IPA Demand Analysis Case: How to understand the user’s demand and expectation?

During the subsequent iterative optimization of the product, the user experience and user needs are important reference factors, and the effective analysis of user needs helps to drive product subsequent users. In this article, the author introduces IPA, which is important – the degree of expression, and combines the actual case to summarize the IPA demand analysis method, let’s take a look.

I, background

Suppose your company plans to experience optimization of the product, collect some of the problems facing the current user experience by depth interview, but too little sample size is too small enough to support version iterative transformation decisions, hoping to collect more through the questionnaire Feedback, judging the priority of the experience optimization.

Second, questionnaire design

This stage is slightly interview to collect the process of optimizing “experience factors”, directly enter the questionnaire design.

The purpose of the questionnaire is to learn the priority of the experience optimization, so the quality of the “experience factor” in the A product and two problems, as shown below.

About the level: What do you think is the following elements of the product to experience A products? Experience experience: How do you experience the following elements experience during the A product?

¡ø a product experience questionnaire

Questionnaire table

Scored a 7-point scale.

Abroad: 1 point (very unimportant), 2 points (not important), 3 points (not important), 4 points (general), 5 points (a bit important), 6 points (important), 7 points (very important . Experience experience: 1 point (very unsatisfactory), 2 points (unsatisfactory), 3 points (not satisfied), 4 points (general), 5 points (a bit satisfied), 6 points (satisfied), 7 points (very satisfied) .

2. Questionnaire

Questionnaires are issued by Tencent to ask for users who have a product experience with A products, and collect 145 valid questionnaires.

Note that all the questionnaires that need to be removed to avoid interference to the overall sample. If the factor analysis is followed, Gorsuch (1983) suggested that the number of quantities should be 5 ~ 10 times the number of questions, and the sample is greater than 100 (Qiu Haozheng, 2000).

¡ø survey results

Ok, Questionnaire Collection & Clear, the following can enter the key content of this article, data analysis link. Briefly introduce the IPA analysis method used.

Third, IPA introduction

Important – Importance-Performance Analysis, referred to as IPA, is often used to understand the subjective feelings of customers or services provided by the company.

Through the IPA analysis results, it is known that the company’s goods or service attributes are located in which quadrant is located, assist in understanding the advantages of goods or services; finding the priority of the product or service attribute improvement, will be limited in the customer first The attribute level of attention is taken to enhance the company’s performance.

The coordinates are based on the basis of the assessment and satisfaction, and draw a two-dimensional matrix pattern and divided into four quadrants.

Icon limit definition

¡ø IPA four quadrant

The first quadrant (a): indicates that the degree of importance and performance are high, and the attributes must be docked in this quadrant should continue to maintain (the second quadrant (b): indicates that the importance is low and the degree of expression is high. The attributes falling within this quadrant; the third quadrant (C): indicates that the degree of importance and the degree of expression are low, and the attribute in this inexpensive is lower (low priority); fourth quadrant limit (D): It indicates that the degree of importance is high but the degree of performance is low, and the attribute in this inexpensive is that the supplier should strengthen the key point of improvement.

2. Draw a step

Drawing tools You can use Excel or use SPSS or other tools. As the X-axis, the performance is as a Y-axis; through the split, the coordinate axis forms four quadrants, and the split is indicated by all questions, one average importance, one average expression.

Fourth, IPA analysis

1. Step 1

First, the average calculation is performed, using the Excel calculation of the average function = AVERAGE (), and the result is kept 2 decimal.

A post-application formula is calculated to obtain an average of other single questions.

¡ø Calculate the average of each question

2. Step 2

Squiring data to new Sheet facilitating drawings, seeking overall average importance and flat expression, also use = average () calculation.

The average importance = 5.55, the average performance = 5.39.

¡ø Calculation Importance & Experience Average

3. Step 3

Drawing the experience feature distribution scatter plot, first box selection requires the data, the left data is the x-axis, and the right data is the Y axis. Then select Insert and select a scatter plot.

¡ø Insert a scatter plot

At this time, you can get the “A product experience element” distribution.

¡ø A product experience feature distribution map

4. Step 4

Next, it is necessary to split the point to form four quadrants in the coordinate axis. Click on the corresponding x-axis and Y axes in the figure, depending on the importance and experience sensing average, set the coordinate axis value.

As shown in the figure below, in order to clearly show, you can take the table line together. ¡ø Set an X-axis coordinate

¡ø Set the Y axis coordinate

¡ø Remove icon grid

5. Step 5

Finally, the distribution point is visualized, and the data of each coordinate corresponds to the feature name. First select any point, right click to add a data label.

¡ø Add data label

At this time, the factor point will appear the data corresponding to the Y axis, which is not the effect of our ultimate needs. You can select any right click to set the data tag format.

¡ø Set data tag format | Source: Guofu homemade

Check the value in the cell, then select the cell that needs to match, click OK.

¡ø Set the value in the cell-1

Finally, you need to remove the Y axis, display the boot line, you can get the following effects.

¡ø Set the value in the cell-2

6. Step 6

Take a little more beautiful, you can interpret the data at this time.

¡ø IPA analysis results

As can be seen from the figure, the results of the survey have fallen in the D-area (improved important) in the picture: the elements of the page opening speed and data security; the C area (the secondary improvement) is: customer service service attitude, Customer service speed and processing BUG timely.

The priority of processing can be planned according to the D area> C area> A area> B region. If there is no DC area, perform an optimization of the A area, there is an opportunity to bring surprises to users.

Five, summary

Doing any research work, the core goals are discovered, and the improvement direction is found through the problem. Therefore, IPA is simple and easy to use than other analytical methods, and can be applied quickly in daily work of product managers, user research, designers.

This is an analytical method I have recently used to study the research. Data is collected for real-world research.

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