing" mechanism, using data indicators and multi-dimensional comprehensive evaluation. The operation team has targeted to give each fair relatively fair opportunity to participate in the next round of "horse racing" after adjustment.

In this way, the real money that comes out eventually must be a good quality.

The result of a horse race and 2-3 races each week can basically determine the difference between good and bad.

First round: comprehensive marking

The commodity analysis function of the business staff provides a complete product data, with a very fine granularity. Besides the indicators of visitors and paction, there are indicators such as purchase, collection and page retention time, which can reflect customers' preferences for commodities.

We often encounter the following problems when we select "good or bad" in commodities.

The quantity of visitors is large, and the conversion rate is low.

Commodities with high conversion rate have less turnover.

Low volume of goods and low unit price.

Then what kind of products are high quality? We need to use the comprehensive evaluation analysis method, using multiple indicators to score multiple products.

The monthly visitor quota data are often tens of thousands, and the conversion rate is a percentage, so we need to standardize the index data first, so that we can calculate and compare the same channel.

After the standard score is calculated, the total score is added according to the weight of each index.

In the details of the product effect of the business staff, you can download all the indicators of the Commodity daily:

After downloading, the comprehensive evaluation analysis method is used to calculate the index data and get the final score. The result is a "horse racing" report card.

{page_break}

The second round: adjusting commodity flow and pformation

After the first report card comes out, we need to adjust the flow and pformation of the goods to give more fair opportunities to the commodities so that they can make progress in the next "horse race".

For different types of commodities, the adjustment strategies are different.

For the high number of visitors, the high proportion of commodities will gradually increase the number of visitors.

For the high number of visitors, the low total number of commodities, gradually reduce the number of visitors, while considering greater preferential / mix adjustment, to improve the conversion rate;

For the low number of visitors, the high proportion of commodities will gradually increase the number of visitors.

For the low number of visitors, the overall score is low, consider greater concessions, and improve the conversion rate;

If the strategy is not implemented effectively, it is empty talk.

Whether we are in place or not, we can monitor by the single product analysis of business tools.

Whether there is an upward trend in the number of merchandise visitors in the next race race, whether the conversion rate, residence time and other indicators show an upward trend, can be seen very clearly through the trend map, if not implemented in place, can be improved for the first time.

Third round: comparison of results of each race

In addition to looking at the trend, we need to see the cumulative value of each race, and confirm whether this period is compared with the previous period.

The cumulative value needs to be aggregated from the detailed data of the product downloaded from the business staff.

After the 2-3 phase of the race, we can basically judge the "good and bad" of the merchandise accurately. Next is the adjustment of the merchandise strategy, the excellent merchandise supplement, the good money continues, the medium and the bad money will be discounted as soon as possible and go to stock.

Since it is "horse racing", we should be well aware of the strengths and weaknesses of horses through the adjustment ahead, and make the best performance of the whole "horse group".

We will find that after a few rounds of adjustment, the overall score of some large visitors is still low, indicating that this type of commodity has strong drainage capability and may belong to the "no applause" type of merchandise. Through the analysis of the single product in the business staff, we can see where the main part of the product is coming from the source and whereabouts. We promptly adjust the related products of this commodity and regard the commodity as the traffic entrance. If the related commodities are adjusted well, the overall turnover will be good.

As an original design women's clothing brand developed from Taobao, the fireworks and ironing operation team attaches great importance to the products. All the operation strategies and actions are operated at the core of the product.

In the fireworks operation team, "everyone is a product manager". Through the adjustment and optimization of all aspects of the data through the data of the business staff, we can truly achieve the ultimate goal of data operation.

We started the "horse racing mechanism" in 2015 after the double 11 in 2015. Through half year's optimization adjustment, we promoted the upgrading of new products in spring and summer.

Under the efforts of everyone, the sales of Tmall flagship store in 2016 1-5 months compared with the same period in 2015, the sales growth rate exceeded 100%.