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Influencer Marketing in B2B (as in Back To Basics) With @markwschaefer

Influencer marketing is getting big. Here and there, a lot of noise is made about instagram influencers and suchlike. With sponsored posts reaching a €2,000 pricetag in France and up to £75,000 in the UK, “influence” is becoming big business indeed. Even though some marketeers are still wondering whether what they are doing is the right thing and besides some people are trying to abuse the system

There are two SocialPR ambassadresses I often refer to. The first is Shonali Burke, the second is Lisa Buyer.  Both definitely worth following. Check out this in interview of Shonali Burke on the Influencer management platform Traackr 

New Post has been published on http://www.learn-digital-marketing.com/top-50-people-most-retweeted-by-digital-marketers-what-does-it-mean/

Top 50 People Most ReTweeted by Digital Marketers – What Does It Mean?

When identifying influencers as part of your social media and content marketing program, topic match and popularity are not enough to qualify an influencer as “effective”.

By effective, I mean the ability and likelihood that a person can actually inspire action amongst a community.

To determine the effectiveness dimension, it’s important to use tools that look at other criteria such as the extent to which people respond and take action in response to a person. When it comes to Twitter, things like ReTweets and sharing of links are signals worth looking at.

To shine a light on the digital marketing category, Leadtail and Punchtab have published a new report (h/t SocialFresh) “How Digital Marketers Engage on Twitter” that includes a list of publishers and people that are the most often mentioned and ReTweeted by digital marketers. The report also includes topics that digital marketers are discussing on Twitter and their top content sources. (download report here)

Discover, Consume, Act:

The information in reports like this one can be pretty useful for understanding how influencers interact with social content. The formula is pretty straightforward:  How do influencers discover new information, what are their preferences for content consumption and engagement, which topical triggers will inspire them to take action?

If you’re working in the digital marketing influencer space, this kind of report can be insightful. Keep in mind, it’s a snapshot of interactions and activity over a 2 month period of time, vs. an extended period.

Congratulations to the many people in the digital marketing and PR space that appear in the list – your curating and sharing is what makes the social web go ’round!

There are several lists and word clouds in the report, but here’s the list of the 50 most ReTweeted by Digital Marketers. Yes, I’m as surprised as you are to see me in the #5 slot just below Jeremiah Owyang and above Guy Kawasaki:

1. Jay Baer – @jaybaer 2. Vala Afshar – @ValaAfshar 3. Chris Brogan – @chrisbrogan 4. Jeremiah Owyang – @jowyang 5. Lee Odden – @leeodden 6. Guy Kawasaki – @GuyKawasaki 7. Brian Solis – @briansolis 8. Ann Handley – @MarketingProfs 9. Danny Sullivan – @dannysullivan 10. Darren Rovell – @darrenrovell 11. Mark Johnson – @MJohnsonLoyalty 12. R Ray Wang – @rwang0 13. Sean Gardner – @2morrowknight 14. Richard Branson – @richardbranson 15. Maria Popova – @brainpicker 16. Mark W Schafer – @markwschaefer 17. Amber Naslund – @AmberCadabra 18. Jeff Bullas – @jeffbullas 19. Glen Gilmore – @GlenGilmore 20. Mari Smith – @MariSmith 21. Shelly Kramer – @ShellyKramer 22. Michael Brenner – @BrennerMichael 23. Barack Obama – @BarackObama 24. Rainn Wilson – @rainnwilson 25. Neil Tyson Degrasse – @neiltyson 26. Anil Dash – @anildash 27. Anthony DeRosa – @AntDeRosa 28. Ann Tran – @AnnTran_ 29. Bruce Van Horn – @BruceVH 30. Nick Bilton – @nickbilton 31. Peter Shankman – @petershankman 32. Mark Ragan – @MarkRaganCEO 33. Dan Primack – @danprimack 34. Brian Fanzo – @iSocial_Fanz 35. Mack Collier – @MackCollier 36. Tim Siedel – @badbanana 37. Ted Rubin – @TedRubin 38. Chris Voss – @CHRISVOSS 39. Gerry Moran – @GerryMoran 40. Brian Morrissey – @bmorrissey 41. Heidi Cohen – @heidicohen 42. Lolly Daskal – @LollyDaskal 43. Stephen Colbert – @StephenAtHome 44. Magic Johnson – @MagicJohnson 45. George Takei – @GeorgeTakei 46. Ariana Huffington – @ariannahuff 47. Marc Andreessen- @pmarca 48. Elon Musk – @elonmusk 49. Kim Garst – @kimgarst 50. Gary Vaynerchuk – @garyvee

I’m sure people are wondering, “How do you get ReTweeted more often than “real” business celebrities like Richard Branson or Ariana Huffington?

Clearly those with large networks and that consistently share useful information are going to be engaged with and mentioned more often.

Additionally, if someone on a list like this is an active public speaker and smart about promoting live tweeting during their presentations, they’re going to rank pretty high. Also, if you’re a guest on several Twitter chats during the sample period, that can boost RT numbers too. Those of us that work with this kind of project and data will dig and dig until we find answers so we can develop an informed approach.

With lists like this, it’s worth making the effort to distinguish the merit of the influencer over time vs. the merit of the moment because of events. High engagement for both situations is great – it’s just that you may want to approach influencers differently based on where they’re getting that engagement from. Ex: Connecting via a Twitter chat vs. pitching via email.

Another consideration for lists that are samples from social networks like Twitter is that engagement levels for many influencers is dynamic.

Taking a took at the past 30 days of RT + Twitter handles for the top 3 on the most ReTweeted list, @ValaAfshar (CMO at Extreme Networks) clearly dominates when factoring in all Twitter users vs. just digital marketers. That’s something to consider as you evaluate influencers as effective over time with a broader audience.

What else can you do with a list like this?

Part of the identification and recruiting of influencers involves networking your way into their social field of view. For example, I’m not connected to every relevant digital marketing person on this list but there could be mutual connections that could be leveraged.

To find out where those connection opportunities might be, I logged in to a tool called Traackr, which has an awesome new(ish) feature that allows you to import a list of Twitter handles to create a Group or Project. From there you can get info on the other social networks the influencers are active on, latest content published or shared and a sweet visualization of how they’re connected. Disclaimer: Traackr provides me a limited version of their tool with no obligation.

For this post, I imported the list of 50 people most ReTweeted by Digital Marketers above and filtered down to those I have the strongest connections with. You can do this for any known entity discovered through the influencer search or for those who you import.

From here you can click on any “node” to see specific connections and even social network data for each person. I’m showing a visualization here, but you can see the info in a more tabular format too.  It also suggests other influencers you may want to add based on characteristics of the list you imported. It’s a pretty cool tool actually and I’ve found myself using it more often.

Who influences the influencers?

Another approach to take with lists like this is to find out who influences the influencers you would like to connect with.

In this view, the blue lines pointing inwards represent influencers of the influencer in question.  The idea here would be the “influenced by” dimension can help reveal introduction and engagement opportunities by identifying the second level influencers you’re already connected with. For example, if you’re already connected with Kim Garst and Mark Schaefer (lucky you) those connections could be useful in a pitch to Jay: “We already have Kim and Mark on board and would love to have you too…”

How you execute on these opportunities for connecting with influencers depends on which networks you already have connections on, timeframe, and what you want them to do.

You could also use a tool like BuzzSumo to drill down into the influencer’s blog and see who is sharing their posts. Additionally, you can use BuzzSumo to get a list of the links shared by a particular influencer on Twitter to see who they are often pointing to. You can drill down on each of those shares to see other influencers sharing the same link. Most of the data from BuzzSumo can be exported so you can crunch away.

There are many ways to use lists like this to identify influencers and influencer engagement opportunities. The good and bad news of tools is that there are way too many specialized tools that do the same kind of thing and very few that do most of the things you might want to do.  Rest assured, I’ll continue testing and share tools here.

Congratulations to everyone and the publications included in this report. It can be very satisfying to learn from 3rd party sources that the social content you’re sharing has resonated with a relevant audience.

If you were making a short list of digital marketing publications and another list of individuals, who would you include?

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Congratulations to Team TwitterTV (Jony F, Justin S, Todd C, Chris K, and Jie Z) for taking top prize at the Hopper ElasticSearch Hackathon for their utilization of ElasticSearch to create interactive visualizations of the top 150 TV shows trending on Twitter. Summaries of the other five team (or individual) presentations are below, and viewable on ChallengePost. Thank you to everyone who participated, and to our generous sponsors ElasticSearch, Traackr, and SoftLayer! 

- Exploring the Special Relativity of Politics (Aki B, Siva C, Vaidehi V) came in 2nd place winning a seat in ElasticSearch Training for one lucky team member! They filtered tweets by topic (Obama, McCain, Obamacare, Rowhani) and measured sentiment to "analyze the overall vibe around each topic by gathering aggregates of the positive and negative words"

- Enron Connections (Marty J and Peak X) queried the Enron data set (~500,000 emails) to quantify the connections between all the email participants and determine the degrees of separation between people. They created drop-down lists to facilitate the comparison of any two participants in their exploration of the "6 degrees of Kenneth Lay."

- Cluster in Azure - Boom on Load (Chris M) built an ElasticSearch cluster in Azure running on six machines and devised to create a map that showed "influencers near a given city", but he unfortunately encountered a few problems and ended up learning a lot about troubleshooting the ES cluster!

- Pathfinder (Sarah L) was inspired by the original form of the Wikipedia game 'Clicks to Hitler' and used ElasticSearch to generate the shortest optimal path between two Wikipedia articles. 

A few months ago Jack Dorsey (founder, CEO of Square) wrote a post & letter to his employees condemning the use of the word "users" to refer to Square's...well, users.  In his post, he compels his team to replace the term "user" with "customer" in all future communications.  The idea being that his team will build better products and offer better service to Customers vs Users.  It's worth a read - it offers an interesting perspective from a dude that is/has in many ways defined much of our modern web experiences.

With that said, I don't really agree with Jack in this case.  While I understand the main point and reasons for his stance (if Howard Shultz was on your board and asked the same question, you'd have the same reaction), I disagree with his extreem stance on the term user.

USERS ARE CUSTOMERS

Before you kick me out of SoMa (Jack's kingdom), let me explain.

At Traackr, we sell an enterprise software solution.  We have Customers.  And we also have Users. 

For us, Users are one segment of our Customer base - the segment of people who actually USE our product.  But we also have two segments of our Customer base who do not use our product (so we don't refer them as Users):

Our Customers Types/Segments = 

Buyers - People who write the checks and pay us for our product

Decision Makers - People who control the decision to select our product over some other option

Users - People who actually use our product

The breakdown of our Customer universe looks something like this:

The majority of our Customers are Users - and only Users.  Some of those Users are also Decision Makers (and vice-versa); some of our Decision Makers are also Buyers; but we don't have any Customers who are all three (that I know of).  

I think this is probably a fairly common pattern for most enterprise software offerings.  Consumer applications will have a different patter - in many cases, the vast majority of their Customers are Users (until, of course, they try to bring on advertisers).

WHY IS THIS IMPORTANT?

I would argue that breaking down & deeply understanding your Customer base is essential for great execution across the whole organization.  Using one blanket term to describe all your customers just isn't good enough.

When we develop/build our product, we focus mainly on Users (and a bit on the Decision Makers).

When we market our product, we focus mainly on the Decision Makers (and a bit on the Users).

When we sell our product, we focus mainly on the Decision Makers, but often have to convince all three Customer Types before closing a sale. So knowing them all is essential for our sales team.  

When we support our product, we focus completely on the Users.

GO EVEN DEEPER

And I don't think you can stop with these three, high-level buckets either.  You should go deeper.  At Traackr, we have broken down each of these Customer Types into very specific sub-types - each with a very specific & deep persona attached (persona building is probably worth another post).  We have:

3 different Buyer-types;

3 different Decision Maker-types; and 

6 different User-types

The point is - we need to know how to build for, market to, sell to, & support each one of these different people.  With every operational decision, we try very hard to understand for whom it is we are working.  For us, this is a robust exercise and ongoing process.      

JACK ISN'T SO WRONG...

In short, I partly agree with Jack.  Using USER as a universal term to describe your customers is not a good practice.  But, I don't have a problem with the term User.  I don't think it carries a negative connotation and I don't think it carries any less weight than the term Customer.  

The fact is, whatever terms you use isn't much more than a matter of semantics.  It's the understanding behind the terms that is most important.  The needs of someone who actually uses your application on a regular basis and the needs of someone who has the power to pay for your product are of equal importance.  

So, whatever language you use to describe these people isn't really the issue. Knowing, understanding and respecting them all as important stakeholders in your business is what really matters.

Traackr’s original model included three distinct data buckets: 1) Influencers, 2) Channels (sites for published content), and 3) Posts (tweets, blogs, etc.). Traackr creates influencer listings based on mining these data sets for keywords. If the information was only loosely coupled or if the wrong type of relationship festered for too long, inaccurate, inconsistent influencer rankings would result. In order to provide higher quality lists to clients, Traackr needed to build stronger associations within their data model, and HBase lacked indexing and ad-hoc querying capabilities to make this happen.

A few other MongoDB features are mentioned in the post, but the key is indexing and ad-hoc queries.

A couple of weeks ago I booked flights for my family's move to SanFrancisco. When I told my wife how much the tickets cost, she wondered why they were so cheap. It took me a second to think about it, but then I realized..."They're a one-way tickets, baby."The response landed with significance well beyond the price of the flights.I grew up in Boston. I moved away and spent some years in LA & NyC before returning for business school. I stayed in Boston for about 7 more years. I met my wife in Boston & we had our first son in Boston. My parents & siblings all live in an around Boston. I bleed Celtic green, know what it feels like to be a real Red Sox fan and don't miss a Pats game. (Hell - I was one of the many who cried upon seeing the old Garden being torn down from the perch of the 93 upper deck.) I don't remember a summer that didn't include road trips to Maine and at least one trip to one (or both) of the islands. I love the fall colors and even the first 5 snowfalls (after that...).

Boston is my home. But it was time to leave.

At Traackr, we realized late last year that Boston would not be our home for long. At the end of '09, we realized that we were onto something with the technology we were building and that we had a real shot to make it happen. We had bootstrapped hard to that point, building the technology and selling enough services on top of it to survive. But we felt strongly that we were onto something. So, like every good startup, we went out in search of financing. We HUSTLED for 10+ months. We met with a bunch of the local VCs (especially the 'early stage' VCs), pitched every angel group, went through due diligence, etc. We raised next to nothing. Nothing. Luckily we were able to continue to grow revenue to keep us alive, but even with that, many of us went unpaid and we were forced to continue our bootstrapping.

We then decided to give up on the Boston scene and head west to see if we could connect with some angels here. Long story short, within 3-4 months, we had commitments for more than we were initially trying to raise. We started with a couple of loose contacts and ended up with a full angel round. Of course, I'm simplifying the details, but the facts remain true.

So, that was great. Having some money in the bank was great (trust me). But more important than the money (which definitely helped) were the interactions we had with people on the west coast. It was the quality of the conversations. It was the excitement around what we were doing.

In Boston, we constantly felt as if we were bothering people. Meetings were hard to get. Cancelled frequently. And even when we scored meetings, most of them (not all), were focused on small issues, short-term thinking, searching for the negatives.  In the bay area, people were excited to talk to us. They quickly saw the big opportunity, saw beyond the short-term revenue (the Boston folks loved to talk about our gross margins -- seriously) and they wanted to get involved.

In some ways moving west was a very hard decision. In some ways it was a remarkably easy decision. And in many ways the decision was made for us (both us as Traackr & us as me and my wife). It didn't take long to realize that we had choices. We could stay in Boston and slowly fade away or we could move west and give this thing the oxygen it needs to, at the very least, have the opportunity to flourish. Like I said. Not a difficult decision.