Due to changes in consumer purchasing behavior in the new normal, EC sites have become familiar to consumers regardless of age and gender. For many companies, including manufacturers and retailers, the importance of EC sites seems to be increasing year by year. As the importance of EC sites increases, the workload on the management side increases proportionately, and the site is constantly suffering from a labor shortage. Specifically, compared to real stores, EC sites generally have no physical planograms, making it easier to increase the number of products handled. Being able to provide customers with a wide variety of products that are not available in real stores is an advantage, but it is also one of the major factors that increases the burden on the management side. In such a situation, it is difficult to complete all tasks perfectly, and it is necessary to respond while setting some sort of priority.
This time, we will explain how to efficiently find bottlenecks that are directly linked to business results and how to proceed with improvement actions for busy EC site managers.
Author profile
Representative of Colabofact / CDO of Bsidefunny Co., Ltd.
Mr. Yusuke Komatsu
Joined Members Co., Ltd. after graduating from Hosei University. Six and a half years of experience in website construction / operation direction and project management for major domestic financial institutions and manufacturers. Engaged as manager of the company. Joined Amazon Japan GK since 2015. After two years of experience as a site merchandiser in digital marketing, from strategy to execution and analysis, as a buyer, experienced business strategy, P/L management, demand forecasting, and product planning in the category in charge. Participated in Principle Co., Ltd. since March 2019. Launched a dedicated sales department, and since October 2020, has been in charge of launching the company's DX business department and responsible for business operations. In May 2021, he joined Bsidefunny Co., Ltd. as a partner and CDO. Independent as a sole proprietor from June 2021.
[EC Business Growth x AI] Series No. 5 INDEX
- Increase in EC site operations and need for overall optimization
- How to find bottlenecks from data analysis
- How to link data analysis to improvement actions
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▼[EC Business Growth x AI] Click here for previous articles in the series
[Part 1] What are the specific measures to grow your EC business? Explain the points to keep winning in the expanding EC market!
[Part 2] The success or failure of ASKUL Corporation, which handles more than 10 million items, uses AI behind the EC
[Part 3] How to reduce opportunity loss due to shortages in EC site management? Introducing the points of inventory management using AI demand forecast!
[Part 4] Key Points for Competitive Pricing Using AI on EC Sites
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1. Increase in EC site operations and need for overall optimization
In order to find bottlenecks that are directly linked to EC site growth, it is necessary to first organize the overall picture of EC site management operations.
EC site management starts with the purchase of products to be sold and product planning, and extends to post-sales delivery and after-sales support. While there are issues and things to think about in each business, it is never easy to identify bottlenecks across operational tasks in different departments and responsibilities. Readers may be having trouble deciding which areas to focus on on their e-commerce sites. In order to maximize business results with limited resources, we identify areas to focus on based on objective facts, allocate resources, and take continuous improvement actions for overall optimization. is the first step towards continuous growth.
2. How to find bottlenecks from data analysis
So how do we identify specific areas to focus on? In order to eliminate various biases and determine bottlenecks as much as possible, it is important to read and understand the data (data analysis). The following two points are important for data analysis on EC sites.
- Breaking down the elements that make up the sales of the EC site (dividing work)
- Compare each decomposed element (work to compare)
The first step in data analysis is to divide the data. There are two ways to divide the data.
a. How to divide so that it can be expressed by multiplication
b. How to divide so that it can be expressed by addition
As an example of expressing the sales of an EC site a. by multiplication, there is a method of breaking it down into "number of visits x conversion rate (CVR) x unit price of purchase". Also, as an example of b. addition, there is a method of breaking down sales by category such as "Category A + Category B + Category C". Just by dividing the data, you can get various information hidden in the whole number.
However, it is necessary to compare the data after dividing the data in order to gain insights that lead to the identification of bottlenecks. For example, how would you answer the question, "Is ¥1,000 expensive or cheap?" Most likely, the answer would be “I can’t say either way”. In order to evaluate the data, it is necessary to have some kind of standard, a comparison target. As a premise for the previous question, if "juice normally sold for about ¥100 is sold for ¥1,000", it will be evaluated as high, and "if clothes normally sold for ¥5,000 are sold for ¥1,000" If it is sold at ", I think that it will be evaluated as cheap. The following is a simple example, but by combining the elements divided in 1. with the contents compared in b., you can quantitatively narrow down which areas are likely to have issues. If I were you, I would focus on the CVR of Category C in this example, and since it is at a low level compared to other categories, I would judge that there is some kind of bottleneck (growth margin), and proceed with detailed analysis. Take action that leads to action accordingly.
3. How to link data analysis to improvement actions
As the next step after objectively identifying bottlenecks based on data analysis, we will move on to the work of connecting the bottlenecks to improvement actions for business growth.
Of course, finding the bottlenecks alone will not produce results, and you will only get results once you take action to improve them. In my experience, there are few cases where the action that will always produce results is clear from the beginning, and by repeating trial and error to find a success pattern for your own site and continuing improvement actions, it will lead to continuous growth. There are many Here, we will explain the relationship between important indicators and actions on general EC sites.
First, the three important indicators for EC sites are "A. Number of visits", "B. CVR", and "C. Purchase unit price", which were introduced as examples earlier. By breaking down sales into these three indicators, it becomes possible to link data and customer behavior for analysis.
- Number of visits: An indicator that shows how many times customers have visited your website
- CVR: An index that indicates what percentage of customers who visit your website make purchases
- Purchase unit price: An indicator that indicates how much a customer purchases a product
By linking and analyzing data and customer behavior, it becomes clear what actions should be taken.
[Examples of improvement actions based on data analysis]
A. When "number of visits" is the bottleneck
In order to show that the number of customers visiting the site is small in the first place, it is effective to implement measures to make the flow of customers to the site smoother. SEO, advertisements, and improvement of leads within the site are considered typical examples.
B. "CVR was the bottleneck
This shows that there are many cases where customers do not make purchases for some reason despite visiting the site, so it is effective to take measures to improve the situation in which customers find it difficult to make purchases. Typical examples include the maintenance of necessary and sufficient catalog information (product information) for customers to make purchasing decisions, price setting, and securing inventory.
C. When the "purchase unit price" is the bottleneck
It is effective to implement measures that make it easier for customers to buy products with higher unit prices or bulk purchases.
The point here is to consider whether the measures to be implemented are “actionable” or not. For example, as a result of data analysis, even if the cause is inventory shortage (out of stock), it is difficult to take immediate improvement action if the product is out of stock for a long time due to shortage of parts, and recovery measures other than this product are difficult. I have to take lessons.
In this way, in order to achieve continuous growth under various constraints, it is a shortcut to prioritize and speedily implement measures that can be taken or are easy to take in areas with high impact on growth potential. I think it is.
Did you get an idea of how to proceed with data analysis on your own e-commerce site from the content so far?
At Macnica we provide support through assessment services on how to identify more specific bottlenecks and create action plans. Please feel free to contact us for a free initial diagnosis.
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