AI-driven feedback analysis empowers Kia to discover insights from more and more data sources. 

Cosmin Donose, Assistant Manager CX Intelligence @ Kia Europe

As the European headquarters in the automotive industry, Kia Europe is committed to delivering products and experiences that align with the specific needs of its local customers. At first, their CX Intelligence team started leveraging Caplena to provide a centralized overview of the thousands of feedback collected among their European dealers. Today, Kia analyzes a growing number of data sources, including App store reviews for competitive benchmarking and website feedback. Discover their journey.  

“

AI-driven feedback analysis has transformed how we understand customer sentiment at Kia Europe. By swiftly processing and categorizing thousands of open-ended responses, Caplena helps us identify key trends and improve the overall customer experience across our European markets. For example, we can now analyze app store reviews and perform competitor benchmarking of car charging services. This allows us to stay ahead of industry trends and better align with consumer expectations."

Cosmin Donose

Assistant Manager CX Intelligence

Highlights 

• Kia already centralizes 6 feedback sources and more to come. 

• 14 subsidiaries and multiple departments in Europe (CX Intelligence, Electrification, Ownership Experience) rely on Caplena for insights. 

• Topic-level sentiment is a “game-changer”: with Caplena, Kia can identify the precise levers of customer satisfaction. For instance, they discovered that for new Electric Vehicle buyers, the “handover” moment is a strong driver of satisfaction.

The Challenge 

1. Creating a Voice of Customer overview across 14 markets 

Kia’s main challenge was analyzing feedback from 14 markets in different languages. Kia was gathering customer feedback from dealerships and was making it available for dealers to read. As Kia was sourcing 150k+ comments per year, the opportunity to get a centralized overview was clear, but Kia lacked the tools to achieve it.

2. Internal solutions were falling short 

They tested different solutions internally. They tried using Google Translate and creating word clouds in Tableau. Word clouds were nice, but did not provide quantifiable information. Then using Monkeylearn, Kia experimented with sentiment analysis. While this was a good start, Kia wanted to understand the context and the topics behind their 150k+ comments to dig deeper.

3. Translations and sentiment analysis were prone to error 

Translation accuracy was also a challenge. Looking into verbatims, sometimes the sentiment was correct, but the translation was wrong (or the other way around). In addition, cherry-picking 2-3 verbatims was not enough to generalize, and the resulting decision-making was rightfully called into question. Kia needed a robust solution to back their business decisions with reliable data.  

Transition to Caplena 

In their search for a more reliable and scalable solution, Kia evaluated Caplena.

An AI platform one can understand, control, and trust

Their main priority was to find a tool they could trust to give correct topic-level analysis. As Caplena offers transparent documentation about its AI model, and as its interface allows to control and fine-tune the AI output, it gave Kia confidence in comparison with other solutions which can sometimes feel like a black box.  

“Killer features” 

Two features stood out and convinced Kia that Caplena was the right solution for them. 

• Driver-Analysis came as a perfect way to pair quantitative KPIs (like NPS) to their qualitative data (open-ended responses) to identify which topics drive satisfaction up or down and quantify their positive or negative impact.  

• Kia Europe found AI summaries to be very useful to serve quick insights when looking for a specific answer (for instance: is there something happening in the UK regarding waiting times for delivery?).  

Implementation & Results

1. A successful Phase 1 project 

As a first phase, Kia integrated the Dealership Sales and After-Sales satisfaction surveys. This allowed them to finally get a unified view of the 150k+ open-ended responses collected across their 14 markets. They were able to unlock topic-level sentiment analysis, identify drivers of satisfaction, and successfully engage dealers with real-time dashboards. For the first time, Kia was able to drill down to the Dealer level or use internal data to segment the analysis. Also, the national users appreciated being able to automatically translate a verbatim or read it in its original language at the click of a button.

2. Gaining insights into strategic segments: the case of EV buyers

Segmenting by type of car engine allowed Kia to gain insights into the unique needs of Electric Vehicles (EV) buyers.

As the below chart reveals, EV buyers have higher expectations. Their survey responses more often mention the car in general, customer & vehicle service, and also the vehicle's interior compared to other car owners.

Especially, using the driver analysis, they discovered the handover of an EV car is a very important moment in the EV car buyer journey. Using these insights, Kia has implemented a specific handover process for the EV9 – Kia’s premium EV model in a few markets and named dedicated call center agents to address the higher expectations of EV customers.

Before, Dealers were not sure how to approach EV buyers. Using Caplena, Kia helped dealers understand their specific needs, and was able to increase the NPS of EV buyers.  

3. A single place to analyze feedback

After this successful project, Kia had confidence they could analyze more data, especially as creating new projects can be done on the spot, without the pain of preparing and transferring the data. Here are some examples:  

• By analyzing Electric Vehicle charging apps (including competitors’) on the App store and Google Play store, Kia discovered a need for an advanced EV route planner that is connected to the car's state of charge, and can recommend a specific route with charging points. Kia noted that some competitors had such a feature, and the Product team started to work on it. 

Using driver analysis, Kia discovered the Route Planner feature has a +0.3 stars net positive impact on overall review scores for EV charging apps.

• Upon reviewing feedback from their website and configurator, Kia identified that prospects need a more effective way to visualize the cars they are configuring. As a result, the digitalization team is actively working on enhancing these aspects of the user journey. 

So what's next?

Among the next projects on the CX Intelligence department roadmap, Kia will focus on Online Reputation Management. They plan to analyze Google My Business reviews. Their goal is to equip Dealers with tools to proactively manage their Google My Business pages across Europe. However, such tools do not include advanced feedback analysis. This is where Caplena comes in, so Kia can centralize and dig deeper into Google reviews.  
 
Kia is also planning to integrate in-app surveys, as they will collect feedback on the overall app experience.  
 
Kia is leveraging customer feedback from the car experiences to refine and enhance the overall ownership journey. By analyzing real-world insights, the manufacturer aims to better understand customer needs and expectations, driving continuous improvements in their products and services.

Conclusion

Before Caplena, Kia was missing data-backed confirmation from the market.  
 
Now Kia can validate assumptions, discover new insights backed with quantitative analysis, and make business decisions with confidence. This process facilitates alignment with stakeholders and top management and gives ground to bigger projects to meet the needs of customers.