Switchboard – or why native messaging Apps are the future of mobile research


Between them WhatsApp, WeChat and Facebook Messenger boast billions of users. People have become habituated to sharing intimate thoughts, mundane snippets, photographs and videos with their closest friends and family through these private apps.

At the same time ethnographic researchers have been using these platforms formally, and informally, as part of projects for several years. At a basic level their capacity for capturing photographs, videos as well as conversational data makes them simple, reliable research tools.

But perhaps because they are not marketed as research platforms, this use is largely taking place under the radar. Not many researchers talk about these native messaging apps as credible research tools.

They suggest these apps can ‘make-do’ when you require something quick-and-dirty but for best results a proprietary research app is required. But might native messaging apps represent more than a stop gap? We think they are superior to specialist research apps and may well represent the future of mobile research as we know it.


The benefits of using native messaging platforms for research


From a research perspective using native apps has several hard-wired benefits.


For a recent project we wanted to understand how and when people were using voice interfaces (think Siri, Google Assistant) on their smartphones. In addition to conducting ethnographic work it was important to capture real, in-the-moment behaviour over time. So we invited participants to join a WhatsApp group and share their experiences.


Compared to specialist research apps, using WhatsApp in this situation had some distinct advantages.

Native apps enable more intuitive sharing


Most participants in the study were regular WhatsApp users already. This meant that the app was ‘ready to hand’ for sharing the specific behaviour we were interested in. Each time they spoke to their smartphone we asked them to take a screen shot of the instruction, a picture or video of where they were, and offer commentary on how the interface performed.


Clearly making such contributions is not a ‘normal’ thing to do, but because using WhatsApp came so naturally to them friction was reduced. This meant that the quality and frequency of the contributions was far higher than when we’ve experimented with specialist research platforms. When a tool is so familiar, using it for something unfamiliar is much easier than using an unfamiliar tool for an unfamiliar activity. The result is better data and, by extension, better research.

Native apps create more expressive contributions


When your grip on a language is shaky then it’s more difficult to say what you mean. Searching for the right word can make what we end up saying stilted or imprecise. Because most people are using these native messaging apps everyday they are fluent users of the interface. Their contributions are more articulate and suggestive on messaging platforms where they have colloquial familiarity.


For example, in the voice project we asked subjects how misunderstandings made them feel (moments when they did not get the response they wanted). Using WhatsApp, they called on a range of emojis to express themselves with nuance and humour. Combining these contributions with videos, photographs and location data gave us a rich understanding of their emotional states in the context of specific real world situations.

Native apps provide a more intimate setting


Native messaging apps are typically used for communicating with close friends and family. While it’s difficult to be definitive, our experience suggests participants subconsciously associate messaging groups with intimate, private conversation. These tacit associations establish a more honest and confidential setting for research. People generally feel more confident in expressing what they really think, and do, because that’s what they use these platforms for everyday, versus other more public, curated forums like Facebook or Instagram.


In the context of the voice interface project, we found people shared examples of basic mistakes and misunderstandings. Behaviour they may have been too embarrassed to share in more formal or unfamiliar settings.

The drawbacks of using native messaging platforms for research


These benefits aside, there is a good reason why specialist research apps still exist: native messaging platforms are not designed with research in mind.

When you use WhatsApp, Messenger or WeChat there are no in-built capabilities for segmenting participants, tagging content or managing tasks. Furthermore, the raw data is difficult acquire and, once you have it, tricky to analyse. This means researchers must spend serious amounts of time cleaning up and organising the data.

In response specialist research apps boast a more sophisticated back-end; addressing the lack of technical research features that makes using native apps cumbersome for data management and analysis.

However, the front-end of these specialist apps are often a slightly clunky version of the native platforms that they aspire to be like. It is understandable that they ape the interfaces that people are used to, but given the vast resources and scale Facebook and their ilk they will never be as slick. No matter how similar they look and feel, they will always look and feel like distinct research apps whose use needs to be learned. They will never feel as natural. Their use never as uninhibited.


Combining the best of native and specialist research platforms


Having experienced the benefits and drawbacks of both native and specialist platforms, we decided there must be a better way. So we developed Switchboard – a platform that we believe combines the best of both worlds.

Switchboard enables researchers to use Whatsapp, Facebook Messenger and WeChat, but adds segmentation, analysis and output features that transforms these ubiquitous platforms into sophisticated research tools.

Our mission with Switchboard is to unlock the research potential of these incredible messaging networks.

Switchboard is still in Beta testing but is proving a powerful tool. If you are interested in becoming involved in a pilot project please get in touch.


// Tom Hoy