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Can Influencer Marketing Learn from This Data-Driven Brand & Entertainment Consultancy? The 32,000 Data Points Used to Help Identify New Partnerships

Unless you’ve been in a coma or living off-grid for the last few years, you’re likely to have heard of influencer marketing.

The hype, the tools, how much influencers really get paid, and the slew of influencer marketing agencies popping up all over the world.  Love it or hate it, be it mega influencers or micro influencers, influencer marketing is here to stay.

The trouble is, how to find the right influencer for your brand?

In this article, I catch up with Edward Bass from EntSight to learn about how he approaches data driven celebrity partnerships.  Just don’t say the words “influencer marketing” to him. For Edward, celebrity sponsorship is a different beast all together…

“It’s annoying how celebrities and influencers get thrown in together just now. That mindset is fundamentally wrong especially when you start to consider the customer journey”.

Two Sides of The Same Coin?

Influencer marketing is based on the same premise as the halo effect and mass reach.  And, while I might argue that celebrity partnerships are the granddaddy of the influencer marketing world, there are a few real differences.

Perhaps unsurprisingly, the value of the deal tends to be a lot higher.  But, as Edward tells me, that doesn’t necessarily mean that decisions are always data driven.  

When he started out he was surprised about the lack of available information on audience behaviours and celebrity partnerships.  He explains:

“There was a lot of money, running into millions of dollars, but there was no data to back up the partnership or media activation with detailed audience insights.”

With so much money on the table, and research to suggest that more people trust peers or influencers and not celebrities, should the focus be on celebrity partnerships?

Edward believes that the role that celebrities play and the role that influencers play in the customer journey are fundamentally different. For example, in his latest film, Tom Cruise will have a much larger impact on product awareness than an influencer would have.  However, product placement in a Tom Cruise film won’t have the same influence on purchase consideration, consideration the role of the influencer.

When it comes to creating a broad general awareness of say, a product, or campaign, evidence show us that celebrity partnership will be more successful in getting results.  However, when you move further down the customer journey, when people are actually considering products to purchase, the influencer plays a much stronger part.

Edward believes that both celebrity partnership and influencer marketing are needed, as some brands and products have a much longer consideration stage. But he stresses the importance of decision making on who to work being data driven, not based on emotion or assumption.

Data, Data, Data and More Data

Yes, there are plenty of tools to help you along the way to generate audience intelligence from social data.   Sucking in all the data they can to predict who might be the best fit for you.

But bear in mind that some of the data points being used in this tech aren’t always helpful.  They don’t really interpret and predict how customers are motivated or what their passions and midsets are.  

Edward tells us that EntSight was created to bring a scientific and data-driven approach to brand/celebrity partnerships instead of simply scratching the surface with celebrities’ follower numbers or ‘engagement’. Taking an informed, qualitative approach to defining the audience and how they interact is at the heart of everything his company does.

He continues to explain that you need to go deep into a qualitative, strategic and audience centric approach, not one that is engagement or vanity centric.  Advising on strategy in addition to making partnership recommendations is also recommended.

Edward’s solution at EntSight is to use data from multiple platforms across social, web and trend data, with a whopping 32,000 data points being measured.

The 32,000 Data Points

Cynical about the 32,000 data points?

Me too.

I remember when I was running research into the mattress-in-a-box industry, one of the brands I analysed promoted “8,000 sleep data points” in their sales literature.  

Like me, you’re probably wondering what the heck a sleep data point is.  

I tried to find out.  

But, alas, there were no other mentions of sleep data points.  It still remains a mystery.

Whenever I hear about a lot of data points being measured, I always think back to that example. When Edward, mentioned that he can use 32,000 data points to identify the best partnership opportunities I needed convincing.  

Edward told me that he considers a data point to be an identified audience attribute, behaviour or preference.  So, there are 32,000 behavioural preferences that can be used to identify the best celebrity partnership.

EntSight don’t use all 32,000 data points for every project.  That would be madness and, if I’m honest, lead to context holes and unusable insights.

Edward says that deciding on the best data points to use comes from gaining a lot of experience. Having the opportunity to run projects, he makes decisions based on the parameters of the campaign. Personally, I can’t help but feel that the standard metrics used by some of the influencer marketing tools miss this nuance.

There’s still a bit of secrecy around the exact data points used at EntSight, but, as mentioned earlier, Edward does mention that they are a blend of how people behave and what drives their preferences around celebrities and brands.  This includes data on areas such as:

  • Brand Preference and Interactions
  • Celebrity Preference
  • Favoured TV Shows and Movies
  • Technology Used
  • Sports Watched and Played
  • Music Artists, Genres and Events
  • Fashion Preferences and Behaviours  

For me, the metrics used would be what I call “lifestyle metrics” that are used to predict how customers are motivated, their passions and mindsets.  Edward shared a couple analysis examples…

He says that the EntSight difference is the depth and nuance in the data points used, as well as the in depth strategic advice they provide on how to active the partnership.  I can’t help but feel that the strategic advice is their key point of differentiation. 

Measuring Impact

So, it’s one thing to use data to identify a potential partnership, but how do you measure the impact of that partnership?

Social stats and buzz can look great and give you big numbers, but they don’t tell you how effectively you have influenced those specific audiences.  

For EntSight, this means that impact is measured by exploring how closely the partnership has met brand expectations and the impact on the behaviour of the target audience.  Edward says that too much of campaign reporting looks at the overall results rather than focusing on how activations resonated with the target audience.

For him, it’s also important that influence isn’t measured on engagement but behaviour.

Lessons for Influencer Marketing

Edwards says that

“having provided strategic direction for brand and celebrity partnerships for leading brands such as BMW, Piaget and Tommy Hilfiger, the biggest lesson is in understanding the objective of the partnership and using appropriate data points to understand the behaviours of the target audience”.  

So, the moral of the influencer story is to consider the metrics you are using to inform your partnerships.  

Not every project will use the same metrics and you’ll need to blend behavioural and lifestyle metrics to understand how customers are motivated, their passions and mindsets.  

We all know that big follower numbers don’t make the best influencer metric.  Brands are comforted by big numbers, so it can be difficult to take them out of consideration. 

But, big metrics don’t mean big successes. 

That magic happens when you’re confident that you understand the mindsets of the influencers target audience.  

 


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Jillian Ney
the UK's first Dr of Social Media and a Digital Behavioural Scientist. For over ten years I've been analysing social data to find insights into how people make decisions. I now use this knowledge to help brands to make their social data work harder for them and turn noisy social chat into actionable marketing intelligence quickly. More content by

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