Analyses are at the heart of Ipiphany. They store, organise, and present the insights that are found within your data. 

Analyses come in all shapes and sizes but a popular type in Ipiphany is called a Painpoints Analysis. A painpoints analysis is simply a list of specific problems that customers are experiencing. When painpoint analyses are done well and frequently they are very powerful tools for business improvement.

The following is a step by step process for creating a simple Painpoints analysis.

2.1 - Create the analysis

From the Ipiphany home screen click the 'New' button and select 'Analysis'

Choose the 'Painpoints Analysis' type 

Select a dataset - for this example select the 'Airline Reviews' dataset which contains more than 8000 airline customer reviews

Give your analysis a name and click CREATE ANALYSIS. Don't worry about changing the metric, filter, or project at this stage.

2.2 - Find and add painpoints to the analysis

When the analysis is created you are displayed the Insights > Categorize screen. This screen is the easiest and fastest way to build up a list of insights (painpoints in this example) but remember that this is just the start. Ipiphany contains many other powerful tools for extracting insight.

On the right side of the screen are all the things that Ipiphany has found in your text data. For this example, we will look at the default 'THEMES' which are colored by 'Impact'. You should see the following:

'Themes' are dynamically generated groupings of records that mention the same idea. By coloring them by Impact (a measure of the effect they are having on NPS in our example) you can quickly identify painpoints highlighted in red. 

Now all you need to do is drag the red themes into the analysis list area to create them as insights. If two or more are the same just drag them onto an existing insight and Ipiphany will intelligently combine the results.

2.3 - Tidy up your painpoints

At this stage, you have discovered some painpoints but they are poor quality. It is important to do the work to tidy up your painpoints so they can be quickly and efficiently used by relevant business stakeholders.

A good quality insight needs to have a few things:

  • To be well named
  • To have a detailed description that establishes cause and effect
  • To have at least 1 key example

Let's take our painpoint 'Connect Flight' and see if we can tidy it up.

Hover over the 'Connect Flight' painpoint in the list and click the 'Preview Insight' button to bring up the preview panel.

Now click 'EXAMPLES' to see the records that mention 'Connect Flight'.

If you read through some of these examples you will see a range of causes and effects of customers missing connecting flights. Based on this new understanding you should be able to tidy up the name of the painpoint and create a high quality description.

Click on the name of the painpoint and update it:

Click the 'Show more' arrow of the painpoint and add a description

Find an example that you think exemplifies the painpoint in the list of examples and click the small 'tick' icon to set it as a key example



Now go ahead and do this for the other painpoints in your analysis.

Done? Good, now on to:
Step 3 - View and share analyses

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