How does this British bank compare customer reviews across its branch network?
February 17, 2021
The banking industry is probably the area where customer experience has a central role to play.
Indeed, with the emergence of online banking, consumers increasingly need to feel close to their bank and in particular to their branch advisor. The experience perceived by your customers and especially their emotions is undoubtedly the most important point in the loyalty process.
In this article, we will see how a major English bank can compare customer reviews across its branch network using the Q ° emotion solution. Then we will see what are the benefits of this analysis.
1 / The preliminary steps
Before embarking on an automatic analysis of your customer comments, there are several parameters to take into account.
a. Choose the sources of advice to analyze
The first and arguably most crucial parameter is the correct selection of the opinion source to be analyzed. Indeed, depending on the type of business you use, the sources will be different. If you wish to learn more, we have detailed this process in a dedicated article: https://www.qemotion.com/en/blog/top5-best-sources-customer-reviews
In a bank, the preferred source is undoubtedly hot or cold customer surveys. However, for confidentiality reasons, in this example, we will be using reviews from open platforms, including Google Reviews.
b. Choose the main thematics
To carry out an excellent semantic analysis, it is necessary to define the relevant themes for our business. We have detailed this process in an article specific to semantic analysis: https://www.qemotion.com/en/blog/comparison-manual-or-automatic-semantic-analysis
The Q°emotion tool allows us to save time and automatically select topics relevant to our business, which is what we will do in the context of this article by selecting the Banking and Insurance category
Of course, if you want to define thematics specific to your company, it is quite possible to do so, you can contact us and we will prepare a tailor-made project to meet your needs.
c. Collect customer feedback from these opinion sources
Once we have selected our review source, all you need to do now is import the reviews into the cxinsights.io platform as shown in the screenshots below.
1. Select the chosen review source (here Google Reviews
2. Name the source and type the name of the chosen agency in the Google Place ID field
3. Choose the language in which the verbatim is displayed, the date and the associated satisfaction score if necessary
4. Automatically feed the project or not: you can ask the tool to automatically retrieve new verbatim on a regular basi
And voila, you just have to go to your project to observe the first results!
2/ The results
a. Emotional KPIs used
To properly interpret the results, we must first understand how the emotional KPIs used on our platform.
A temperature varying from -20°C to + 40°C defined by the main emotion detected in the speech
2. Emotional intensity
The average emotional intensity measured by the words used and the language codes (superlatives, emojis, punctuation
3. 6 primary emotions
The algorithm is able to identify the 6 primary emotions in speech namely: happiness, sadness, surprise, anger, disgust and fear (as well as calm
b. Global results
By observing the results of this analysis, we can see from the first glance that this banking group generates a lot of disappointment among its customers and in particular sadness with 52.2% of the 765 verbatims of the project which have it as that main emotion
Happiness, however, only reached 8.1% of total comments.
We must therefore seek to know where this sadness caused in customers comes from in order to implement actions to remedy it.
The Q ° emotion tool will analyze all of the verbatims and highlight the three main points of success but also of improvement.
For this English bank, we can notice that the ability to solve customer problems is particularly problematic with an emotional temperature of -3 ° C
By clicking on this precise point, it is possible to display all the verbatims that correspond to this theme and we realize that there are indeed complaints about customer service but also about the waiting on the phone
Now that we have been able to observe the global problems of this banking group, it is interesting to compare the different branches of the network to have a comparison between them and to identify any priority branches.
c. Comparisons between agencies
Thanks to the Q°emotion solution, it is possible to identify points of success and improvement agency by agency in just a few clicks
So, looking at the results of the Birmingham agency, we see that the ability to solve problems is rather a point of success of the agency unlike what we saw previously in the overall results. On the other hand, there is the negative aspect of the wait time that we detected in the comments. There is therefore an action to be taken to resolve this irritant.
To have a more complete comparison on the same screen, the creation of a benchmark between the different agencies in the territory is necessary.
We can thus see that the agency which generates the most happiness in the customer is the Bristol agency with 12% against 8.1% of the overall average.
Many indicators can be included in the benchmark such as stages of the customer journey, the themes chosen, or even, as can be seen on this screen, the satisfaction score
d. The benefits provided by Q°emotion
Thanks to Q°emotion, this English bank was able to identify new insights and obtain significant results.
The irritants could be reduced by 18% following the actions taken following the discovery of the results.
The initial intention rate due to long wait problems has been reduced by 30%
The NPS (Net Promoter Score) has been increased by 15 points
The time saved on verbatim processing is estimated at 2 hours per week
The new insights detected could be shared immediately and automatically with the various teams and agencies, on several access levels (managers, headquarters, etc.)
The emotional analysis offered by Q°emotion has allowed this bank to stand out from its competitors and strengthen the feeling of proximity to its customers.
If you want to find out more about the solution, you can discover our customer cases.
Test our semantic and emotional analysis platform for free by registering at cxinsights.io/sign-up
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