Latest posts from Danny Brown

Enjoy the latest posts from Danny Brown, and feel free to add your own thoughts in the comments after the post.

On Standing Up to Cyberbullying

Earlier this week, my ArCompany colleague Hessie Jones wrote a damning blog post on the state of social networks and their approaches to cyberbullying.

It’s a powerful read and looks at both sides of the coin – is it merely down to platforms to tackle, or users of the platforms as well, by speaking up when they see something wrong happening?

As someone who’s suffered bullying as a child, it struck home with me, especially now since online personas make it easy to target victim(s) behind a veil of anonymity.

Which is why I’ve started a Clipsi board around the topic of cyberbullying and where social networks fit in. I’ve covered the value of Clipsi as a news resource on this blog previously, so it made perfect sense to use this new platform.

Some statistics around the topic of cyberbullying:

Nearly 43% of kids have been bullied online. 1 in 4 has had it happen more than once.
Girls are about twice as likely as boys to be victims and perpetrators of cyber bullying.
About 58% of kids admit someone has said mean or hurtful things to them online. More than 4 out 10 say it has happened more than once.
Bullying victims are 2 to 9 times more likely to consider committing suicide.

That last statistic is tragically pertinent, with recent high visibility news stories highlighting the impact of cyberbullying on teens and what they see as the only way to escape.

Of course, cyberbullying isn’t restricted to teens, with adults coming under unwanted and threatening scrutiny. Clearly there is a major problem with today’s society and easier accessibility to people.

While we can’t stop it overnight, we can continue the process to eradicate it – or, at the very least, make it something that won’t be ignored. This Clipsi board is my way of joining the battle.

If you have any resources you’d like to share, please leave them in the comments below and I’ll add to the board. To follow the board and suggest resources, simply create a Clipsi account for yourself and hit the “Follow” button.

Let’s get started.

image: kid-josh

3 Reasons You’ll Hate the Influence Marketing Book

Back in May this year, Influence Marketing – the book I co-authored with Sam Fiorella – was published.

Published by the Que Biz-Tech imprint of business publisher Pearson, it was the result of 3-4 years of criticism of current influence models, as well as years of research, client work and case studies that highlighted what real influence means.

Since the book was published, a few folks have asked if the book would be of use to them, based on their goals, personal and professional. Instead of writing why the book would be a good fit, I thought it might be more fun to show why you’d hate the Influence Marketing book instead.

1. It Won’t Help You With Your Klout Score

When we first announced the book, a lot of people expected it to be an anti-Klout book, or anti-social scoring. After all, both Sam and I have been pretty vocal with our views on social scoring platforms and their take on influence.

However, contrary to popular belief, neither of us “hate” these platforms; nor do we discount the role they’ve played in starting the bigger conversation around influence within the social sphere, and what that looks like today.

That being said, we’re also realistic in what the likes of Klout can and can’t do, as this quote from the book shows:

We’re not suggesting that social scoring platforms are useless, only that basing influence marketing campaigns on them is shortsighted. To measurably and effectively generate business value from influence marketing, we must first understand and navigate the disruptive forces created by social media and the pervasive [social scoring] technologies previously outlined in Chapter 4.

One of my biggest “pet projects”, if you like, is the value of context when it comes to data, and for Sam and myself scoring platforms lack the level of contextual data needed to really define influence.

To that end, we share information on current social influence tools in Chapter 4, but that’s pretty much the only mention of these platforms. So if you’re looking to increase your Klout score or similar, this book isn’t for you.

2. It’s Not an Easy Read

When we first started the book process, one of the topics of discussion that came up was the language of the book. From the start, we knew that the direction of the book – a “true” business book versus a 101-type business book – would mean the language would need to complement the direction.

This meant deep conversations around text analytics, ontology, trend currents and more. Initially, the publisher wished for a simpler approach that would appeal to the everyday reader.

While we could have simplified the copy, that – for us – would have diluted the mature direction we wanted to move the influence conversation in. Full credit to our publisher, they acquiesced and allowed us to write the book we wanted.

Some reviews allude to the writing style – Alan Kelly mentions, “Beware, the authors do go geek. References to ontologies (p. 117) are spot-on and may scare the casual reader.” while Robert Clarke states, “…the tone and language felt a little too technical, and text-bookish for me.”

Funnily enough, the text book quip makes perfect sense, as Sam has already been approached by Rutgers to run one of their digital classes, and I’ll be presenting a 14-week course on Influence Marketing at Seneca College early next year. Since one of our goals was to make the book one that could be used in a scholastic setting, this was vindication we’d succeeded in that respect.

So, if you like an easy weekend read with little to make you stop and think, this book is not for you.

3. It Doesn’t Offer Short Cuts

Back in the “good old days” of marketing, there were no real shortcuts to identifying market opportunities and delivering strategies and tactics based on the information available to you.

Research was laborious, filtering data could be mind-numbing, and settling in for the long haul was expected when it came to setting goals and milestones for meeting these goals.

Enter social media and, by association, social scoring, and a lot of the legwork was taken care of – or so it would seem. Instead of having to research, identify and curate lists of target audience members, now you could pay a premium and have a ready-made list of “influencers” do your job for you.

Instead of having to correlate expenses to goals, what the success metrics would look like and how that impacted both top and bottom line, now you could promote the fact you got X amount of impressions and your social proof – Likes, retweets, etc., – was through the roof.

All well and good – except impressions, social proof and their ilk rarely equate to financial return on the scale needed to see the campaign recognized as a success.

In the book, we share the framework we’ve used, as well as the methodologies that will help your brand truly understand what influence is, and how to tie it directly to your Return on Investment (ROI) and profit metrics. But as we also point out in the book, this takes time and effort – lots and lots of effort.

If you’re looking for a quick buzz fire sale when it comes to influence and your brand, this book is not for you.

If You Can Get Past These Flaws…

So there you have it – three simple yet important reasons why you would probably hate Influence Marketing. Like any book, especially a non-fiction business book, it’s not for everyone, and I’d hate to see you disappointed with your purchase if you were to buy it.

However, if you can get past these flaws above, you’ll find why Nielsen BookScan recognized it as “one of the Top 100 Business Books in America”, and why Evy Wilkins, VP Marketing at Traackr said:

Sometimes a book comes along that changes the way we do business. Influence Marketing will be one of these books.

The choice is yours. If the three reasons here resonate, run for the hills and far away! If, on the other hand, that sounds the opposite of your approach, you can choose your preferred book retailer here.

Either way, don’t say you haven’t been warned… 😉

Ontology image: Francis Rowland

Without Context, Data is Meaningless

There’s a big push at the minute by marketers and technology vendors around the concept and importance of Big Data. Run a Google Search for the term and the resulting titles of posts, articles or books speak for themselves:

Big Data: The Next Frontier for Innovation, Competition and Productivity;
Big Data: A Revolution That Will Transform How We Live, Work and Think;
Big Data Transforms Business;
Put a Fork In Big Data – It’s Done (just to balance the positive/negative results).

So, Big Data is clearly big business, and – with more than 1.7 billion search results – something that businesses are looking to understand, come to grips with and benefit from.

That’s understandable – after all, the potential of Big Data is huge. In March 2012, no less an institution than the White House itself announced the Big Data Research and Development Initiative.

So, yes, Big Data = Big News.

The thing is, though, while access to such huge amounts of data helps us be better marketers and – by association – better businesses, there’s also the danger that we let this data inform our decisions, without stopping to think of that most important aspect of any data analysis – context.

Context Drives Educated and Informed Decisions

Think of any major decision you’ve made in life, either personally or professionally. While there will be examples of impulse buys or snap decisions made in the heat of the moment, the majority of your actions will be based on the context surrounding them.

I wanted the sports car, but it wasn’t kid-friendly;
Job A offered more money, but Job B offered me deeper satisfaction;
The penthouse condo in the city offered amazing views, but the suburb neighbourhood was safer.

Three very simple examples of decisions that looked at the bigger picture of context, and took into account the long-term view versus the short-term buzz. Each option would satisfy our basic instincts, but the latter option of each choice is the one I’d go for based on its deeper context.

It’s simple economics of educated decisions, based on the data available – yet as the following examples show, context is still being missed where it’s needed the most.

Visual Data is Great, Real Data is Better

Professional social network LinkedIn is continuously looking to increase connections and the viability of its service with new additions, some useful, others less so. At least, currently.

One of the new features they’ve released is the visual ability to see who’s viewed your updates, and how far they’ve spread. Visually, it’s pretty cool, as can be seen below:

The problem is, functionality-wise, it’s very limited.

While the image on the left tells me my update had 536 views, it doesn’t allow me to dive into the data to see who actually viewed the update. The same with the image on the right – I can’t click into the big purple circle to identify the type of people viewing my content.

The potential for this visual data is obvious – I can see if I’m attracting my target audience to my content – either potential clients or new employers – and, by having access to this information, tailor my sharing even more, as well as connect with these folks in particular.

It’s not just LinkedIn that’s missing the importance of context, though. Check out the image below from technology vendor Jugnoo?(click to expand):

The results are from a search around the words “social business”, and show not only the main keywords around the topic, but also who’s discussing them, via what platform, and the time they’re most likely to be discussed.

This basic data offers a simple overview of that particular search – but where’s the bigger context?

For example, you can see that “business” is the most discussed word, and then I’ve highlighted “product”, “agencies”, “customers” and “platform”. As you can see from the two yellow circles I’ve overlaid, a couple of people are in multiple results. So what’s the context behind that?

Is it because they’re connected to these different communities?
Is it because they’re seen as influential around these joint topics?
Is it because they’re more active than the other profiles?

Again, these are simple questions, but ones that the software doesn’t answer, or at least attempts to help with. Because of this, other software and analysis is needed to see how valuable these folks might be to my business.

That’s not to advocate lazy marketing, nor to forget about the legwork that real analysis requires. But if a software tool can’t provide further context around the solution it offers, why use that platform at all?

Dig Deeper, Think Bigger

And this is where Big Data’s main weakness can be found – it’s encouraging lazy solutions that seem to offer reams of data, but in reality offer very little. By doing so, it’s impacting the true potential of Big Data when used properly.

It’s this type of limitation that’s attracting valid critique of Big Data.

In his 2013 paper entitled Big Data for Development: From Information to Knowledge Societies, Martin Hilbert raised the concern that Big Data-led decisions are “informed by the world as it was in the past, or, at best, as it currently is.”

Last year, Harvard Business Review published an article, Good Data Won’t Guarantee Good Decisions, which highlighted the bigger issues around the data available to us today.

For all the breathless promises about the return on investment in Big Data, however, companies face a challenge. Investments in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision making.?Meeting these challenges requires anthropological skills and behavioral understanding?traits that are often in short supply in IT departments.

Simply put, we can have all the data in the world available to us, but unless we understand the context in which it’s presented, and the actions that will drive based on our analysis, we’re as effective as driving at night with the lights off.

It’s up to us to think bigger when it comes to Big Data, and start providing the context and meaning behind it, as opposed to just the “But it looks cool, right?” mindset that seems popular today.

Challenge on.

image: Kris Krug

The Fallacy of the Democratization of Social Influence

When we currently think of influence, we probably think of social scoring platforms like Klout, Kred and PeerIndex. These are the early adopters to the social influence space and, as such, have built an impressive level of awareness around their platforms and definition of influence.

Proponents of social scoring have praised Klout, as the most popular platform, for democratizing influence – allowing anyone to be an influencer regardless of audience size, social standing and location.

While it’s true that social scoring can start the process of finding influencers, it’s not quite as clear cut when it comes to being democratic around influence itself.

Social Scoring Silos the Elite

The problem with any scoring system is that it only rewards those with a high number. Want to buy a car? Tough luck if your FICO score is under a certain amount.

The same goes for social scoring in the influence space. Want to have a new Cadillac to test drive for a weekend? You better have a score over X amount. Free flight or upgrade to first class hotel accommodation? Make sure your score is high enough.

This engenders an “us against them” mentality.

Jane Average may be a better person to drive conversation and foot traffic to a car dealership because she’s a gearhead yet Joe Average, who has no intent to buy that car brand but has a higher Klout score because he’s more active online, is the one that gets the car keys.

This elite rewards system now causes another problem – it begins to affect the natural tone of online conversations, as those below the fold realize they can change their language online and be identified as an industry influencer because they’re speaking about a certain brand more.

As the online language changes, the algorithms are rendered ineffective because now everyone truly is an influencer – and yet, they’re clearly not.

The True Definition of Influence

Which brings us to the real crux about influence – who truly impacts how a decision is made and at what point in the purchase cycle of a customer does this decision get made?

Is it as a result of a socially active broadcaster, or someone else completely?
And, if it’s someone else, do social scoring platforms have the ability to identify that person?

My belief is that social scoring is not true influence, and that’s why the democratization of influence through social scoring is a flawed, if worthy, ideal.

It’s one of the reasons that an early mover like Kred is moving away from scoring as a defining metric. There are bigger pictures and scenarios at play at every single touchpoint of a customer’s journey through an influence-led path, and the results of who actually influences their decision may surprise you.

Yet it’s these decisions that truly matter to a brand when it comes to influence marketing – because scores and amplification will only get you so far. No company can remain in business on the amount of retweets and Facebook Likes they received alone.

The conversation around the future of influence is just getting started – and it’s not about an elite partygoer trading on online noise and a grade…

[vimeo]https://vimeo.com/65202873[/vimeo]

A version of this post first appeared on the Influence Marketing book blog.