The WPMU DEV Survey

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Survey Maker | Design Surveys With #1 Online Survey Creator

Free Online Survey Maker | Fynzo online survey builder makes the process of creating online surveys easier than ever before.

Visit Website: https://www.fynzo.com/survey

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Net Promoter Score Software | Create NPS Surveys | Fynzo

Fynzo brings to you free online NPS survey software. Now create NPS surveys easily. Join Fynzo for a free trial. No credit card required.

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Net Promoter Score Software | Create NPS Surveys | Fynzo

NPS surveys can be drafted easily, all you need to do is signup for Fynzo Survey’s NPS Survey Platform and we will do the rest for you! The responses can be easily viewed on the form. You can include the following questions in your survey.

For more info visit: https://www.fynzo.com/survey/lp/nps-software

#nps survey software #net promoter score software #free online nps survey software #create nps surveys #nps survey platform

Best NPS Software | 5 Best NPS Software | Fynzo Survey

NPS is a metric through which you can measure how much a customer is willing to recommend your product or services to the people he knows like friends and family members. It is a measure to see how well you are doing with your business and how much your customers are satisfied. You know that you are in the right direction when your Net Promoter score is higher than that of your competitors or is higher than your previous one. The best way to create and run a Net Promoter Score survey is to use NPS software. The software will help you create, share, analyze, and calculate NPS.

The best NPS software today

Getting NPS has become crucial for all businesses to do a better job in serving the customers and to measure competition. So, a software with user friendly features to measure NPS is very important for a company. Some of the best NPS software are:

• Fynzo Survey
• AskNicely
• Zonka Feedback
• SurveySparrow
• SurveyMonkey
• Delighted
• Promoter.io

Best NPS software #1 : Fynzo Survey

Fynzo provides a powerful and advanced suite of software that fulfills your different business needs. Their support team is available around the clock for hearing out their customers and helping them utilize the software to the fullest.
Fynzo offers an NPS Survey tool, which comes with modern features and multiple customization options. Given below are the key features of the Fynzo Survey:
Comes with an easy survey builder interface.
Create multiple question types including NPS, Likert scales, and smiley, star ratings, and many more.
Implement advanced survey features like jump logic, piping, and custom variables, and many more.
Share surveys on different social media platforms, send them via email, embed on your website, or circulate them with the help of QR codes, etc.
Analyze the reports received in different formats including cross-tabulation, trend report, and many more.
Schedule reports on multiple emails.
Collaborate with your team members while creating surveys, analyzing reports, etc.
Personalize your surveys by adding your organization’s logo, background, theme color, etc.
Download the data received in Excel, CSV, SPSS, pdf, and many other formats or export to Google Sheet.
Integrate with the apps you love including Zapier, Google Analytics, Slack, Facebook Pixel, and many more.
Fynzo Survey comes with an online survey app that supports on Android, iOS devices. You can create surveys, share them, and view/download the results with the mobile app too.
Grab geolocation while taking the surveys in the field with mobile App.
On top of all these amazing features, Fynzo Survey pricing starts at only $17 a month
These advanced features of this survey software along with its pocket friendly pricing plans make it #1 NPS builder.

Best NPS software #2 : AskNicely

With AskNicely, you get to add logic-based questions for your survey. The software makes your analysis better and easier with the help of individual divisions like channels, products, and many more. It gives scope for sharing the surveys by embedding the link in websites, email, and text messages. The surveys can be integrated with Intercom, Hubspot, Zapier, and others. It has a number of support networks as well making it a place in one of the best NPS software. If you want, you can also have a look at AskNicely alternatives here.

Best NPS software #3 : Zonka Feedback

Zonka Feedback is an interactive survey option between the business and the customers. The questions are so framed that the respondents need to give a reason behind their chosen option. This feature helps you to learn about customer satisfaction in a more detailed manner. Sharing surveys is easy as it has multiple channels like QR code, embedded links, and other networking solutions. It is not free to use software though you can opt for a free trial period of 15 days.

Best NPS software #4 : SurveySparrow

Surveys conducted under SurveySparrow can be integrated with any Google applications. It provides scope for multiple access to the surveys. Questions framed for the survey can be divided or branched questions in this software. Data analysis is viewed in an easily understandable method to get better results and better development. Survey Sparrow is also very affordable with a number of features that are beneficial and that one of the best NPS software offers.

Best NPS software #5 :SurveyMonkey

SurveyMonkey is also amongst the best NPS software that many businesses prefer using. It has more than 100 question templates that fit your requirements in any scenario. Surveys can be integrated with Microsoft Teams, Zapier, and almost every other platform. Through its subscription price is a bit in the higher range, it has still managed to give customers what they wanted. You can choose SurveyMonkey if you want your surveys to be efficient and engaging to your customers. If you are currently using SurveyMonkey and would like to make a switch, we have collected a few SurveyMonkey alternatives here.

Best NPS software #6 : Delighted

Delighted comes under the list of best NPS software because it is extremely easy to use for everyone. Delighted has the feature of filtering responses and thus helps to accurately analyze the information collected whatever is necessary to the business. These surveys can also be integrated almost with every platform like Zapier, Salesforce, Intercom, and many more.

Best NPS software #7 : Promoter.Io

As the name suggests, it is a great way for your products and services. You can use your logo in the survey and customize it as you require. Promoter.Io is also on the pricier side. Surveys can be shared through SMS, emails, and website and its integration options are favorable by many as well. Help and support are available via SMS, emails, and chat.

Conclusion :

You can choose any of the software from this list of best NPS software as all of them are very user friendly and have great reviews. It has to be kept in mind that a low Net Promoter score like 1 to 5 in a total of 10 can hamper your reviews and sales. So, you need to be careful that your customers are not so much dissatisfied that you get more of these low ratings. Whereas scores like 8 to 10 out of 10 is a pretty impressive score and do a great deal in uplifting the business image. So, the target should always be to achieve high ratings so that your overall score is satisfactory and more than the competitors.

**Original Source: **7 Best NPS Software To Track Customer Satisfaction

#nps survey software #net promoter score software #free online nps survey software #create nps surveys #nps survey platform

Exploring survey data with the pewmethods R package

The methods team at Pew Research Center regularly works with survey data in R, and we’ve written many functions to simplify daily tasks like cleaning, weighting and analyzing data. The pewmethods R package, available to the public on the Center’s GitHub page, evolved as a way to reuse and maintain this sort of code and share it with other researchers around the Center. Since many of the problems that these functions were designed to solve are not unique to our own projects, we’ve made the pewmethods package publicly available for other researchers who might find the functions useful, too.

This post goes through the process of exploring survey data in R using pewmethods, including recoding and collapsing data and displaying weighted estimates of categorical variables. Throughout these examples, I’ll make extensive use of the tidyverse set of R packages, which is a great tool for data manipulation that we highly recommend using along with pewmethods. You can learn more about using tidyverse in this blog post.

The example dataset

The package includes a survey dataset called dec13_excerpt, which contains selected variables from a survey conducted by Pew Research Center in December 2013. The data contains demographic and some outcome variables, as well as survey weights. You can learn more about the details by calling ?dec13_excerpt.

> dec13_excerpt
# A tibble: 2,001 x 14
   psraid cregion q1    q2    q45   sex   recage receduc racethn2
    <dbl> <fct>   <fct> <fct> <fct> <fct> <fct>  <fct>   <fct>   
 1 100005 Northe… Disa… Very… Disa… Male  55-64  HS gra… White~H…
 2 100007 South   Appr… Very… Appr… Fema… 55-64  Coll+   White~H…
 3 100019 South   Appr… Very… Appr… Fema… 55-64  Some c… Black~H…
 4 100020 Midwest Appr… Not … Appr… Fema… 65+    Some c… White~H…
 5 100021 Northe… Appr… Very… Appr… Fema… 65+    HS gra… Black~H…
 6 100023 Midwest Don'… NA    Disa… Male  45-54  HS gra… White~H…
 7 100027 Northe… Appr… Very… Appr… Fema… 65+    Some c… White~H…
 8 100031 South   Disa… Very… Disa… Fema… 55-64  Coll+   White~H…
 9 100034 Midwest Disa… Very… Disa… Fema… 55-64  Some c… White~H…
10 100037 South   Disa… Very… Disa… Male  35-44  Coll+   White~H…
# … with 1,991 more rows, and 5 more variables: party <fct>,
#   partyln <fct>, weight <dbl>, llweight <dbl>, cellweight <dbl>

Most Pew Research Center survey datasets, as well as those from other organizations, will have one or more variables for the survey weight. This weight is crucial for obtaining correct numbers from the survey data, since it allows the sample to resemble the overall U.S. adult population more closely. In dec13_excerpt, the weight variable is simply called weight, and we’ll be using it to look at weighted cross-tabulations of other variables in the dataset.

Cleaning and editing survey data

Let’s look at some outcome variables:

> names(dec13_excerpt)
 [1] "psraid"     "cregion"    "q1"         "q2"        
 [5] "q45"        "sex"        "recage"     "receduc"   
 [9] "racethn2"   "party"      "partyln"    "weight"    
[13] "llweight"   "cellweight"

We see three variables that look like survey outcomes: q1, q2 and q45. Let’s take a look at q1. As dec13_excerpt was originally stored as an IBM SPSS file, we can use the get_spss_label() function to view the label associated with q1. For Pew Research Center survey data, this will either be the question wording or a brief description:

> get_spss_label(dec13_excerpt, "q1")
[1] "Q.1 Do you approve or disapprove of the way Barack Obama is handling his job as President?"

q1 is an Obama approval question, so let’s run a quick table:

> tablena(dec13_excerpt$q1)
dec13_excerpt$q1, a factor
                  Approve                Disapprove 
                      839                      1042 
Don't know/Refused (VOL.) 
                      120

The tablena() function in pewmethods works the same way as base R’s table() function, except that it tells you the specific object you just ran a table on (along with its class), and will always display any NA values rather than hiding them by default.

Now let’s look at q2:

> get_spss_label(dec13_excerpt, "q2")
[1] "Q.2 Do you [approve/disapprove] very strongly, or not so strongly?"

q2 is a direct follow-up to q1. After asking respondents whether they approved or disapproved of Obama, we asked them whether they did so very strongly or not so strongly. So q1 and q2 are best analyzed together.

We can do this by creating a new variable, which we’ll call obama_approval_scale, that combines the two into a single variable with the categories Approve very strongly, Approve not so strongly, Disapprove not so strongly and Disapprove very strongly, as well as Don’t know/Refused (VOL.). The fct_case_when() function is a straightforward and readable way to create that combined variable. fct_case_when() is a wrapper around the case_when() function from dplyr that coerces its output into a factor whose levels are in the order that they were passed into the function.

#statistics #methodology #surveys #r #survey-analysis #data analysis