Increase user satisfaction to make it easier for users to find the information they need

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In the previous article--User task completion analysis I seem to have missed an important question: Why do you want to analyze the user's task completion? In fact, every site analysis of the program and the model should have its purpose and significance, no one lost the value of analysis. So this article is to answer this question, but also as "make it easier for users to find the information needed" the end of the topic.

So here's a hypothesis: to make it easier for users to find the information they need to help them accomplish their intended tasks, and to effectively improve their customer satisfaction.

Factors influencing customer Satisfaction

Let's take a look at how user satisfaction is defined, based on the description of the American Customer Satisfaction Index model (ACSI, Anglo Customer Satisfaction Index), User satisfaction is the difference between the user's expectation of the product or service and the feeling of the product or service, the smaller the gap, the higher the satisfaction. For the information service-oriented Web site, users visit the site is expected to find their own needs of information, to complete the set of tasks (looking for information, shopping, entertainment, etc.), then how to measure the actual quality of the users received the site service level, and then speculate between the gap between them? For the user on the actual experience of the site, Can be reflected in the following 3 aspects:

Whether the user completes the expected task (whether the website passes)

A good experience in completing a task (maybe eighty or ninety points for a website)

Feel the creative or unexpected harvest (get additional points of opportunity)

Therefore, to ensure that the user to complete the expected task is the quality of the Web site pass line, can also be seen as the lifeline of the website. Does the task completion degree have such an important impact on customer satisfaction? We need to validate the above assumptions.

Degree of task completion and user satisfaction

In order to verify whether the task completion has a significant impact on the user's satisfaction, we need to collect the user's satisfaction on the website while the user's task is completed, so the data collected in the questionnaire survey on the user's satisfaction is useful. We can verify the effect of task completion on customer satisfaction by comparing the difference between the user who completed the task and the user with the unfinished task.

Here you can use a two-set independent sample T-test method, the sample data collected in the questionnaire are divided into two groups, one is the satisfaction rating of the unfinished task, the other is the satisfaction rating of the task users, we can think that these two sets of data are approximate to the normal distribution, And then compare the overall mean value of the two groups of samples for significant difference. (Perhaps you think this result is obvious, this verification is completely superfluous, then when I am superfluous, bored to pass the time.) )

First put forward 0 assumptions:

H0: μ1 =μ2

Then the collected sample data through SPSS or Excel data analysis function of the double sample mean T test, the process is not discussed in detail, or it is estimated that many users will immediately leave the site or even directly close the browser.

From the analysis results of SPSS, it can be seen that the completion of tasks and unfinished tasks of the user satisfaction scoring mean (above a table score value) can be seen, the completion of the user satisfaction mean significantly greater than the unfinished user. From the test results of the 95% confidence intervals in the following table, we can see that the significance probability of f test is 0.847>0.05, so we can think that the sample variance of the satisfaction of the task user and the unfinished task user is not significantly different, and the probability of T test is approximately 0. is less than 0.05, thus rejecting the 0 hypothesis, that is, the total mean of two samples is significantly different, and we can conclude that the user satisfaction of accomplishing the task is significantly higher than that of the unfinished task.

Through the analysis above, we verify the hypothesis that the user's task completion has a significant effect on improving the overall satisfaction of the users. So how to improve the user's task completion to improve customer satisfaction?

How to improve customer satisfaction

To enhance customer satisfaction, we may need to do a lot of things, from the overall to the details, need to be everywhere for the user's experience and feelings. Now that we have verified that the user's task completion has a significant impact on user satisfaction, we can start by improving the user's task completion. Here you can refer to my previous 4 articles on how to make it easier for users to find the information they need--optimizing the information architecture of the website, optimizing the internal search of the website, optimizing the website navigation design, and optimizing the relevant content recommendation.

These optimizations can improve the user's task completion from a general level, but obviously these are not enough, because the user's knowledge constitutes a difference, the user encountered problems will be different, so the previous article in the questionnaire when the user did not complete the task of why did not complete the task open question can play a role , we need to provide effective solutions to the different problems faced by various users (even individual users), which is why many websites set up FAQs and even online customer service.

So we first have to meet the user to visit the most basic expectations of the site-to complete their expected task, from this level to enhance customer satisfaction, the following is a simple sketch of my drawing, as the end of the article:

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Original address: http://webdataanalysis.net/web-quantitative-analysis/improve-customer-satisfaction/