The future of influencer marketing: B2B influencer engagement

carvermoneyWhen you hear the phrase “influencer marketing” – a consumer product example comes to mind, doesn’t it? It’s a kid on Instagram, being paid to post a photo of a pair of shoes, or some such thing.

Well…that’s not the only game in town. In fact, it may not be the best game in town, over the long term. Many people say influencer marketing is more effective than advertising because the world demands authenticity now, more than ever. Honestly, though, paying someone to advocate for a consumer brand isn’t that far from advertising and so the advantage that model enjoys seems unlikely to last. (That said, my thoughts on paid influencer marketing are shifting away from outright rejection, lately.  That’s another matter.)

Influencer marketing: Building relationships with the people your customers are listening to.

Today, as part of a 3 part series of posts on The Future of Influencer Marketing, I want to share some thoughts about one big trend I see emerging: B2B influencer engagement. These thoughts are based on my years of serving customers in the influencer marketing market, many of the most successful ones being B2B companies, what I see from other vendors in this space, and frankly my hopes and desires. I secretly hope more influencer marketing shifts to B2B because I think B2B is smarter and more interesting, less aimed at serving the lowest common denominator and pointless material consumption. Whatever, though, I totally work with B2C companies too, of course.

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From the top right, clockwise. Click to enlarge.

B2B influencer marketing is going to challenge assumptions, both for the marketer and for the thought leaders, or influencers.  Marketers will need to take a more strategic view of influencer engagement.  Look at this incredible webinar that Aileen McGraw of Microsoft did with us on her influencer engagement for a #A1 example.  Remarkable.

Influential people in B2B will need to navigate what it means to work with brands in the future.  Is it a peer-based, unpaid collaboration? Is it a sponsored arrangement?  I’m sure we’ll see both and more.  It won’t be like the stereotypical sponsored Instagram post, though, at least not all the time.

Technology needs will be different too.  I’ll refer you to my previous post about building long term relationships, because there’s a lot of overlap here.

Finally, B2B influencer marketing is going to require a different kind of people, staffing.  It’s going to require people who have or who can build credibility in an industry context, with leading practitioners.  I’ve done this in data-related parts of the Internet, and it takes time.  Junior staff, told to jump in and engage B2B thought leaders, are going to struggle until they have invested time, learned, and contributed.

Finally, B2B influencer engagement, because it requires credibility, and is best served by long term relationships, is going to require that people really take responsibility for their work and reputation.  B2C “influencers” may, to too many brands, feel like expendable, interchangeable resources – but B2B influencers are not.  They’ve invested years working, taking risks, succeeding in business or technical matters.  Engaging them is a serious business responsibility.

Last week was about building long term relationships in the future of influencer marketing.  Next week I’ll write about the 3rd of 3 trends I see: gathering market intelligence from your influencer engagement.

The future of influencer marketing: Long term relationships

Influencer marketing, as most practices do, is advancing along a maturity curve.  Here is the first of three ways I see evidence it is moving, based on engagement with customers, watching other vendors in the space, and more. Then some thoughts on the consequences of these developments.

Building long term relationships

Influencer engagement has compounding returns and the model of just-in-time cold call pay-to-play is far from the only game in town.

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Clockwise from the top right: If we as influencer marketing practitioners start building more long term relationships, we’re going to need technology to manage that.  Specifically, in order for this to be a sustainable practice, we should be able to track our organization’s history of engagement with a given thought leader and we should be able to leverage automation as much as possible where appropriate.  I like to say: let’s use automation to surface opportunities to engage – let’s not use automation for the actual engagement itself.  

Next, we’re going to need to get to know the people we’re engaging with: as a group, as individuals but across platforms, and based on relationships built by the right people in the right places in our organizations.  For your company to get to know influential people well is a staffing issue.

Finally, developing long term relationships and working with people over time requires that we give up some control.  I’ve honestly had someone say “these thought leaders you found are great…how do I get them to do what I want?”  Lol, yeah so…that’s not really how it works.  We’re going to engage with and collaborate with these people respectfully, as peers.  That means two other things: we need an organizational structure that supports that kind of work and we need to be selective about the people we engage with.  Since they won’t be reporting to us – let’s vet them before we spend a bunch of time engaging them.  Or we could use software to discover and vet thought leaders for credibility in specific contexts, then use its automation to track opportunities and history of engaging with them…that’s what I suggest.

This post took longer to write than I thought it would. I’m sitting in the lobby of the Brooklyn Museum and just got surrounded by kids, curious to look at my computer. 😉  In subsequent posts I’ll write about the future trends of B2B influencer marketing and the use of influencer marketing for gathering market intelligence research.


Source based vs keyword based social listening

Almost all social listening is done based on keywords, but as a former journalist that broke a lot of news stories by listening first to the right people online, no matter what words they happened to use, I can tell you that keyword based listening is not the whole opportunity.

That’s what we do in Little Bird, we find the people at the center of a given community (say, Internet of Things experts, or Makeup Artists) and we watch to see what they talk about.  No keywords required, we just want to know what they come up with.  When they post something that gets a lot more engagement than their content usually does, that’s extra important.  Now as a part of Sprinklr, we’re able to get some great aggregate content analysis out of these groups of people, set up rules engines to route messages around to various departments in an organization based on what keywords they do use, and much more.

One of my favorite source-based listening workflows right now is an email alert I have set up for any time any of the 60+ people in my VIP list uses the words amazing, incredible, or new.  I get to discover all kinds of cool  things and important conversations this way!  It’s amazing, incredible even.

Find the right people, watch them, discover unknown unknowns, and it is good.  Below, an important conversation was brought to my attention that I hadn’t really thought that much about – until I saw a couple of super-smart people discussing it critically.  What’s that saying? I can’t read everything Zeynep Tufekci writes, but when I do…

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The challenge and opportunity of Extelligence

Being human is hard.  It’s complicated, at least if you want to do it well, I think.  Now picture the amount of data available to us exploding in the next few years.  Most of that data will be processed for us by machines, but the sheer number of analytical conclusions the machines offer us will be overwhelming, as well.

Models and Frameworks 

I’m excited about the conscious and practiced use of models to understand data super-rich experiences.  My latest favorite has been something I learned from a Kirk Borne blog post.  This is about data science, but it can just as easily be applied to any complex part of life, I think. “Dimensionality reduction is a critical component of any solution dealing with massive data collections. Being able to sift through a mountain of data efficiently in order to find the key (1) descriptive, (2) predictive, and (3) explanatory features of the collection is a fundamental required capability for coping with the Big Data avalanche.”

I added the numbers to that sentence but have literally found it very useful to look at complex situations and ask myself, “of all the things you could say about that situation, which one or two are most descriptive of the whole?  Then, of all the qualities of this experience, which are most predictive of its outcome?  Finally, which of the many parts of this whole thing go the furthest in explaining the whole thing?”

I used that framework in an influencer engagement training session with a very large B2B company last week, explaining that the thought leadership data mining system I’d just trained them to use could be best defined by its networked nature – the people at the center of the community have built and earned a ton of connections to others, that’s the most defining quality of the situation.  The most explanatory feature, I believe, is the humanity of the participants.  They’re all just like you, and they’ve worked hard to contribute to the network.  You’re going to have to too, and be human with the people you can connect with, if you really want to understand the social space you’re looking to do business in.  Finally, the most predictive quality of social networking is its cumulative nature, I said.

We’d previously discussed how all tasks can be understood as either optimization tasks (to be completed as fast as possible), maintenance tasks (where there’s a linear relationship between effort and outcome) and investment tasks (greater than linear, sometimes exponential value derived relative to effort).  And we talked about how influencer engagement can and should be done as all three of those task types.  Mixing it up.  So the most predictive feature of the experience is probably its cumulative nature – the more you do all kinds of work in connecting with influential people online, co-creating value with them, the more impact each engagement makes over time.

That’s a couple of models, I suppose, both identifying the most defining, explanatory, and predictive features in a phenomenon, and the model of optimization, maintenance, and investment tasks.  What are those kinds of things? I think they could be understood as forms of “extelligence.”


Tonight I was reading some writing from Belgian Internet of Things thought leader Rob van Kranenburg (amazingly thought provoking, delightful to see that tons and tons of other leaders in IoT follow him on Twitter according to our data) and came across the term “Extelligence.”

“Extelligence,” van Kranenburg writes,”a term by Ian Stewart and Jack Cohen, a biologist and mathematician, is cultural capital available to us as external media.”  It’s external, not internal like in-telligence. Get it? Cool.

Van Kranenburg concludes a strongly worded piece of writing titled The end of strategic leadership: be extelligent or extinct with the following:

“In an information-rich, digitally connected world, where much of the knowledge and tools that we make use of are outside our heads there will be a need to develop new communication ‘senses’ that allow us to manage and make use of the enormous amount of information we will be confronted by. This will lead to the development and adoption of new and different types of human-computer interfaces and different ways of communicating with technology.  We know this as deep learning and machine learning; artificial intelligence.

“But this is the superficial reading of extelligence.  Extelligence, a term by Ian Stewart and Jack Cohen, a biologist and mathematician, is cultural capital available to us as external media. For them ‘complicity’ – a combination of complexity and simplicity –  of extelligence and intelligence is fundamental to the development of consciousness, and your business, institution, government or startup.

“What does this mean if you are over 50.000, 100.000 as an organization? Get the scouts and scavengers on the ground operating autonomously, build complicity only in the links between them. Provide good exits to anyone else and keep them close to where you think the teams are not heading.”

New communication “senses” that allow us to manage and make use of the enormous amount of information we will be confronted by?!  How exciting is that?  I nominate “the network,” social media, frameworks and models as great new sources of extelligence, of cultural capital available to us as external media!

I said I’d mention the challenges, too, in the title of this blog post.  I think the biggest challenge is that this requires stretching your brain, or hiring someone to help you think.  I do that every week, personally, and my counselor tells me “people aren’t stupid, they’re just cognitively efficient. We’ve evolved to expend the minimal amount of energy possible so we can keep it in reserve for a crisis.”

Well, we’re in a crisis, but it’s abstract, collective, and we’re not inclined to recognize it, much less address it with tools of extelligence.  Thus the challenge.

But wow are the opportunities incredible.


PS: Speaking of leveraging the network as a source of extelligence, I just wrote this first blog post in months because I finally figured out how to get my blog to load faster. I posted a Twitter poll asking if it was maddeningly slow for others and found (a) that a fair number of people reported it loaded just find and then (b) one of my contacts pointed out a specific problem that was slowing the load! So I fixed it and now I feel like blogging!  Thanks, extelligent internet friends!

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