1800 Aggregated Swedish reviews about Budbee – Our analysis

All the Way home – We analyze customer feedback on logistics startup Budbee

As e-commerce grows ever more ubiquitous, it makes sense that new players will emerge to capture new and growing opportunities. Budbee was founded in 2016, and at time of writing focuses on the Nordic cities Stockholm Gothenburg, Malmö, Helsinki and Copenhagen. Budbee position themselves as a tech company providing last-mile home delivery that’s smooth and hassle-free.

Budbee handles deliveries to major nordic cities | Image-Source

Like many other industries, e-commerce players are increasingly betting on customer choice – whether that customer is a sending e-retailers or a receiving consumer. As such, it’s more important than ever to keep your finger on the pulse regarding what your customers think.

In order to look closer at how customers regard a logistics company like Budbee, we took 1800 Swedish reviews from trustpilot.com and ran them through the Gavagai Explorer.
The analyzed data is in Swedish, but you can check out the results here in the Dashboard!
Visit gavagai.io/blog for more analyses like this in your own language.

This graph from the report shows the 15 topics that occur most frequently (height), as well as the sentiment we measured around each topic (expressed as % of red/green within each bar)

Here’s what we could observe

Budbee’s customers most often mention terms related to speed. This, in and of itself, does not necessarily have to be positive (e.g. for statements like “anything but fast”) but as the report shows, sentiment expressed in this case is overwhelmingly positive!

Mentions of Budbee as easy are both frequent, and indicated as the main driver of positive sentiment. In the analysis, the topic Easy includes terms like “smooth”, meaning this finding quite strongly indicates that Budbee is delivering on its promises.

Digitally adjacent aspects such as information, choice/re-booking, and tracking are mentioned frequently, and all of these topics have more positive mentions than they have negative mentions. As these are defining characteristics for a logistics-tech company, it’s a good sign that they are well-regarded and mentioned often.

Staff seems to be an area for potential improvement. A number of customers remarked negatively regarding staff, drivers, delivery-people. However, more customers expressed positive sentiment on this topic than expressed negative sentiment.

Parcels/packages also showed up in the topics with partially negative sentiment. A closer look reveals a number of customers mentioning broken or damaged parcels. Accidents and poor packaging by the sender are unavoidable factors in logistics, but this development is of course still woth investigating as it can have a major impact on affected customers’ experiences.

Getting deliveries to your door is overall discussed positively. Meanwhile, a number of customers express negativity around needing to be at home. This could be a question of communication, and is worth further investigation.

>>Feel free to take a look at the report yourself, and see what insights you can gain! (Data is in Swedish)

What’s next?

Armed with this kind of data, we recommend companies to look into more sources using the same topic modelling. Do these trends also appear in data from other customer groups or markets? We would also recommend setting up projects to track development of sentiment over time. This is all possible using the right tools and good methodology.

With a solid foundation of data-driven insights, there are significant gains to be made regarding customer experience!

Want to try this kind of analysis on your own data?

Gavagai Explorer is free to try (no credit card needed) and works in 46 languages.

Gavagai is a Swedish language-tech company using advanced AI to help businesses analyze text and feedback – so they can understand their customers better. Spun off from the Swedish Institute of Computer Science, our Word Space Technology has grown and improved over 20 years, and our research team has published more than 400 academic papers.