BTC common analysis index
1, commodity
commodity is one of the most detailed dimensions of retail analysis, most of the indicators are attached to commodities to make detailed records, and many dimensions are also cross analyzed through commodities
2. Customers
customers are sales targets, including members. The location of the customer is related to the region
3. Region
region is a geographical location. From a global perspective: continent country region; From the perspective of the country: District - province / city - county / district - town / township / village, generally divided by formal administrative units
4. Time
time is a very important dimension for data analysis, and the angle of analysis includes Gregorian calendar and lunar calendar. Among them, the Gregorian calendar angle: year Quarter Month Day period (every 2 hours is a period); Weekdays, Gregorian holidays. From the perspective of lunar calendar: year solar term day moment; Lunar holidays< (2) sales data indicators
1. Sales quantity
the quantity of goods consumed by customers
2. Sales including tax
the amount paid by customers to purchase goods< 3. Gross profit
gross profit = actual sales cost
4. Net profit
net profit = sales excluding tax - cost excluding tax
5. Gross profit margin
sales gross profit margin is the percentage of gross profit in sales revenue, also referred to as gross profit margin, where gross profit is the difference between sales revenue and sales cost
gross margin = (gross margin / actual sales) × 100%
6. Turnover
turnover is related to the statistical time period. Turnover = (sales tag amount / inventory amount) × 100%
7. Promotion times
promotion times have macro concept and micro concept. Macroscopically, it refers to the number of promotions launched by a sales unit in a period of time, or the number of promotions participated by a supplier's goods in a period of time; On the micro level, it means the number of times a single proct participates in promotion over a period of time
8. Transaction times
the customer pays a transaction record at the POS point as a transaction
9. Customer unit price
the sum of the amount paid by customers in a transaction is called customer unit price
customer unit price = sales volume / transaction times
10. Turnover days
turnover days = inventory amount / sales tag amount. The longer the turnover days, the lower the operating efficiency or the worse the inventory management; The shorter the turnover days, the higher the operating efficiency or inventory management
11. Return rate
return rate = return amount / purchase amount (over a period of time); An indicator used to describe operating efficiency or inventory management. It is time-dependent
12. Sold out rate
sold out rate = sales quantity / purchase quantity
13. Stock to sales ratio
stock to sales ratio = ending inventory amount / (current sales price / sales days * 30)
(only quantity can replace amount in single SKU calculation.)
14. Joint rate
joint rate = number of sales / number of transactions
15. Average unit price
average unit price = sales amount / sales pieces
16. Average discount
average discount = sales amount / sales tag amount
17. SKU (depth and width)
the English full name is stock keeping unit, short for sku, which is defined as the minimum available unit to keep inventory control. For example, a SKU in textiles usually represents a specification, color, style), i.e. article number, for example: amf80570-1
18. Futures
the so-called futures generally refer to futures contracts, which are standardized contracts formulated by futures exchanges to deliver a certain number of objects at a specific time and place in the future. In the clothing instry, it specifically refers to the goods ordered at the order meeting and delivered in installments
19. Floor efficiency
refers to the efficiency of 1 square meter of terminal stores, which is generally used as an important standard to evaluate the strength of stores
floor effect = sales amount / store business area (excluding warehouse area)
20. Promotional commodities
refer to the commodities designated ring the promotion period whose prices are lower than those of the same kind in the market. Including DM goods, store promotion, ordinary promotion goods (special price), excluding normal price rection< (3) sales data analysis methods
1. Direct data analysis
2. Combination analysis of indirect data.
The three common indicators of commodity data analysis are:
1, passenger flow, customer unit price analysis:
mainly refers to the average daily passenger flow and customer unit price of this month, compared with the same period of last year. This group of data in the analysis of store customer flow, customer unit price, pay special attention to the comparative analysis of stores ring and before the promotion activities, whether the promotion activities play a certain role in improving the store customer flow, customer unit price
extended data
the combination analysis method of indirect data of commodity; The analysis conditions are time period (arbitrary time period, natural time period) and operation mode; Analysis level is headquarters, stores, category, style, price band, single proct
2. Correlation analysis (year-on-year / month on month analysis)
pass the report conditions of the upper level analysis to the year-on-year analysis, use the structure of year-on-year analysis to test the results of our gross profit adjustment strategy, and look at the data change trend, so as to carry out the commodity adjustment in the next stage
3. The number of customers and the unit price of customers are two effective ways to increase sales: increasing the number of customers to realize consumption and increasing the amount of money each customer purchases. The high number of effective customers (i.e. the customers who realize consumption) indicates that your goods, prices and services can attract and meet the needs of consumers, and the high unit price of customers indicates that the width of your goods can meet the one-stop shopping psychology of consumers, and the relevance and coherence of commodity display can continuously stimulate the purchasing desire of consumers
1. Such as the number of users, new users, UGC (social procts), sales volume, payment volume, various data ring the promotion period, etc. These are the most basic and also the most basic indicators that bosses are most concerned about. When you take over this work, the first task is to sort out the data
2. Channel analysis, or flow analysis. For an app in the rising period, you will spend resources to attract traffic and attract users from other channels. At this time, we need to monitor the quality of each channel, which effect is good, which unit price is cheap, which needs channel data monitoring to complete. Of course, you also need to track and monitor the follow-up performance of users in different channels, score the users in each channel, and let the boss know which channel is worth investing and which channel is rubbish. At the same time, it can also monitor the quality difference between iPhone and Android users. Generally speaking, the quality of iPhone users is slightly higher than that of Android users. Of course, if you have extra energy, you can also monitor the performance differences among users of different models. In short, it is to monitor the performance of different users in different dimensions
3. Core conversion rate of users. Think about what is the core function of your app, and then monitor the conversion rate of this core function. It may be called payment rate in Game App, and it may be called purchase rate in e-commerce app. Different instries have different conversion rates. You can compare your procts with the instry average to see the position of your procts in the instry. At the same time, through long-term monitoring, you can use this data to judge the quality of different versions of app
4. Monitoring of user usage time. On the one hand, it's a very good indicator of user activity. Long usage time means high activity, and vice versa. On the other hand, when designing your app, how much time did you expect a normal user to spend every day, and whether the actual time users spent after going online is the same as you expected? If there is a big deviation in this, it means that the user's perception of app is different from your assumption at that time. At this time, you need to think about how to adjust your proct to meet the user's cognition Here's a digression. I think that when we make changes to the proct, we must try to cater to the users, rather than try to change the users so that the users can adapt to the proct. Taking microblog as an example, users always regard microblog as a media proct and an information exchange tool. Microblog has always wanted to build it into a comprehensive social platform, launching microblog members, user recommendations, various private letter comment rules, etc. background facts have proved that all of these have not changed users' cognition of microblog, and everything microblog has done is invalid. So when you are worried about why the user does not use the proct according to my idea, you must think about how I can change to meet the user's needs, rather than how I can change to make the user approve the proct design
5. Loss of users. On the one hand, we need to monitor the churn rate of users, such as how many people are still using the proct in the first, third, seventh, and thirtieth days after new users come in. The change of turnover rate can directly reflect whether app is developing in a good direction or a bad direction. There are also some average indicators in the instry, you can refer to these indicators to judge the quality of your app. On the other hand, we need to find out where users are losing, see where users are losing, and then make corresponding changes. If you have the ability, modeling will depict all kinds of user churn, so that you can be more comfortable in the subsequent changes of the proct
6. Active users. Pay close attention to the dynamic of APP active users and listen to their voice. Once found abnormal, immediately organize personnel to discuss countermeasures. Active users (or core users) are the most valuable resources of app. It's not necessary to say more about the importance of paying attention to their every move.
7. User characteristics description. This has little to do with indicators. It's a bit of modeling. The more detailed the user's characteristics, the better. Such as gender, age, region, mobile phone model, network model, occupation income, hobbies and so on. This data is usually useless, but for proct personnel, sometimes it will give them a lot of inspiration. If possible, it can be divided into the following dimensions: what are the characteristics of active users, what are the characteristics of silent users, and what are the characteristics of lost users
8. Monitoring of user life cycle. This is specifically for social and game apps. When your app is online for a period of time (6-12 months), you can look back at a normal user to fully experience the process of your app and how long it will take. According to this data, combined with some other data, we can roughly estimate the scale of your proct, and let your boss know what kind of proct will eventually develop into. Of course, this is very difficult. The development of the proct is affected by too many factors. It is obviously not so reliable to rely on you as a data analyst.
the first is to obtain external public data sets. Some scientific research institutions, enterprises and governments will open some data, and you need to download these data from specific websites. These data sets are usually relatively perfect and of relatively high quality
1、 Short term solvency analysis:
1. Current ratio, calculation formula: current assets / current liabilities
2. Quick ratio, calculation formula: (current assets inventory) / current liabilities
3. Cash ratio, calculation formula: (cash + cash equivalents) / current liabilities
4. Cash flow ratio, Calculation formula: cash flow from operating activities / current liabilities
5. Repayment ratio of principal and interest of maturing debt. Calculation formula: net cash flow from operating activities / (principal of current maturing debt + cash interest expense)
2. Analysis of long-term solvency:
1. Asset liability ratio. Calculation formula: Total Liabilities / total assets
2. Shareholders' equity ratio, Calculation formula: total shareholders' equity / total assets
3, equity multiplier, calculation formula: total assets / total shareholders' equity
4, debt equity ratio, calculation formula: Total Liabilities / total shareholders' equity
5, debt ratio of tangible net worth, calculation formula: Total Liabilities / (shareholders' equity net intangible assets)
6, debt service guarantee ratio, Calculation formula: Total Liabilities / net cash flow of operating activities
7, interest protection ratio, calculation formula: (pre tax profit + interest expense) / interest expense
8, cash interest protection ratio, calculation formula: (net cash flow of operating activities + cash interest expense + cash income tax) / cash interest expense
3. Operation analysis
1 Inventory turnover, calculation formula: sales cost / average inventory
2. Accounts receivable turnover, calculation formula: net sales revenue on credit / average balance of accounts receivable
3. Current assets turnover, calculation formula: sales revenue / average balance of current assets
4. Fixed assets turnover, calculation formula: sales revenue / average net fixed assets
5 Total assets turnover, calculation formula: sales revenue / total average assets
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IV. profit analysis
1. Return on assets, calculation formula: total profit + interest expense / total average assets
2. Return on net assets, calculation formula: total profit + interest expense / average net assets
3. Return on shareholders' equity, Calculation formula: net profit / average total shareholder's equity
4. Gross profit rate; calculation formula: gross sales profit / net sales income
5. Net sales interest rate; calculation formula: net profit / net sales income
6. Net cost interest rate; calculation formula: net profit / total cost expense
7. Profit per share, Calculation formula: (net profit - dividend of preferred stock) / number of outstanding shares
8, cash flow per share, calculation formula: (net cash flow of operating activities - dividend of preferred stock) / number of outstanding shares
9, dividend per share, calculation formula: (total cash dividend - dividend of preferred stock) / number of outstanding shares
10, dividend distribution rate, Calculation formula: dividend per share / profit per share
11, net assets per share; calculation formula: total shareholders' equity / number of shares outstanding
12, P / E ratio; calculation formula: market price per share / profit per share
13, profit margin of main business = profit of main business / income of main business * 100%
v. development analysis
1, business growth rate, Calculation formula: current business growth / total business income of the same period last year
2, capital accumulation rate; calculation formula: current owner's equity growth / owner's equity at the beginning of the year
3, total assets growth rate; calculation formula: current total assets growth / total assets at the beginning of the year
4, fixed assets newness rate, Calculation formula: average net value of fixed assets / average original value of fixed assets
1. Purpose:
KD is developed on the basis of WMS, so KD has some characteristics of WMS. When reflecting the change of stock price, WMS is the fastest, K is the second, D is the slowest. When using KD index, we often call K index as fast index and D index as slow index. K index is quick but easy to make mistakes, D index is slow but steady and reliable< Second, how to use it:
1. Considering the value of KD, over 80 is the overbought area, and under 20 is the overbought area. If KD is more than 80, it should be considered to sell, and if KD is less than 20, it should be considered to buy
2. Considering the cross aspect of KD index, k over D is the golden fork. For a buying signal, the position of the golden fork should be relatively low, which is in the oversold area. The lower the better. The number of intersections is the least, the more the better
3. Consider the deviation of KD index
(1) when KD is at a high level and two downward peaks are formed, and at this time, the shares are still rising vigorously, which is called top deviation and a signal to sell
(2) when KD is in a low position and the bottom is higher than the bottom, and the stock price continues to fall, it constitutes a bottom deviation and is a buying signal
4. If the value of J index is higher than 100 or lower than 0, it belongs to the abnormal area of price. If the value is higher than 100, it means overbought. If the value is lower than 0, it means oversold. Moreover, the signal of J value will not appear frequently. Once it appears, the reliability is quite high
use experience:
1. When the stock price fluctuates violently in the short term or the instantaneous market amplitude is too large, using Kd value cross signal trading often leads to the dilemma of buying at the high point and selling at the low point. At this time, we should give up using KD random index and use CCI, ROC, Bollinger Bands ··. However, if the fluctuation is large enough and there is still a profit after decting the handling charge between sales and purchase, you can turn the picture into a five minute or fifteen minute graph, and then trade with the cross signal of KD index, and you can make a little profit
2. The extremely strong or weak market will cause the index to hover up and down in the overbought or oversold area, and the K value will also be issued. We should refer to VR and ROC index to observe whether the stock price is beyond the normal distribution range. Once the trend is determined to be extremely strong or weak, the overbought function of K value will lose its function
3. Replacing K value with D value will make the function of overbought and oversold more effective. In normal market, when D value is greater than 80, the stock price often falls back; When D value is lower than 20, the stock price is easy to rise. In the extreme market, when the D value is greater than 90, the stock price is easy to reverse instantly; When the D value is lower than 15, the stock price is easy to rebound instantaneously.
KDJ index, also known as random index, is a quite novel and practical technical analysis index. It was first used in the analysis of futures market, and then widely used in the short-term trend analysis of stock market. It is the most commonly used technical analysis tool in futures and stock market. If you are a friend who just entered the stock market, we will let you better learn this technical index through text and video. In fact, the random index KDJ is generally a statistical system used for stock analysis. According to the statistical principle, the immature random value RSV of the last calculation cycle is calculated by the highest price, the lowest price and the closing price of the last calculation cycle in a specific cycle (usually 9 days, 9 weeks, etc.) and the proportional relationship among them, Then according to the smooth moving average method to calculate the K value, D value and J value, and draw a curve to study the stock price trend. Next, I will share the stock knowledge I learned on HuiFu platform
1. Course Name: KDJ index of technical index refinement. The course will talk about the role of technical index, the classification of technical index, and the three principles of using technical index. In the course, you will be able to understand and use the index tactics after listening to the trend cases of indivial stocks
Second, KDJ, the index with the highest interest rate in the stock market, has more details. I hope you can watch it carefully, and I believe you will get something. KDJ is one of the most common K-line indicators, also known as "short-term trading artifact". Next, the author will introce in detail how to use KDJ indicators and grasp the short-term market
thirdly, KDJ index uses real price fluctuation to reflect the power comparison between buyers and sellers in the market. In the calculation process, only the recent highest price, lowest price and closing price are considered, which is characterized by being able to judge the market quickly and intuitively
KDJ is an index of overbought and oversold, which studies and judges the high and low stock prices. According to the value of KDJ, we divide the KDJ area into:
1, overbought area: K, D, J below 20 are overbought areas, which are buying signals
2. Oversold area: the three values of K, D and j above 80 are overbought areas, which are selling signals
3. Wandering area: K, D and j are wandering areas between 20 and 80, so we should wait and see
operation points:
1. When the top deviation occurs, the higher the position of the K line, the stronger the bearish signal of this form
2. If the trading volume continues to shrink in the process of top deviation, it verifies the signal of continuous shrinkage of multi forces in the market. At this time, the bearish signal of this form will be stronger
3. If the K-line deviates from the top of the stock price and the D-line deviates from the top of the stock price, the bearish signal of this form will be more reliable
KDJ trading principle
1. Kd value is always between 0 and 100, and 50 is the long short equilibrium line. It means that if many parties are strong, 50 is the support line; If you are in the short market, 50 will become the pressure of rebound
2. If K value is above 90, it is an overbought area, and if K value is below 10, it is an overbought area; If the value of D is above 80, it is an overbought area, and if the value is below 20, it is an overbought area
3. When the K-line breaks through the D-line upward, it indicates an upward trend and can be bought; When the K line breaks down through the D line, you have to consider selling
in addition to the above criteria, in a complete process of rising and falling, KDJ has two more direct forms of judging buying and selling signals, which we often call golden fork and dead fork
KDJ index knowledge, if you can't understand the text? You can listen to HuiFu's "KDJ index of technical index refinement", which will make it easier for you to learn and use KDJ index method.