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.

Beyond Social Scoring – The Situational Factor of Influence

If you thought influence marketing was a hot topic at the moment for marketers and brands, it?s only just beginning to really take shape.

While much of the conversation both here on this blog and across various networks has concentrated on where social influence is today, this is a just the prelude to where influence marketing will be tomorrow and beyond.

In the next few weeks,?our book will be released?and we?re excited to share the concepts and methodologies that we?ve come up with in both our research for the book as well as real-life case studies we?re documenting with our clients, using our framework.

Our goal with the book is simple ? while early movers in the social influence space have provided a starting point for brands to understand this tactic, the real business value requires actions and solutions that go deeper than a score and an ?influencer? based on amplification and popularity.

Additionally, online influence is just one component of a very large picture, and only paints a small part of that same picture. Let?s talk about that a little more today.

Decisions Based on Limited Information

Social influence data as it stands today is based primarily on one core metric: public social profiles and footprints. So if you have your Twitter account set to public, then companies like Klout and Kred will create you a ?profile? and allocate you a score, based on their algorithm.

If you sign up and connect your other accounts, like Facebook, LinkedIn and Google+, the score will change, since these companies now have more information about you. So far, so good.

The problem comes when the accounts aren?t set to public, or you have different privacy settings for different accounts. So, Twitter and Google+ may be public, but Facebook may be primarily for friends, so your sharing method on that network is very different.

But let?s say it?s these private conversations where the decisions on the majority of the choices you make are made, when it comes to making a purchase.

These choices are the ones that are defining the influence factor at that time:

Is it situational, where your current situation (financial, need for a product or service, etc) comes into play?
Is it emotional, where the desire for something outweighs the logic of not actually needing it?
Is it personal, where your partner/wife/husband puts the foot down and says no?

These are three simple factors that can?t be measured directly ? and yet they have a direct impact on you as a person, because they influence your decision.

Because this process isn?t measured by public scoring algorithms, it can lead to distortion of data when measuring a brand influencer program.

You may have initially shown positive signs of interest in a new product launch, as featured on an influential blog, and that would go down as a success metric. But the truth is, the real influence was exerted when the situation came into play in your private conversation(s).

It?s this missed data that (currently) limits the reporting metrics on some of today?s platforms.

The Offline Influence Equation

Another part of this equation is the fact that most influence platforms don?t take into account what happens offline ? they simply measure online noise and conversations.

While this approach still allows for a lot of data to be collated about someone and their influence, as well as who and what influences them in return, it?s still only half the big picture.

As Pierre-Loic Assayag mentioned when we interviewed him about?the approach his Traackr platform takes, imagine trying to decide a large bank loan with only half the financial information about a person available to you ? you just wouldn?t make that call.

In fairness, this limitation is being recognized by the influence platform developers. Kred, for example, allows you to upload your offline achievements (although they don?t validate them so you could still upload false information), while Appinions measures reactions and opinions from traditional media as well as online publications.

However, as much as we try and measure how offline decisions impact measurable public conversations online, there?s still the question of what truly impacted the decision to take an action or decide to pass at this moment in time?

To get to that stage, we need to move beyond just public personas when it comes to influence, and begin to look at the macro and micro influencer level, and where they sit in the influence circle around each of us.

In the next few weeks, we?ll be doing just that. We look forward to sharing with you.

A version of this post originally appeared on the official Influence Marketing blog.

The Question of Reach as a Viable Metric

Last week, I posted the following update across a couple of networks: “Please don’t use ‘Reach’ as a viable metric. It’s a BS number to get clients to pay more for data: don’t go down that road.”

The update resulted in some great discussion on both sides, with agreement and counterpoints on how viable reach is as a metric.

These included:

Let’s not be so quick to disregard Reach. After all, big companies buy Superbowl spots exactly for the Reach it gives them. – Dino Dogan.
Reach has 2 parts. How many people saw something (actual reach) and how many potentially could see something (fictitious reach). If I have a reach of 2 million but at the time I post every day only 3 people see the post what is the real reach? 3. – Howie Goldfarb.
Reach is definitely?ephemeral because reach doesn’t really matter. Action does. Click throughs, downloads, sticky site traffic, purchases, that kind of thing is what really matters. – Shelly Kramer.
But what about quantifiable reach? Meaning, reach is tracked against response & metrics? – Mitch Arno.

All good points – yet (for me personally, anyhoo), I’d disagree on Dino and Mitch’s points on when reach could be used as a viable metric. Here’s why.

The Attraction of Reach

By definition, reach is simply a potential number. It can be broken down a few ways:

On social networks, reach can be the amount of people that may interact with your content, through either seeing it directly, or through one of their connections, or even a social ad;
On blogs, reach can be the amount of people that interacted with your post, through direct readership, a shared link, or a forwarded email;
On media, reach can be the amount of people that could see a TV show, a print ad, billboards, etc, through direct contact or shared discussion later.

Marketers like to use reach as a client metric because it sounds impressive. Instead of having to be restricted by real actionable data, reach can be used instead.

“Twitter User X has 1,000 followers, but a reach of 100,000. That’s 100,000 new customers just waiting for us.”
“Blogger Y has 10,000 subscribers as well as 1,000 followers. Even more new customers just waiting for us.”
Free Local Newspaper Z has a reach of 50,000 homes delivered to. That’s 50,000 new customers waiting for us.”

And so on, and so on. Which would all be great and dandy if reach was a viable metric, but it’s not.

The Problem With Reach

The reason reach isn’t truly viable as a metric is simple – it’s based on the hope that eyeballs are available.

On Twitter, for example, reach is defined by the potential audience of a user you’re connecting with. So, someone may have 1,000 followers, but the followers of these connections combined may equal 100,000 (at least).

When User X with the 1,000 followers tweets something, the hope is that person’s followers will see the tweet and reshare with their audience. If a follower has 100 followers themselves, that’s now another 100 eyeballs to potentially see the share. Potentially being the key word.

Because no-one is online all the time, just waiting for a tweet. And that’s just the live, organic stuff – when you add bots and fake followers into the equation, things become even less impressive, as we can see by the following example of the same Twitter power user.

In the image above (click to expand), I used TweetReach to gauge the potential reach and visibility a certain power user could offer. The user in question has over 217,000 followers.

As you can see from the image, the estimated reach is just short of 200,000, with potential exposure (followers of followers) at just over 2.6 million. Impressive, right?

But this is where reach as a metric falls down, as we can see in the next image.

Using the Fake Follower Check software from Status People, I entered the same user’s details, to see how many of his 217,000+ followers were real. The definition of “real” here is simple – active and not bots or fake accounts.

As you can see by the image above, there’s a huge disconnect between how many of this user’s 217,000 followers are classed as real, active followers.

Suddenly, instead of having access to a potential 2.6 million impressions (which is what the potential reach of the followers pre-fake check would give), you’re now down to 182,000. Still impressive, but a hell of a lot less than 2.6 million.

And that’s assuming that each of the 182,000 “real” numbers are around when this power user sends out a tweet.

This is why reach is such a crappy metric to be using – and yet many marketers use it to increase their rates when charging clients for audience size.

The Real “Reach” Metrics

To Dino and Mitch’s earlier points at the start of this post – I agree, to a small degree, where reach is used by the likes of the Super Bowl ad buy agencies, as well as quantifying the reach. But there’s still the overarching problem that it’s a hit-and-hope metric.

In the Super Bowl example, companies use data from Nielsen, one of the world’s leading audience measurement companies – but it’s aggregated data based on average audience behaviour, versus specific targeted individual behaviour. This means it doesn’t take into account people getting up during ads to grab more beer, food, etc.

With Mitch’s example of quantifying reach, this gets closer to viable metrics, but it’s still relying on the bigger number that can’t be quantified. If we move the conversation over to quantifiable metrics based on more in-depth filtering, then we can get more actionable insights.

Ignore the big number and target the demographic instead – male/female, locale, language, age;
Use search history to identify common keywords and themes relevant to your brand;
Use software like oneQube to identify when users are on Twitter, for instance, and who they’re talking to. Do the same with software relevant to the platform you’re interested in;
Collate this information with Google Analytics or similar to understand what content is attractive and what content was physically shared and acted upon;
Set goals based on real action (as Shelly mentioned in her examples) – click throughs, recommendations, downloads/purchases, referrals, etc;
Compare these actions to the target audience size to determine reach vs. actual ratio.

By doing this, you’re now beginning to bypass reach alone and get to the real nitty gritty – ?your true audience size, as well as the real numbers to filter and use as a proper business metric.

Reach itself can be a starting point when it comes to social proof and how many eyeballs could be reached – but only as a starting point. You need to then do the legwork to define your captive audience.

Otherwise you’re constantly just reaching for what could be – and few businesses, if any, can live on that alone.

Moving Influence Beyond Public Personas

If you thought influence marketing was a hot topic at the moment for marketers and brands, it’s only just beginning to really take shape.

In the next few weeks, our book will be released and we’re excited to share the concepts and methodologies that we’ve come up with in both our research for the book as well as real-life case studies we’re documenting with our clients, using our framework.

Our goal with the book is simple – while early movers in the social influence space have provided a starting point for brands to understand this tactic, the real business value requires actions and solutions that go deeper than a score and an “influencer” based on amplification and popularity.

Additionally, online influence is just one component of a very large picture, and only paints a small part of that same picture. Let’s talk about that a little more today.

Decisions Based on Limited Information

Social influence data as it stands today is based primarily on one core metric: public social profiles and footprints. So if you have your Twitter account set to public, then companies like Klout and Kred will create you a “profile” and allocate you a score, based on their algorithm.

If you sign up and connect your other accounts, like Facebook, LinkedIn and Google+, the score will change, since these companies now have more information about you. So far, so good.

The problem comes when the accounts aren’t set to public, or you have different privacy settings for different accounts. So, Twitter and Google+ may be public, but Facebook may be primarily for friends, so your sharing method on that network is very different.

But let’s say it’s these private conversations where the decisions on the majority of the choices you make are made, when it comes to making a purchase.

These choices are the ones that are defining the influence factor at that time:

Is it situational, where your current situation (financial, need for a product or service, etc) comes into play?
Is it emotional, where the desire for something outweighs the logic of not actually needing it?
Is it personal, where your partner/wife/husband puts the foot down and says no?

These are three simple factors that can’t be measured directly – and yet they have a direct impact on you as a person, because they influence your decision.

Because this process isn’t measured by public scoring algorithms, it can lead to distortion of data when measuring a brand influencer program.

It’s this missed data that (currently) limits the reporting metrics on some of today’s platforms.

The Offline Influence Equation

Another part of this equation is the fact that most influence platforms don’t take into account what happens offline – they simply measure online noise and conversations.

While this approach still allows for a lot of data to be collated about someone and their influence, as well as who and what influences them in return, it’s still only half the big picture.

As Pierre-Loic Assayag mentioned when we interviewed him about the approach his Traackr platform takes, imagine trying to decide a large bank loan with only half the financial information about a person available to you – you just wouldn’t make that call.

In fairness, this limitation is being recognized by the influence platform developers. Kred, for example, allows you to upload your offline achievements (although they don’t validate them so you could still upload false information), while Appinions measures reactions and opinions from traditional media as well as online publications.

However, as much as we try and measure how offline decisions impact measurable public conversations online, there’s still the question of what truly impacted the decision to take an action or decide to pass at this moment in time?

In the next few weeks, we’ll be doing just that. We look forward to sharing with you.

The Fallacy of Transparency in Social Media

Spend any amount of time around social media conversations, and one word usually pops up more than any other – transparency.

People talk about social media empowering consumers, because now brands have to be “transparent” in every communication.

People talk about social media sorting the wheat from the chaff, because Google is their friend and ideas can be challenged.

People talk about snake oil salesmen losing their grip because transparency (or lack of) will eventually show the frauds from the real deal.

All good ideals. All good hopes. If it were really true.

Transparent Only If We’re Allowed to Be

The thing is, this whole “transparency thing” in social media isn’t actually happening, because we’re essentially not allowing it to happen.

There’s this unwritten rule in social media that it’s best to focus on what you can achieve versus calling out fakes and bad practices. It’s the way the social web works best, folks say.

And that may be true – but then that approach also dilutes the whole transparency argument too.

For example, there’s a very well-known blogger-turned-author in the U.S. that talks a lot about community and how humble he is to have one of the best. Yet the same blogger is quick to send nasty emails to people who don’t offer anything but platitudes for his book(s).

Then there’s the Canadian social media guy who talks a lot about how to be active online, but – much like his American counterpart – sends rather nasty emails and direct messages on Twitter to folks who dare to question his approach.

You’ll notice I didn’t refer to these two people by names (and there are many more like them). Because, as I mentioned earlier, it’s just not done in social media. People call you a hater, and you’re seen as unprofessional.

Transparency, indeed.

Rewarding Silence

Yet should we really care? After all, as so many people say, we should concentrate on what we do, right, not what others do?

The thing is, if we do that when the behaviour of some people verges on bullying, by staying silent we’re encouraging this behaviour. We’re essentially saying, “You know what, you continue to show one face in public and a completely different one in private, because it doesn’t affect us.”

But it does affect us.

It’s our friends that are being picked on. It’s our colleagues that are being affected. And, most importantly, it’s our morals that are being compromised by staying silent.

So what do we do? Do we do anything? Do we contact these people directly and say we know what’s happening and try stop it? Do we publicly question them? Or do we continue with this idea that social media has made everything transparent, so leave the status quo as it is?

The decision is yours.