NetBase: On using social listening and influencer marketing to ‘get more with less’ for campaigns
When the concept of social listening platforms first came about, it was that rarest of things in martech: a ‘solution’ which actually solved people’s problems. As data created on the social web reached ever-increasing levels, this made sense – but what’s more, being able to take this data and create insights from it was the real jam in the sandwich.
John Tyrrell (left), senior vice president EMEA at social listening and influencer marketing platform NetBase, shares a good example of how these extra insights can be found – and how NetBase could find it more readily than competitors.
One client had recently acquired a home storage product and wanted to find out how its customers were using it. Market research and surveys found common ground in the usual methods, such as using it to fold clothes and save space. Yet by analysing social conversations, NetBase found that almost a third of the discussion was around how this product had been a lifesaver for outside activities; storing items on trucks, using it on holiday, and while moving house.
This journey to customer success through social listening platforms, however, has had the occasional bump in the road. Tyrrell joined NetBase in 2012, working in sales leadership roles before taking over the EMEA region earlier this year. As data constraints changed, so did NetBase’s positioning. The company had traditionally been – and continues to be – strong in the enterprise, with Coca-Cola and L’Oreal among its blue chips.
“We had to realise that we would continue to serve the enterprise brands, but we needed to be more nimble and work with smaller accounts as well,” Tyrrell tells MarketingTech. “For every Coca-Cola, there are probably 30 or 50 more agencies and other smaller brands that are ready for social listening as well.”
But there was more. Last year, as Tyrrell reports, there was disruption in the market. Social listening is not only a two-way street between brand and consumer, but also between vendor and social media provider. “Folks whose data we rely on put some real constraints around how we get that data and what we do with that data once we have it,” Tyrrell explains. “Those constraints, I think, led to a lot of companies active in the space reconsidering their role.
“Fortunately, NetBase was in the position to be agile and keep up with those changes,” he adds. “In a reverse way, what may have been challenging for the industry of social listening, we were able to make adjustments to the new market realities and continue operating.”
The use of artificial intelligence in social listening technologies has the potential to make the insights greater and the decisions sharper. But buyer beware: many martech firms are stuffing the acronyms AI and ML into their promotional material whether they’ve got a simple chatbot or an entire neural network under the hood.
NetBase is in a strong position to parry this question. Why? Because they use multiple models – and can easily delineate between them. The company’s AI Studio product, launched to great fanfare in June, is a case in point. “Most of the products out there are talking about machine learning,” says Tyrrell. “Machine learning is one of three general classes of artificial intelligence; there is also expert systems and then there’s deep learning. NetBase uses all three.
“There’s a lot of artificial intelligence around social listening naturally – there’s a lot of data, it’s the right place for applying it,” Tyrrell adds. “Why the introduction of [AI Studio] was so well received was that if you’re just working with machine learning, someone needs to train the machines. It becomes really powerful once you’ve trained it, but you need to train it on every topic, every theme. The way NetBase is implemented with artificial intelligence, it doesn’t require that work.”
Customer response has been good, but they tend to be distinctly uncurious around how it works – just delivering on the promise of reducing the length of a task from four hours to four minutes. “This is the promise of deep learning where it doesn’t require someone to build and maintain the learnings of the engine,” adds Tyrrell. “You plug in a topic, and four minutes later it’s telling you what the themes are, so it’s doing the work for you.”
Tyrrell notes another key benefit. Take the home storage company from earlier. Market research was naturally biased in that it asked about home storage. NetBase found a world of use outside the home. It is a similar concept at work here.
“If you’re an analyst and you’re trying to filter the conversation to find out the meaningful parts of it, you have to know what to look for,” he says. “The machine goes off and says ‘here’s different elements of the conversation that are appearing’, and there’s an independence to that, an objectivity. That’s really important.”
Influencer marketing and social listening dovetail – in theory at least – by helping to solve the problem around ROI. Tyrrell’s response when asked about the concept’s efficacy differs little from many in the industry. “Influencer marketing is not the answer [on its own] – I think you need to do it smartly,” he says. “If you multiply influencer by number of followers and engagement, that won’t tell you how well they’ll carry your message.
“Our customers go a level deeper to say ‘on a particular topic, how effective is this influencer? How engaged is the other audience on that topic to tell them how well their message is going to play through that channel?’” adds Tyrrell. “They do this with the macro influencers, the micro influencers, the heads of tribes. It’s about better understanding which influencer is going to be more effective with which audiences.”
Tyrrell is speaking at #DMWF Europe later this month, alongside Gilbert Saktoe of MetrixLab, on this very topic. The theme of ‘getting more with less’ will be prevalent amid changing economics – a theme Tyrrell knows all about on his EMEA travels. “Times have changed – people are forced to look at what their strategies are and stack things,” he says. “We have a very efficient way of producing insight, so that’s the first thing. The second thing is that people need to tighten our belts.
“For us, our artificial intelligence and the depth of insight that we can bring to the table makes that possible.”
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