KR20070076884A - Method for predicting the amount of selling using sensory evaluation and system therefor - Google Patents

Abstract

A method and a system for predicting sales based on sensory evaluation are provided to predict a market share from a sensory evaluation result of a new product by extracting a relation between sensory quality competitive power and the market share from the sensory evaluation result and the market share information. An input part(130) receives the sensory evaluation result, the market share/sales information, and purchase decision factor information of each product. A weight calculator(140) calculates sensory evaluation quality weight and non-sensory quality weight of each product from the purchase decision factor information. A sensory quality competitive power calculator(150) calculates the sensory quality competitive power from the sensory evaluation result stored in a sensory evaluation database(100). A market share predictor(160) calculates the relation between the sensory quality competitive power and the market share from the information calculated in each part, and predicts the market share/sales from the sensory evaluation results by using the relation.

Description

METHOD FOR PREDICTING THE AMOUNT OF SELLING USING SENSORY EVALUATION AND SYSTEM THEREFOR}

1 is a flowchart illustrating a sales forecasting method through sensory evaluation according to an embodiment of the present invention.

2 illustrates the relationship between sensory quality competitiveness and market share.

3 is a block diagram showing a sales forecasting system through sensory evaluation according to an embodiment of the present invention.

<Description of Signs of Major Parts of Drawings>

100: sensory evaluation database 110: market share database

120: purchase decision database 130: input unit

140: weight calculation unit 150: sensory quality competitiveness calculation unit

160: Market share prediction department

The present invention relates to a sales forecasting method and a sales forecasting system through sensory evaluation. In particular, a relation between sensory quality competitiveness and market share is derived from previous sensory evaluation results and market share information. It is about technology that can predict the market share.

Sensory evaluation of food is a field of science that measures the strength, weakness, goodness and dislike of individual characteristics of a product through human senses (visual, olfactory, taste, auditory and tactile). It is mainly used for product development, quality control and marketing.

However, the current level of the use of sensory evaluation results is to grasp the degree of product quality or to measure the preference or preference of the consumer group and to use it as a basis for decision-making on the launch of new products. It is difficult to judge the success of a product in the market or to predict the success rate.

In addition to the sensory quality of a product, the success of the product in the market is influenced by several factors (e.g. brand image, price, raw materials, promotions, advertising, etc.). There is no comprehensive analysis.

In order to solve the above problems, the present invention derives a relation between sensory quality competitiveness and market share from previous sensory evaluation results and market share information in consideration of non-sensory quality competitiveness and derives market share from new sensory evaluation results of new products. The purpose is to provide a sales forecasting method through predictable sensory evaluation.

According to the present invention, a method for predicting sales through sensory evaluation includes constructing a sensory evaluation database from sensory evaluation results for each product; Calculating sensory quality competitiveness from sensory evaluation information for each product of the sensory evaluation database; Deriving a relation between sensory quality competitiveness and market share using the calculated sensory quality competitiveness and previous market share information; And predicting market share and sales for each product from the sensory evaluation results for each new product using the relational expression.

In addition, the sales forecasting system through the sensory evaluation according to the present invention includes an input unit for receiving sensory evaluation results for each product, market share and sales information for each product, purchase decision factors for each product; A sensory evaluation database configured to receive and store the sensory evaluation result for each product from an input unit; A weight calculation unit for calculating the sensory quality weight value and the sensory quality weight value for each product from the purchase decision factor information for each product; A sensory quality competitiveness calculation unit that calculates sensory quality competitiveness for each product from the sensory evaluation results for each product of the sensory evaluation database; And the sensory quality competitiveness and market share using the calculated sensory quality competitiveness output from the sensory quality competitiveness calculation unit, market share information for each product, sensory quality weight value for each product output from the weight calculator, and non- sensory quality weight value. And a market share prediction unit that calculates a market share and a sales amount of each product from the sensory evaluation result of each new product using the relationship equation.

Hereinafter, with reference to the accompanying drawings, preferred embodiments of the present invention will be described in detail.

1 is a flow chart illustrating a sales forecasting method through sensory evaluation according to an embodiment of the present invention.

Referring to FIG. 1, a market share database is constructed from market share and sales information for each product (S10).

From the sensory evaluation results for each product to build a sensory evaluation database (S20).

The purchase decision factor database is constructed from the result of the purchase decision factor survey for each product (S30).

The sensory quality weight value and the non-sensory quality weight value for each product are calculated from the information of the purchase decision factor database (S40).

The calculation process is performed by classifying items of purchasing decision factors for each product into a sensory quality and a sensory quality and then summing the indexes of each item according to the classification.

Table 1 shows the importance data of purchasing decision factors by product obtained from the survey of consumers.

flavor price brand Raw material Promotional Event tofu 0.261 0.112 0.115 0.361 0.111 if 0.330 0.110 0.136 0.265 0.159 Bean sprouts 0.248 0.115 0.162 0.365 0.110 Kimchi 0.280 0.099 0.155 0.339 0.127 Seasoned seaweed 0.331 0.136 0.111 0.249 0.173

Here, taste is about sensory quality, and price, brand, raw materials used, promotion events, etc. are about sensory quality.

Therefore, after classifying items of purchasing decision factor by product on sensory quality and extra sensory quality, the result of summing up the index of each item according to classification is shown in Table 2.

Sensory Quality Weights Sensory quality weight tofu 0.261 0.739 if 0.330 0.670 Bean sprouts 0.248 0.752 Kimchi 0.280 0.720 Seasoned seaweed 0.331 0.669

The sensory quality competitiveness of each product is calculated from the sensory evaluation results of each product of the sensory evaluation database (S50).

Sensory evaluation can be performed between one's own product and one or more third-party products, assuming that there is only one third-party product to be compared.

Table 3 shows the sensory symbol scores of the company's and other companies' products as a result of sensory evaluation.

Our product Third Party Products tofu 5.93 5.73 if 6.47 6.08 Bean sprouts 6.45 6.15 Kimchi 6.42 5.74 Seasoned seaweed 6.19 6.57

Sensory quality competitiveness of each product is calculated by the following equation.

Sensory Quality Competitiveness (%) = (Company's Sensory Functionality Score) / (Company's Sensory Functionality Score + Company's Sensory Functionality Score) * 100

Table 4 shows the market share information for each product in the market share database.

Own product (%) Other company's product (%) Etc(%) Market size (million won) tofu 27.2 8.6 64.2 169,342 if 15.5 34.7 49.8 38,425 Bean sprouts 24.5 4 71.5 46,274 Kimchi 7.6 31.6 60.8 60,017 Seasoned seaweed 5.2 7.6 87.2 244,782

The sensory quality competitiveness obtained in Equation 1 is a competitive index between the company's products and other companies' products.

Sensory quality competitiveness in terms of market share is calculated by the following equation.

Sensory Quality Competitiveness (%) = Sensory Quality Competitiveness (%) * (Market share of own product (%) + Market share of third party product (%)) / 100

If there is more than one third-party product to be compared, the third-party product is a combination of the product with the highest market share and the highest sensory preference among the third-party products.

For example, if the sensory acceptability of the third-party product A is 4.7 and the market share is 18%, and the sensory acceptability of the third-party product B is 6.3 and the market share is 10%, the assumed sensory acceptability of the third-party product is 6.3 and the market share is 18. Will be%.

Table 5 shows sensory quality competitiveness and converted sensory quality competitiveness calculated according to the sensory symbol scores in Table 3 and market share information in Table 4.

Sensory Quality Competitiveness (%) Converted Sensory Quality Competitiveness (%) tofu 50.9 18.2 if 51.6 25.9 Bean sprouts 51.2 14.6 Kimchi 52.8 20.7 Seasoned seaweed 48.5 6.2

The non-sensory quality competitiveness is calculated from the market share information for each product of the market share database, the calculated sensory quality weight value and the sensory quality weight value, and the calculated sensory quality competitiveness (S60).

Equation for calculating sales using sensory quality weight and non-ensory quality weight, sensory quality competitiveness and sensory quality competitiveness, and overall market size is as follows.

Revenue = [(Sensory Quality Competitiveness * Converted Sensory Quality Competitiveness) + (Sensory Quality Competitiveness * Sensory Quality Competitiveness)] * Overall Market Size

In Equation 3, if the sales are divided by the total market size, the market share is obtained.

Market share = (Sensory quality weighting * Converted sensory quality competitiveness) + (Sensory quality weighting * Sensory quality competitiveness)

If Equation 4 is summarized for the non-sensory quality competitiveness, Equation 5 is obtained.

Sensory Quality Competitiveness = [Market Share-(Sensory Quality Weighting * Converted Sensory Quality Competitiveness)] / Sensory Quality Quality

Therefore, it is possible to calculate the non-functional quality competitiveness from the equation (5).

Table 6 shows the results of calculating the sensory quality competitiveness from Equation 5.

Converted Sensory Quality Competitiveness (%) Sensory quality competitiveness (%) tofu 18.2 30.4 if 25.9 10.4 Bean sprouts 14.6 27.8 Kimchi 20.7 2.5 Seasoned seaweed 6.2 4.7

By using the calculated non-functional quality competitiveness, a relationship between sensory quality competitiveness and market share is derived (S70).

Substituting Equation 2 into Equation 4 yields the following equation.

Market share predicted value = (Non-functional quality weight value * Sensory quality competitiveness) + (Sensory quality weight value * (Original product market share + Existing third-party product market share) / 100 * Sensory quality competitiveness))

The market share of the company's own products and the market share of the other company's products can be obtained from the market share database, and the sensory quality weight value and the non-functional quality weight value are calculated as above, 6 is a linear equation between sensory quality competitiveness and market share forecasts, so a relationship between sensory quality competitiveness and market share can be derived.

Table 7 is a relation between sensory quality competitiveness and market share calculated through Equation 6.

Relation tofu Market share = 22.45 + 0.0934 * Sensory quality competitiveness if Market share = 6.96 + 0.1657 * Sensory quality competitiveness Bean sprouts Market Share = 20.88 + 0.0707 * Sensory Quality Competitiveness Kimchi Market Share = 1.81 + 0.1098 * Sensory Quality Competitiveness Seasoned seaweed Market Share = 3.14 + 0.0424 * Sensory Quality Competitiveness

Table 8 shows the market share by changing the competitiveness of sensory quality.

Sensory Quality Competitiveness (%) tofu if Bean sprouts Kimchi Seasoned seaweed 20 24.3 10.3 22.3 4.0 4.0 30 25.3 11.9 23.0 5.1 4.4 40 26.2 13.6 23.7 6.2 4.8 50 27.1 15.2 24.4 7.3 5.3 60 28.1 16.9 25.1 8.4 5.7 70 29.0 18.6 25.8 9.5 6.1 80 29.9 20.2 26.5 10.6 6.5 90 30.9 21.9 27.2 11.7 7.0

2 is a diagram showing the relationship between sensory quality competitiveness and market share for tofu. Referring to Figure 2, it can be seen that even if the sensory quality competitiveness changes, market share can be obtained.

Predict the market share and sales by product from the new sensory evaluation results (S80).

When sensory quality of the company's product is changed or sensory quality of other company's product is changed, a new sensory evaluation is performed, and the sensory symbol score, which is the result of sensory evaluation, is input.

In addition, after calculating the sensory quality competitiveness from the sensory symbol score in Equation 1 and substituting the relationship, the market share can be predicted, and the market share can be predicted by multiplying the total market size by the market share.

When sensory evaluation of a product family is conducted to derive a relationship between sensory quality competitiveness and market share of the product family, the sales of a specific product can be predicted from the sales share information of the product within the product family.

In addition, it obtains the actual market share and sales information for the product that predicted the market share, and manages the accuracy of the prediction system by comparing the two (S90).

3 is a block diagram illustrating a sales forecasting system through sensory evaluation according to an embodiment of the present invention.

Referring to Figure 3, the sales forecasting system through the sensory evaluation sensory evaluation database 100, market share database 110, purchase decision factor database 120, input unit 130, weight calculation unit 140, sensory quality Competitive calculation unit 150, market share prediction unit 160, it is composed of.

The sensory evaluation database 100 receives and stores a sensory evaluation result for each product from the input unit 130.

The market share database 110 receives and stores the market share and sales information for each product from the input unit 130.

The purchase decision factor database 120 receives and stores the result of the purchase decision factor for each product for the consumer from the input unit 130.

The input unit 130 receives sensory evaluation results for each product, market share and sales data for each product, and purchase decision factors for each product, and delivers them to each database.

The weight calculator 140 calculates the sensory quality weight value and the non-ensory quality weight value for each product from the information of the purchasing decision factor database 120.

The calculation is performed by classifying items of purchasing decision factors for each product into a sensory quality and a sensory quality and then summing the indices of the items according to the classification.

The sensory quality competitiveness calculation unit 150 calculates the sensory quality competitiveness for each product from the sensory evaluation results for each product of the sensory evaluation database 100.

Sensory quality competitiveness of each product is calculated by Equation 1.

The market share predicting unit 160 outputs the calculated sensory quality competitiveness output from the sensory quality competitiveness calculating unit 150, the previous market share information output from the market share database 110, and the product output from the weight calculating unit 140. Calculate the relationship between sensory quality competitiveness and market share by using the sensory quality weights and non-ensory quality weights, and predict the market share and sales by product from the results of sensory evaluation by new products.

The market share prediction value is calculated by Equation 6.

In addition, the market share prediction unit 160 predicts sales by multiplying the market share prediction value by the total market size.

In addition, when the market share prediction unit 160 calculates a relation between the sensory quality competitiveness of the product line and the market share by performing a sensory evaluation on the product line, the market share prediction unit 160 of the product Forecast sales.

In addition, the market share prediction unit 160 receives the actual market share and sales information for the product that predicted the market share, and manages the accuracy of the prediction system by comparing the two.

The sales forecasting method and the sales forecasting system through the sensory evaluation according to the present invention derive a relation between sensory quality competitiveness and market share from previous sensory evaluation results and market share information in consideration of non- sensory quality competitiveness. The market share can be predicted from the new sensory evaluation results.

In addition, a preferred embodiment of the present invention is for the purpose of illustration, those skilled in the art will be able to various modifications, changes, replacements and additions through the spirit and scope of the appended claims, such modifications and changes are the following claims It should be seen as belonging to a range.

Claims (13)

Constructing a sensory evaluation database from sensory evaluation results for each product; Calculating sensory quality competitiveness from sensory evaluation information for each product of the sensory evaluation database; Deriving a relation between sensory quality competitiveness and market share using the calculated sensory quality competitiveness and previous market share information; And Predicting the market share and sales for each product from the sensory evaluation results for each product using the relational expression Sales forecasting method through sensory evaluation, including. The method of claim 1, wherein before calculating the sensory quality competitiveness Calculation of sensory quality weight and non-ensory quality weight from purchasing decision information for each product Sales forecasting method through sensory evaluation, characterized in that it further comprises. The method of claim 2, Through the sensory evaluation, the sensory quality and the sensory quality weights are calculated by classifying the items of purchasing decision factors for each product into the sensory quality and the sensory quality. How to forecast sales. The method of claim 1, The sensory quality competitiveness is the following formula Sensory Quality Competitiveness = (Company's functional symbol score) / (Company's functional symbol score + other companies' functional symbol score) * 100 Sales forecasting method through sensory evaluation, characterized in that calculated by. The method of claim 2, Deriving a relationship between the sensory quality competitiveness and market share Following expression Converted Sensory Quality Competitiveness = Sensory Quality Competitiveness * (Market share of own products + Market share of other companies' products) / 100 Calculating sensory quality competitiveness converted by; Calculating non-sensory quality competitiveness from the market share information for each product, the calculated sensory quality weight value and non-sensory quality weight value, and the converted sensory quality competitiveness; And Deriving a relationship between sensory quality competitiveness and market share from the calculation result Sales forecasting method through sensory evaluation, characterized in that it further comprises. The method of claim 5, The non-functional quality competitiveness is expressed by the following equation Sensory Quality Competitiveness = [Market Share by Product-(Sensory Quality Weight * Converted Sensory Quality Competitiveness)] / Sensory Quality Weight Sales forecasting method through sensory evaluation, characterized in that calculated by. The method of claim 5, The relation between sensory quality competitiveness and market share is Market share = (Sensory Quality Competitiveness * Non-Sensory Quality Competitiveness) + (Sensory Quality Weighted * * Own Product Market Share + Others' Product Market Share) / 100 * Sensory Quality Competitiveness) Sales forecasting method through sensory evaluation, characterized in that calculated by. An input unit for receiving sensory evaluation results for each product, market share and sales information for each product, and purchase decision factors for each product; A sensory evaluation database configured to receive and store the sensory evaluation result for each product from an input unit; A weight calculation unit for calculating the sensory quality weight value and the sensory quality weight value for each product from the purchase decision factor information for each product; A sensory quality competitiveness calculation unit that calculates sensory quality competitiveness for each product from the sensory evaluation results for each product of the sensory evaluation database; And Between the sensory quality competitiveness and the market share using the calculated sensory quality competitiveness output from the sensory quality competitiveness calculation unit, the market share information for each product, the sensory quality weight value for each product output from the weight calculator and the non-ensory quality weight value The market share prediction unit that calculates the relational expression of and calculates the market share and sales by product from the sensory evaluation result of each product using the relational expression. Sales forecasting system through sensory evaluation, including. The method of claim 8, Market share database for receiving and storing the market share and sales information for each product from the input unit Revenue forecasting system through sensory evaluation, characterized in that it further comprises. The method of claim 8, Purchasing decision factor database for receiving the purchasing decision information for each product received from the input unit Revenue forecasting system through sensory evaluation, characterized in that it further comprises. The method of claim 8, The weight calculator calculates the sensory quality weight value and the non-ensory quality weight value by classifying items of purchasing decision factors for each product into sensory quality and sensory quality and then summing the survey values according to the classification. Sales forecasting system through sensory evaluation. The method of claim 8, The sensory quality competitiveness calculation unit is the following formula Sensory Quality Competitiveness = (Company's functional symbol score) / (Company's functional symbol score + other companies' functional symbol score) * 100 Revenue prediction system through sensory evaluation, characterized in that to calculate the sensory quality competitiveness by. The method of claim 8, The market share prediction unit Market share = (Sensory Quality Competitiveness * Non-Sensory Quality Competitiveness) + (Sensory Quality Weighted * * Own Product Market Share + Others' Product Market Share) / 100 * Sensory Quality Competitiveness) The sales forecasting system through the sensory evaluation, characterized in that to calculate the relationship between the sensory quality competitiveness and market share.

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