How to Analyse Surveys for KPI data– Part 2

Last Updated: Friday, April 12, 2013 by Johnathan Briggs

https://www.targetdashboard.com/nlimages/CSI-Exp-Boston.png

Over the past few months, we have had some clients who wish to get KPI information from customers surveys. Collecting this data and converting it into understandable KPIs can be tricky.Many companies often use surveys to get accurate KPI information. So, I thought I would show you how to use dashboard software to collect and visualise KPI information. The previous part of this guide showed you how to:

· Collect and Arrange your KPI data to be understood by dashboard software

· Calculate the Customer Satisfaction Index (CSI) of your survey results.

In the second part of this guide on analysing your surveys for KPI data, you will learn how to do the Net Promoter Score calculation (another important statistic learned from surveys) and how to use dashboard filters to show statistics for different categories in your KPI, as shown in this table.

https://www.targetdashboard.com/nlimages/SurveySample.png

4. The Net Promoter Score Calculation

The Net Promoter Score (NPS) KPI is similar to the customer satisfaction index, but aims to show the overall company progress, rather than how people feel about aspects of the company.

As I mentioned in my previous post, the CSI score for the above table shows the overall satisfaction of your customers either at experience level or store level.

Instead of calculating a score from multiple questions (speed of service, communication), Net Promoter Score calculation from just one question, regarding the likelihood of the customer recommending the company to others. The question often looks like this:

https://www.targetdashboard.com/nlimages/NPSQuestion.png

Here, each number on the scale is assigned a status:

  • 1 to 6 – Detractors, who have a negative opinion of the company
  • 7-8 – Passives, who are undecided
  • 9-10 – Promoters, who have a positive opinion of the company and would recommend it to others

To get your NPS, simply find the percentage of responses that are detractors and promoters, and subtract the % detractors from %promoters. This percentage is your Net Promoter Score Calculation.

As a formula, this looks like:

((Promoters/Total Respondents) x100)– ((Detractors/Total Respondents) x100)

While you have to be wary of using percentages in calculations, this one works because the percentages are equally weighted. The NPS can therefore be anywhere from -100% (everyone is a detractor) to 100% (everyone is a Promoter). In some ways, the NPS KPI is more powerful a KPI than CSI, as it shows how your company’s reputation and trust is progressing in the eyes of your customers.

Now that we have seen how to get both both your CSI and NPS KPIs from survey responses, we can now visualise this in a survey dashboard to compare and break down the data.

4. Use Filters to compare your Survey Results

Survey data is very useful because you can compare information from different parts of a company. For the CSI scores in particular, you can potentially compare CSI for each individual stores, to see which needs improvement. Breaking down your data in this way is very easy with an application like Target Dashboard, which filters your data in a few clicks!

https://www.targetdashboard.com/nlimages/Filter-Editor.png

To show you how to visualise and drill into your survey data, I’m going to concentrate on CSI score, as the NPS score is a single display from a single survey question, and easier to display. We need to be able to show the overall CSI per store, as well as for each aspect of customer service.

With your data imported into your Dashboard software, just create a calculated column which contains the CSI formula. With Target Dashboard, the formula for creating a CSI score is,

wqs(column ID for Very Poor:10,Poor:20,Average:60,Good:80,Excellent :100)

Once you have this entered, create a chart with the CSI data shown.

https://www.targetdashboard.com/nlimages/CSI-Exp.png

Here, the CSI data for Experiences is displayed, as this is the highest-tiered category in our table. In order for us to see the CSI scores for the store branches, we have to calculate them using the experience CSI scores.

Now, if we apply a filter to this table, we can see the experience CSIs for a particular store, such as Boston.

https://www.targetdashboard.com/nlimages/CSI-Exp-Boston.png

From this chart, we can see that in Boston, every experience criteria is higher than the overall CSI for each experience. What the filter has done is discarded the data associated with the LA and New York stores, and recalculated the CSI using nothing but Boston’s data.

Being able to filter out the CSI scores means that you can compare each city against each other in a different graph, and spot where improvement is needed.

But, this is just one perspective of the CSI data. What we can also do is show the CSI scores for all of our stores.

https://www.targetdashboard.com/nlimages/CIS_Store.png

This is the exact same data as the earlier chart, but shown in a different way. This lets users spot data trends that were hidden by the previous chart, such as LA’s comparatively bad performance to Boston’s.

We can further break down this Store data in the same way as the Experience data. Let’s show just the speed of service CSI for each store.

https://www.targetdashboard.com/nlimages/Filter-SpeedofService.png

LA clearly needs to be a little bit quicker!

Though I’ve shown you how filters can help you see your CSI KPIs in different ways, your NPS score can also be shown in your survey dashboard. This just requires a table and score column, like the CSI data table. No filters are needed, as the score is measured over just one set of data with no categories.

You can get more tips on displaying your data in a dashboard report by reading our best practice guide.

Survey Data is easily analysed using Filters!

Surveys are used by companies to collect KPI information which can’t be measured internally. Collecting this data may not be that difficult, but understanding it is tricky. Using a KPI dashboard application, you can visualise these survey KPIs and make better decisions from them. This quick guide to analysing survey data has shown you how to:

  • Design your questionnaires to be collected by a computer , saving you time entering the responses manually.
  • Arrange your survey responses in a data table , so that dashboard software can understand it.
  • Calculate the Net Promoter Score and Customer Satisfaction Index, as these are common, powerful KPIs that show the progress of your company.
  • Use filters to see different sets of data in your survey dashboard.

By following these tips, your surveys will become useful sources of information which you can make better decisions from.

To make analysing your surveys even easier, some applications such as Target Dashboard allow you to filter data automatically, as I have shown you in this post. To see how easy these tools are to use, sign up for a free trial now!