Tech influencers are interesting individuals. I know the B2B tech space exceptionally well. I was an early adopter of social media, grew up in Silicon Valley, and have been here ever since. I know many B2B tech influencers, and I have partnered with them on dozens of influencer activations.
I have also learned a few things along the way. Early on, I struck out a few times, working with influencers who did not have the impact I thought they did. I have also hit many home runs, working with some of the top tech influencers in the world. Based on these experiences, I’ve made a list of the five most important things you need to think about before partnering with B2B tech influencers and working with them.
I also want to give you some essential advice because I don’t think anyone else will .. at least not publicly. And I only say that because I spent several hours researching to ensure I wasn’t unknowingly stealing anyone else’s ideas or recycling thought leadership. We do live in a sensitive world.
Identify tech influencers that influence your audience
Real influence can’t be bought. And yes, this happens in tech. It’s not difficult to identify which influencers are trying to manipulate the size of their audience, engagement, and reach. But this post isn’t about that. It’s about helping you maximize your investments in B2B influencer marketing. And if you still haven’t launched an influencer program, there’s no better time than the present. There continues to be massive growth in this space despite the economy, and there are no signs of this slowing down. U.S. companies will increase their spending on influencer marketing to $5B by 2023.
One way to identify the most relevant and influential 3rd party voices is to start with your true north and your one source of truth–the target audience. An audience analysis will include several data sources like primary and secondary research and social analytics, giving you access to actionable data insights.
Using affinity and conversational data, you can start to pinpoint the technology influencers your audience trusts and turns to when seeking information about products, services, and tools that power your technology stack. The one caveat you should be aware of is that the tech influencers you identify with this approach may not be the ones you’d expect, and you need to be okay with this. You aren’t going to find the influencers that appear on the hundreds of influencer lists floating across the internet that were created for link bait reasons.
Once you have your initial list, you should create an influence map to see how the different groups of technology influencers are connected, either by affinity, follower relationship, or by topic. You can do this with a platform like Onalytica or most data visualization software.
Isolate topical relevancy
Sometimes I hear, “Let’s find the most influential Instagram tech influencers!” This is not the right way to think about it.
In B2B and tech influencer marketing, it’s a best practice to start with topical relevancy. This approach begins with analyzing a specific topic, industry, or vertical. For example, if you work for an enterprise AI company, you’d want to start with analyzing the artificial intelligence market first.
The findings should include the top media outlets writing about AI, conversational themes, hidden narratives, influential communities, the top voices leading the AI conversation, and the channels where they have the most authority on the topic.
In many cases, the top voices aren’t necessarily the technology influencers you can collaborate with. For AI specifically, many of the top influencers are CIOs or technologists that work for some of the largest enterprises globally like IBM, Google, Microsoft, and others. In the data, you’ll find analysts from firms like Gartner, Forrester, and IDC, which we all know is a much larger budget investment and “pay to play” than even paid influencer marketing. The data will also uncover the journalists and reporters that write about artificial intelligence. You can’t nor should you even attempt to pay them to write about your company. They wouldn’t do it anyway.
In any case, it’s wise to get a complete purview of the AI market for reference and increase your knowledge about the space. Another best practice is starting with an “always-on” organic influencer engagement program, which is something you should do whether you collaborate with influencers or not.
As with most things in life, this methodology has some challenges. Many “top tech influencers” are somehow influential on every adjacent topic under the sun. You’ll find the same names if you were to analyze Al, 5G, or my personal favorite, “digital transformation.” Google “AI Influencer List,” and you’ll see what I mean.
It’s not uncommon for today’s technology influencers to flood their content with hashtags that aren’t relevant to the subject matter. This is not necessarily a bad thing. It’s a technique to get more visibility for their content. But it does skew the data and makes it more challenging to find the right influencers.
So when you start with the topical analysis, one way to find the most relevant tech influencers is by isolating topical relevance. To continue with the AI example, you’ll want to create your Boolean logic to look something like the following, especially if you want to find true enterprise AI tech influencers with authority:
(“Artificial Intelligence” OR ++”AI”)
AND NOT (SMB OR “small business” OR “start up*” OR “digital transformation” OR #digitaltransformation” OR 5G)
You may have some questions so let me break this down. In the first line of Boolean, I want to look for any mention of “Artificial Intelligence” or AI (the ++ means to look for capitalized mentions of AI.) You may be asking why I wouldn’t include #artificialintelligence or #AI, and that’s fair. The data comes back very noisy whenever you include hashtags in your initial search. I might add the hashtags later, but I always start the analysis this way.
The second and third lines are geography and language-specific. Again, if we are looking to isolate topical relevancy, you’ll want to exclude different parameters that may add spam to your data set. I don’t necessarily use these Boolean operators all the time.
The last line of the Boolean are exclusions. In our initial example, we decided to look at AI influencers with expertise and knowledge in enterprise companies. So I’ve excluded any mention of small businesses, 5G, and digital transformation. You can exclude as many terms and topics as possible to find the most relevant influencers.
I want to stress that building your Boolean query is the most crucial step in a topical analysis. It may take 5-10 hours of trial and error before you feel good about the results.
You might start with basic desk research. Build your Boolean. Review the results. Add keywords and exclusions. Delete keywords and exclusions. Rinse. Repeat. And then do it again until you get it right.
This brings me to my next point.
The distinction between tech influencers and thought leaders
There are many ways to segment technology influencers—by topic, job function, industry & vertical, influencer type, and role are just a few examples.
We’ve already been talking about topical relevancy, so that I won’t get into it again. But once you have your list of enterprise AI influencers, you can further segment them by any of the following parameters:
- Job function: This influencer segmentation would be based on their current professional role–professor, analyst, journalist, consultant, technologist, etc. You can segment this list based on whatever you are trying to do with your influencer program.
- Industry & Verticals: This segmentation would be based on the horizontal industry they work in, report on, or have domain experience with and include industries like healthcare & life sciences, retail, travel & hospitality, and telecommunications. Verticals include supply chain, warehousing, logistics, finance, and marketing.
- Influencer type: This segmentation is similar to what consumer brands do when they segment influencers by follower counts, engagement rates, etc. If you’ve ever worked in consumer marketing, terms like mega, macro, micro, and nano influencers will be familiar.
- Influencer role: This segmentation is an exercise you’ll want to go through when creating your influencer strategy. It involves segmenting the influencers based on what actions you want them to take–write long-form content, record videos, moderate social audio, or amplify and share branded content or content that other influencers are producing.
Whatever mix of actions you want influencers to take, you’ll want to prioritize having them produce unique content. And that doesn’t mean retweeting an AI article written in HBR, adding hashtags, and tagging a few other influencers.
At the bare minimum, B2B tech influencers should be providing unique context or a point of view about that HBR article itself. If they were to say something like:
“This article on HBR has it all wrong … and here’s why: …. “
That’s a little better. But it’s still the bare minimum.
Ultimately, most of your influencer activation should focus on having influencers create long-form content, such as blogs, YouTube videos, and podcasts. This then becomes the distinction between thought leaders and influencers. Thought leaders provide their thoughts and perspectives on the issues. They are the leading voices in their industry. Yes, they might also be sharing articles, podcasts, and other forms of digital media, but they are the authority.
There are two reasons you should prioritize working with technology influencers that are content creators:
- Content visibility: The shelf-life of content created by thought leaders will index very quickly in Google and, shortly after that, will start to rank very high in the search results. This holds true for long-form content written on a blog, byline, or YouTube video.
- Shareability: Because thought leaders are developing new ideas, processes, methodologies, and answering/asking provocative questions, their content travels very far across the entire digital ecosystem. More importantly, it’s being shared by other influencers.
These two factors increase the probability that the influencer’s content will reach, influence, and persuade decision-makers as they navigate the complex buyer’s journey.
That said, when working with B2B tech influencers is that not all of them have to create unique content. In some cases, you will want to partner with influencers that are more content promoters. This means that they will publish and share branded content on their channels. These influencers are good at building community and generating engagement and conversation with their content.
Technology influencers being referenced by other influencers
Another way to validate real influence is to identify the influencers being mentioned or referenced by other influencers. You can get adjacent data like this by building an influencer map.
This reminds me of a project I did for an enterprise cloud security company in 2015. My day-to-day client worked in Analyst Relations, and she presented us with an exciting challenge. Her budget was cut by 45%, and she needed to decide which analyst firm she should invest in for the following year.
Here’s an abbreviated version of our approach:
We started with an industry analysis of the cloud security market. This gave us insight into which analyst firms and their research were being mentioned in the media. This step was only to find our data set; the results are what you’d expect. Gartner, Forrester, IDC, and 451 Research were the top firms.
We built complex Boolean queries for each firm, including brand names, published security-related reports over the last four years, specific analyst and researcher names, and their corresponding Twitter handles.
We collected all the articles where the reports were mentioned, documented were each ranked in Google, and how many inbound links each had. We also cross-referenced all the coverage against her top media list.
We tracked the shareability of each report across social media, calculated sentiment from the community, having discussions about it, and identified any influencers that referenced the research.
We analyzed the social profiles of each analyst and cross-referenced their audiences with other influential voices in the cloud security market.
Lastly, we contextualized the findings and made our recommendation.
Here’s the funny thing. The client did not take our recommendation. Instead, she decided that she was going to use her budget for Gartner’s Magic Quadrant. She said it was an internal decision and that company politics played a part.
Track the quality of the influencer audience
The first consideration in this post was to build an audience and then follow the data. The insights will reveal which influencers the audience has an affinity for. This is a similar approach but in reverse. In this case, we’ve first identified one or more influencers, and now we need to validate their audience.
Only a few influencer marketing platforms have this capability and work well for B2B and tech companies. You can specify audience attributes, interests, and affinities and find influencers with the highest percentage of those audience attributes.
Once you build your list, you can do the same. Most platforms will give you the basics-age, gender, family status, and location. They can also provide occupation and interests. So let’s assume that you are evaluating an influencer and 85% of their audience is interested in Business & Technology, and 65% are either Directors, Managers, CEOs, or Vice Presidents.
This data should factor into your analysis and provide a defendable approach to launching your B2B technology influencer program.
Final Thoughts on Working with Tech Influencers
The B2B tech landscape is filled with buzzwords and jargon. Terms like “Digital Transformation,” “Future of Work,” and now the “Metaverse” are used in the media and by companies and influencers everywhere. And they are being used in different forms and contexts when describing the business, technology, and the current digital landscape.
There is a goldmine of data and insights within these conversations. Here’s why:
By analyzing influencer conversations and media coverage related to topics relevant to your business, you can have a head start as to where the market may be headed in the near future. This data can inform your messaging, product strategy, and editorial approach. The benefit of doing this is twofold:
- Owned media and brand content will start appearing on Google for the keywords and phrases influencers are using and talking about.
- Social and other forms of digital content will align and relate to the more extensive discussion, positioning your brand as an authority on the topic.
This approach and method do not require any go-to-market program or influencer activation. It’s research that you can do to identify the top authority influencers in the space and inform your messaging strategy. And for starters, here are several curated tech influencer lists that have been pre-built using custom influencer scoring and analysis.