INTERVIEW SERIES: Dr Jillian Ney, Digital Behavioural Scientist

I was one of these people that never knew what I wanted to be, at the end of my degree at Strathclyde University I still didn’t know what I wanted to do. My friends were all applying for jobs and finding graduate programmes they wanted to enter into, but I just wasn’t interested in any of that. Speaking to my lecturers, I decided that if I got a first-class honours degree I would stay and do a PhD. I enjoy research so it seemed like the logical step for me. So, I was awarded with a first-class degree, and then I had to find the topic that I wanted to study for my PhD.

That was a tough process. There wasn’t anything that I was super passionate about that I could confidently say I would be happy spending the rest of my life studying. At that point a couple of things happened. The first was advice from my university to map the current trends to predict what was going to be popular in the future. I mapped the trends down to two, social media and then movie tourism – interestingly, both became extremely popular. During this process, I received a grant to work on a project that was exploring ‘volunteer voice for mega sporting events”, that’s basically The Olympics, Commonwealth Games, The World Cup, that sort of thing. The only way I could get to the “voice” of the volunteers was to study online conversations.

I fell in love with the data and the rich conversations you could qualitatively analyse. So, my social media trend became more of a social data trend. Luckily, I was able to find a supervisor for my PhD. At that time research in the area wasn’t really a thing and if I’m honest was seen as a ‘bubble’.

After analysing social data for a decade, I got a bit despondent about the industry and the fact that things were not moving on. It’s still hard to analyse social data properly, it’s much more than tools and clicking buttons, even AI still doesn’t have a massive handle on analysing social data in a meaningful way.

I’ve never been one to do things that I’m not passionate about, so I went back and re-evaluated what I was doing. In doing this I found that there was a growing number of people who also analysed social data as 100% of their job role. I spoke to these people and they were struggling with the same things as me – and the fact that there is no community, no association or even any real accreditation for people who analyse social data.

So, I decided to make it. The goal of The Social Intelligence Lab is to raise the professional standards of social data analysis, and to bring the global community together to have “one voice” and galvanize the future growth of the industry.

At first people were mostly interested in the data to “measure” the success of their campaigns, this hasn’t really changed over the years, people still want to measure those likes. However, over time, more people wanted to “monitor” what people were saying online, this was very brand focused. Then we’ve slowly got better use cases, to really get to understand the people behind the conversations.

I’ve seen a big increase in “audience intelligence” functionality over the past couple of years. In my opinion, this capability is still in its infancy, like what social media measurement was at the start. These tools largely still measure the wrong things, analysis isn’t always meaningful.

For the next stage of growth in the industry, we need to focus on building methodologies and measurement frameworks to approach social data analysis in a meaningful way instead of being guided by automated analysis in the different technologies.

Yes. There’s been so much bad press around social data analysis because of Cambridge Analytica, we’re still talking about this and I hate that. The thing with Cambridge Analytica was not just the data analysis but the retargeting of individuals on the same platform, in no other form of consumer research can you do this.

Ultimately, the analysis of social data for brands is to bring them closer to their consumers, to understand their behaviours, motivations and needs. This should be used to create better customer experiences which in the end benefits the customer as well as the brand. It’s all about value exchange.

I would say thought, that “listening” isn’t enough. You really need to be active with the data, make the data human, tell stories and integrate these throughout the brand to make better experiences. I’ve never liked the term “social listening” as it suggests the process is passive, but it’s actually active.

I still think that one of the biggest challenges is knowing the different use cases, and identifying the most meaningful metrics to use. I’ve always advocated for social data analysis as part of the insights function and I still see teams apprehensive to use social data because they are unsure of their ability to get insights out of the data. They have a host of other research methods that they can use.

My role at The Social Intelligence Lab is to help people get started or level-up their use of social data in a way that produces business results. It’s about getting insight, better, faster and cheaper. We don’t comprise the quality but help brands more easily blend research approaches that help them move faster.

The industry is changing massively, we see a shift more into the customer insights space. Traditionally social listening was positioned in marketing, but there is a general move into the insights space. This is exciting as that’s where I operate, and always have done. It’s nice to see the industry coming of age.

In the future, we’ll see more brands analysing unstructured data sets with social data. The principles for analysis are the same after all. I think we’ll also see a greater use of other data sources, like sales data. The role of social data is “the voice of the customer” so as these types of data sources increase, there will be more to analyse. For example, voice data from all the voice assistants or even data from bots.

The vendor market is very competitive and has always historically been driven by a “functionality war”. There is not major differentiation between competitors in the space. I think that the time has come to start listening to their customers and developing protocols that help them get to the insight that they are looking for quicker.

AI is being hailed as the next big thing, but many of the advances here are the “easy to do” rather than the “business critical”. More time needs to be spent working out what people and brands are trying to achieve with the analysis and creating solutions to meet these needs rather than all these new ways to “look” at the data but still not producing meaningful results. There are some vendors moving to this view, it takes a lot more time and effort, but the results will be worthwhile.

Let’s put this in context, in no other sector would you have people and brands from all these different industries using the same generic models and dashboards. We need to start getting specific.

This is a really tough question to answer. I’ve been to a lot of events this year and I’ve been underwhelmed at the content. Social data analysis is always just a small part of events, and the content here is usually not very advanced. This makes it tough to recommend an event. There’s also no event specific to social data analysis outside of the ones created by the vendors.

I ran an event called Social Intelligence World in 2018. It’s perhaps time to bring this back?! I’ll need to see if there is a demand for this.

Good question. I love my home country of Scotland. On a good day there is no better place in the world. I travel a lot and always get excited when the landscape changes and you see the “green” of Scotland. Abroad, my favourite place that I have visited is Vietnam. The people, the scenery, the food, the culture. I just really felt at home there.