Module °Benchmark: Understanding the Tonality effect (Part IV)

Module °Benchmark: Understanding the Tonality effect (Part IV)

The Tonality effect: 

Definition: Impact on the average due to changes of tonality if no change in weights



Considering the assumption that the categories have kept the same weights, what are the impact(s) of the changes in tonality on the global average ?



Ex1: Imagine the following situation in a restaurant: 

(IMPORTANT : To simplify here, 1 comment = 1 category)

2 periods compared: N vs N-1


Category

E-index

N-1

E-index N

Volume

N-1

Volume

 N

Relative Weight N-1

Relative Weight N

Welcome 

30°

30°

1

1

1/4

1/4

Order

10°

10°

1

1

1/4

1/4

Food

40°


1

1

1/4

1/4

Bill



1

1

1/4

1/4

Average

20° 

(80/4)

10° ↘ (40/4)

4

13




Conclusion: Even if each topic weight has not evolved between N-1 and N, the global score has decrease  -10°! And that was due to the LOWER TONALITY of the category Food in the current period (that was the only change in the data). That is a Pure Tonality impact.

For each category:

Tonality effect = Delta E-index (of the 2 periods) x Relative Weight N-1


The same effect can be calculated for the Satisfaction averaged scores, Recommendation averages, etc.

In the graphics, the tonality effect is displayed at the center when the Details button is activated:
Tonality effect (T)







All rights reserved: Qemotion France SAS (2021)

Qemotion proposes CXinsights.io, a Customer experience solution: A SaaS solution that is capturing emotions from survey comments and webreviews and that is unlocking valuable insights.
The customer experience management platform showcases the emotions along your real customer journey, the interactions with the staff described by your clients etc.

You can therefore determine in an easier way the key action levers like:
- key insights and variations,
- main irritating points, 
- main enchantment points.

The platform helps you manage and prioritize the improvement actions you want to launch in order to improve the customer experience. As a consequence, you will increase loyalty and decrease churn levels.

The platform helps you also diffuse information into your organization with automated emotional alert systems, that transform your CRM into a Customer Enriched Emotion Management system (CEEM).

More information on: https://www.qemotion.com


    • Related Articles

    • °Module Benchmark: The Variance analysis (Part I)

      Introduction If you are following up your results on a Survey-basis / Monthly-basis/ Annual-basis, you will have one main need: explain why the results evolve between two periods (or two batches) and how to summarize evolutions. The idea is to use : ...
    • Module °Benchmark: Understanding the Mix effect (Part V)

      The Mix effect Definition: Impact on the average due to changes of both tonality and volumes in the current period   The Volume effect and the Tonality effect doesn’t explain everything because sometimes even if weights are equals (volume effect = 0) ...
    • Module °Benchmark: Understanding the Volume effect (Part III)

      The Volume effect:  Definition: Impact on the average due to the changes of relative weights if no change in tonality Considering the assumption that the customers have kept the same tonality / emotions / emotional index about each category they ...
    • Filter by satisfaction score, or by NPS profile

      For all projects that have included this option, you can filter on a score criterion: (Satisfaction score, Satisfaction score, Satisfaction response, NPS profile, or Recommendation score) according to the scores available and added as filters. With ...
    • The module °Benchmark

      Each user has the ° Benchmark module in the platform. This module allows you to create, name, edit, delete synthetic tables of results on horizontal and vertical axes with complete freedom.  No prior configuration is necessary to use this ...