What is the e-score model?
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Connecting the way we think to the way we process data efficently
A simple to use universal mathematical model to contain any type of emotional insights that structures data in a conversational way and creates additional level of granularity.
The principals of e-score
Use the way we think and talk to make questions easier to understand and easier to answer.
∴better questions = better answers
Use actual proven science for the rest!
We only use medical, behavioural, and technology science and best practice combined with the most popular business case management processes to deliver accurate reading of the emotional state of your customers and staff.
How e-score helped sitel and Waitrose
Working with existing metrics
Emotion-score provides additional insight to any data source
There is clear disparity between the insight from VOC and the main methods of scoring CX. Some have a poor correlation to the observable and some simply collect such a small layer of insight to make it much less actionable.
The most popular models
NPS has an obvious flaw - there is no opposite of recommend so it could never cover everything and its about the companies agenda not the customer. Also, its a construct (emotional dissociative future active hypothetical - technically) process habit so it failed more frequently than CSAT. And ridiculous as it sounds it has a series of quantum issues as well - don't ask!
WE THINK LIKE THIS
Our model of the world in all cultures is based around the idea ok. Our first thoughts are about how ok we feel when we wake up.
Things are more than ok less than ok. OK = 0 in maths not 1 - 10. What is a perfect 10...so the more we make or questions more compatible with the way people think the higher the probability you will get more constructive results providing actionable insight that is easy to understand.
The score in all these metrics do not reflect the verbatim comments at different levels of failed outcomes.
Factual problem confirmed by observation - All of them worked some times but none of them worked always.
CSAT was good because its about a feeling and proved much more accurate but it failed to differentiate between very unhappy customers and those leaving sometimes. The same was true of CES. Customer Effort Score is an almost perfect metric and it failed least. But it only looked at a small range of emotions. Trust Pilot also failed a bit as did the brilliant Happy or Not both of which failed in the same way but scored much higher for emotional satisfaction!
Why don't they work properly?
Add missing factor - More Than!!!
Back to the way we think about each experience in relation to OK! OK = ZERO
(remember WE THINK LIKE THIS)
Part 2 - The 5 value structure
We needed a structure for describe types of feelings and other experience elements and there was one we could adapt to provide a reliable human data emotional interface. This calibrates any channel data into insight relevant to the best and worst practice in the single experience which is practical insight. It will also match the practical insight you get from every other process or experiences because they all use the same model.
We are driven by a multiple of emotion states at the same time - the model needs to be able to contain that. Sometimes we do compare apples and oranges and we make a choice. This helps define the different feelings that your customers have about you and your experiences. Sometimes we are driven more by fashoin than comfort and sometimes the reverse is true.
This part of the process is vital it produces your emotional framework
The system will accurately calibrate the difference in value of different experiences.
You can describe any feeling. Satisfaction, effort, loyalty, anger, engagement, what ever is important to you. You can use your best and worst examples to calibrate and to develop best practice.
AI is now accessible to behaviouralists and it is now possible to analyse the micro-moments of experience....if you have a model that can tell you 3 things:
Is it true [On/Off]
Does it matter [Active / Passive]
How much [Degree]
These are the data items that are added to time cadence and other metrics to provide a Hi-Def picture of Customer Emotions. They allow for conflicts between drivers and explain them using common language like more than and very.
How angry is the customer....now e-score can tell you the value of your customers emotion!