At the starting point, Neticle’s text analytics ability was built only into Neticle Media Intelligence (NMI), our social listening platform. But many clients, who were satisfied with social listening results, had in-house textual data as well - like survey feedback via text messages, or emails – and they wanted these analyzed the same way. So, we responded to this need and Zurvey.io was born. At first, clients could only upload Excel files, and they got back Excel files enriched with the analysis results. Even the dashboard came later.
Developing the dashboard took a long time: we kept adding more features and charts, then the available types of static exports grew, and the whole thing became a quite useful self-service text analytics tool. But we realized that having a wide range of input data sources was just as important as text analysis itself. No matter how accurate or detailed text analysis is, we cannot understand the Voice of the Customer if substantial feedback is missing or if the feedback collection methodology is not up to par. This notion eventually led to data collection becoming part of our portfolio: clients often needed (and still need) support with customer feedback collection, so we extended the software with a survey builder module. It’s interesting to note that even though we added the survey function just to have an input capability for our text analysis, several clients still happily use it as a standalone service.
A further step was realizing that lots of clients had continuous data streams which we needed to be able to integrate, as downloading and uploading all the time would not be practical. Dynamic data sources are much better in practice, so we started to develop our integrations, like the API and the email connector. Social listening data from NMI also got channeled into Zurvey.io, which created the 360-degree view.
Today, we can do much more than just text analysis: we’re already there from the point of collecting feedback and we advise clients on how to best do it. There are low-code options to channel data from every source into Zurvey.io. In the past few years, we’ve completely adopted a customer experience mindset, building around our core capability of text analysis. All our features serve to improve CX on multiple levels, and we’ve seen the majority of companies embrace the CX mindset as well. Positioning the product like this has helped a lot in being able to successfully work with clients, and enabled us to be more focused in problem solving.
There are three things. First, the feature needs to be desirable to clients. Developing a product cannot be based solely on generally good ideas, we need to think about creating value to customers. Even if something’s super innovative or technologically great, if it does not create added value, it should not be included in the development! When building our roadmap, we prioritize features that significantly increase satisfaction. It should either enable clients to do something that they cannot do without Zurvey.io, or at least they should be able to solve something much faster and easier with it than with another product. The difference should be substantial. The biggest challenge regarding this is that these don’t mean the same to every client. They could even create conflict!
The second thing is that the feature needs to be financially viable. It should increase revenue (i. e. create value to our company as well) enough to be worth the time and effort it takes to do the development. Finally, it needs to be technologically feasible as well. Can it be done with the current tech stack? Does it fit into the current architecture? How long does it take for it to create the value we want? These are the questions we always need to be asking ourselves.
Overall, the worst thing that can happen is developing something that’s indifferent to the client, because we could have spent those resources to create actual value.
The biggest benefit is that there is always something to lean on: we have a good relationship with our clients, we talk to them all the time, we can show them our ideas and we get continuous feedback. The challenge is to align their requests and our long-term vision of the product. We often try to mold the developments in a way that they cover multiple client needs. Many times, we can find solutions that tick several boxes and are still desirable!
Even if we do add client-specific features, we try to keep the user flow and the interface as clean as possible, so that other users (especially the core persona) don’t encounter features that they won’t use all the time. Zurvey.io is modular enough to allow for this. Overall, the tool should be kept simple while still being able to solve complex problems: we want it to be a proper selection of chef knives instead of a Swiss knife, as they often say in product development. This is how you maintain the balance between the product vision and flexibility.
Two of my favorites are Raiffeisen’s mobile app review solution and Telekom’s CX survey setup. Raiffeisen needed a completely unique solution, which we were able to insert seamlessly into Zurvey.io, without shattering the whole system or ruining other users’ experience. Telekom’s case was exciting as that project had great visibility, we had to work with lots of stakeholders through many stages, and all of this was performed under a strict deadline with very little room for errors. I’m proud of the results we achieved in both cases.
The direction I want Zurvey.io to take is towards closing the loop in the customer experience improvement process. Closing the loop on customer feedback does not simply mean resolving a problem: you have to make sure they’re actually happy with the solution, and that it has resulted in an enhanced experience with your product or service.
Zurvey.io can help to make this happen. I want to enable our users to act upon our insights, either by triggering other services and tools, or using Zurvey.io to reach out to customers. This approach is best described with a few pairs of antonyms: I would like our insights to be real-time instead of retrospective, customer-level instead of aggregated, omnichannel instead of single channel, as much as possible.