Before you get started, there are a couple of definitions that will help you get to grips with the tool.
A
Anomaly Alert: These can be set up in the workflow selection and are triggered if a response is outside of your pre-set parameters
C
Category: Themes are grouped together under predefined umbrella categories.
I
Impact Analysis: This is the breakdown of your NPS score and the impact that each theme currently has on your score.
M
Metadata: This is the data that is attributed to each response, it can tell you when the response was submitted, the location it came from etc. The metadata is also filterable.
N
Net Sentiment: This is our own metric, calculated by subtracting % of Negative theme mentions from % of Positive ones. The metric is a universal approach to measuring customer experience across various channels. It works on a scale ranging from -100 to 100.
Negativity Index: Measures the number of negative theme mentions within a set of responses based on your filter selection
P
Positivity Index: Measures the number of positive theme mentions within a set of responses based on your filter selection
S
Segments: Segments are variables or attributes of your comments. For example, you may have a segment named "United Kingdom". Selecting this would return all comments from customers based in the United Kingdom.
Sentiment (Negativity / Positivity): This is the number of Negative or Positive theme mentions per 100 responses.
Sentiment Distribution: Ratio of positive, neutral and negative theme mentions for a given number of responses.
T
Theme: Customer feedback is analysed and tagged with one or more themes. Each theme is characterised as either a positive mention or a negative mention.
Theme Structure: When Alchemer Pulse first analyse your data our tool creates a “theme structure” by examining what topics are consistently being mentioned. These topics are then added into categories that suit your business. From here we can tag comments with theme mentions.
