Who Are My Advocates?

Identifying social media brand advocates has long been among a marketer’s aspirations. We all know that nothing carries cred like a happy, independent believer. And if that believer happens to have, say, a few hundred thousand social media followers, the boost to the brand can be enormous.

The corollary, sadly, is also true: make an enemy out of a highly-influential blogger, and you have a major PR issue on your hands.

Identifying both of them follows about the same course, so let’s stick with advocates. How can you figure out who is advocating on your behalf?

The answer lies in the combination of two “signals” that we identify in a text (in fact, the addition of one more can be a real refinement; more on that later).

The first, and obvious, signal is polarity (a.k.a. sentiment). It’s hard to consider someone an advocate if they don’t like you. So step one is to isolate posts where a positive, direct reference to your brand has been made. Essencient provides that information directly and with an industry-high level of accuracy.

Positive sentiment is not, on its own, a definite marker for advocacy. This is because advocates have more skin in the game than just having an opinion: they want you to have their opinion, too. So, they offer advice about what they advocate: they tell you to buy it, or consider it, or take some other (presumably constructive) action about it.

That’s as distinct from them just intending to do something themselves. “I like that new Beamer and I’m going to buy it” is a good thing, but not as strong an advocacy as “I like that new Beamer and you should buy it”. The offering of advice is a clear marker, with positive sentiment, of advocacy. Essencient, and only Essencient, provides the so-called Guidance signal that can identify advocacy.

There’s a good refinement available: Flamboyancy, another signal that Essencient (alone) provides. Flamboyancy measures how “flowery” the language is in a post. “I took a long, exciting test drive in that beautiful new Beamer.  You should buy it immediately!” is a far stronger endorsement and call to action than the last example above. Factoring Flamboyancy into the identification of advocates can only improve your results.

As I mentioned, the corollary to advocacy is detraction. Knowing who vocally dislikes your brand is pretty important, as well. And, of course, knowing who your competitor’s detractors are is a powerful insight as well. Identifying detractors differs from identifying advocates only in the sentiment being expressed (obviously, it will be negative for detractors).

So there it is: advocates and detractors identified. If you layer on reach or Klout scores, you can pinpoint who your greatest reward and risk bearers are and, through your engagement team, influence them appropriately.

Chasing 80%: Peripheral Sentiment

I recall that academic research performed in the past has demonstrated that determination of polarity in text (what we have come, perhaps incorrectly, to call “sentiment”) has an accuracy ceiling of about 80%. That is, given a body of statements, a team of human beings will not agree on the sentiment in those statements more than 80% of the time. That’s because, well, people have opinions.

So, the best we can hope to achieve in automated sentiment analysis would be that 80%. A lofty goal, indeed.

In an earlier post, I discussed the importance of World Knowledge in making good decisions: that knowledge we’ve gained from lining in our world that biases, hopefully correctly, the calls we make. Computers are not good at world knowledge, although we’re always trying to get better.

At Essencient, we have recently developed a concept that we call Peripheral Sentiment. Since our objective is not to make decisions for you, but to make sure that the texts you see are worthy of human evaluation, PS is a very useful thing.

PS says that for a given topic, if there is no directly measurable sentiment for or against it, but there is sentiment of some kind at the level of the entire text, some of that latter sentiment might be ascribed to the topic. Therefore, the text is probably important enough for human evaluation.

Here’s an example: “I stayed at Hotel Roger last night. The food was terrible.” World knowledge tells us that a hotel can be judged by its food. Therefore, this text could be considered negative about Hotel Roger, although nothing directly critical of that topic was said. Peripheral sentiment score: negative. Human, please take a look.

It’s not perfect. Consider this one: “Drove the Benz to dinner last night. The food was terrible.” You get it, of course: this says nothing bad about the car, since food and cars have no world knowledge relationship. In this case, we’d put this in front of a human, who would probably consider it unimportant (about Benz, that is).

Still, even with imperfections, it does make it more likely that texts with only indirect sentiment towards your brand will at least end up getting reviewed. That’s why PS takes us a step closer to the 80% mark. Expect to see more about PS going forward.

Can Social Leads Actually Pay Off?

Can Social Leads Actually Pay Off?

I’ve had many discussions in the past with customers about the viability of “social leads”, that is, leads mined organically from social media. The consensus has been that it’s an edgy proposition, and for many good reasons. In this post, I’d like to advance the thesis that social leads can be very viable if, and only if, we stop trying to take the qualification and go-no-go decisions out of the hands of those best equipped to make them.

Many social media processing offerings based upon Natural Language Processing set expectations that cannot be met. They promise a continuous stream of viable sales leads generated auto-magically in real time and injected seamlessly into your sales workflow. The sheer volume of social media, we are told, means that leads will simply pour into the funnel. Experience has shown, of course, that it doesn’t work like that.

First off, there’s nothing static or universal about what constitutes a lead, much less a qualified one. I remember a college friend reminding me that, “at two in the morning, any dance is a good dance.” Put another way, when the phones aren’t ringing, any lead is worth following up. The corollary is also true: when the team is under pressure, “I love my friend’s new phone” is probably not going to generate an intervention.

Not only does the definition of a good lead change according to circumstances, the decision to reach out to the social media user is always a matter of risk/reward: blatant intervention violates the privacy expectations of many users, and can really backfire on the brand. Only a trained team member can make that call.

Furthermore, the automatic injection of large quantities of probably-noisy social leads into the sales workflow can really tank the team’s KPIs. Metrics like percentage of opportunities closed, or even just percentage of opportunities addressed, can go right through the floor if the queues are flooded with noise masquerading as leads. Given a low conversion rate on social media interventions, many managers simply don’t want to risk degrading otherwise solid team performance.

So, what to do? Notwithstanding all these obstacles, the social lead generation channel is growing and maturing, and cannot simply be ignored. There’s gold somewhere in all that dirt.

We believe that the application of Essence Mining™ techniques to sales workflow can really boost sales performance. The key is to let your team decide which conversations they should act upon. They can do that, if they’re not overwhelmed by the volume of the lead funnel. Since most posts are noise, Essence Mining can surface the 5% or so of conversations that might actually lead to a sale. Once those conversations, and only those conversations, enter the workflow, your team can qualify them; action them if appropriate; quickly reduce the queue while maintaining or boosting KPIs; and, we may hope, actually generate significant profit and brand benefits from social media.

Essencient technology doesn’t try to decide what’s a lead and what isn’t for you, but just makes sure that what your team sees is worth seeing so you can treat social media exactly the same way you treat other, less noisy channels.

That’s how we see it but get in touch to let us know what you think.

Mining The Undisputed Automotive Gold Standard

Mining The Undisputed Automotive Gold Standard

The continuous onslaught of (artsy, racy, glitzy…) luxury automotive advertising must be effective. Why else would such vast sums be spent on influencing a choice that most of us make only every few years? Clearly, the average buyer is not going to race out and spend North of $60,000 for a luxury sedan on the strength of a 30-second spot, no matter how compelling. It’s about who we think of when we start thinking, “time for a new ride.”

So, who do we think of?

Essence Mining™ (EM) is the perfect methodology for answering that question. To do so, we set up Essencient profiles for each of the major luxury auto manufacturers and turned the analysis loose for two weeks. About six million tweets came in, and the EM engine determined that about 92.7% of them were just noise, and cleared them away. That left us with 438,000 important tweets that we could analyze using the Essencient for iPad app. What we learned was an eye opener.

Essencient for iPad’s  “Competition” view answers the question, “For a tweet focused on a brand, what other brands are most often mentioned by twitter users in the same tweet?” Although one can drill down from there, just the answer to that basic (but hard to answer) question reveals the gold standard.

We found that just about every luxury auto brand’s main competitor was the same brand. The gap between that brand and all others was significant, sometimes two to one. Twitter users with real intent and real opinions regarding luxury autos compared just about every other brand to this one.

And that brand is…

Mercedes Benz.

Duh, you may say. But would BMW or Lexus have been surprising? The competition is fierce, and costly: the real question is, why did Benz win?

They won by sheer brute force: according to Statista, in 2013 Benz topped the nearest US luxury competitor ad spend (Cadillac) by 14% and outspent BMW by almost three to one. The cost of being the gold standard? 323 million dollars.

By marshaling twitter traffic for a mere two weeks, and mining the essence of that traffic, we were able to see that Mercedes’ awareness strategy is working. We could also see what criteria were applied to the comparisons, and what issues drove intent to purchase (or not to purchase). We could even see how each brand was described across the tweets, which goes a long way towards explaining why that brand leadership stays sticky.

Does your brand have that kind of business intelligence?

By the way, people who mentioned Mercedes Benz tended to distribute their comparisons across brands like Range Rover, Jeep, Lexus, Audi and even Ferrari about equally, 10% or so against each. So the impact of that ad spend was pretty even regardless of competition.

Stay tuned for competitive analyses in other important market categories, including mobile devices and…beer.

What is Essence Mining™?

What is Essence Mining™?

What is Essence Mining™?

“Essence” is the “individual, real, or ultimate nature of a thing especially as opposed to its existence.” That’s a good starting point to explain Essence Mining.

More than 95% of your brand’s mentions on social media are “noise”. The other 5% are the super-important mentions that really merit your attention: the questions, the complaints, the recommendations. Essence Mining mines every social media interaction to find those that are of the essence for the development of your business. Essence Mining finds the truly essential comments that your customers expect you to notice – and which you don’t want to miss. If your business has a social media monitoring service then, unless you are already using Essence Mining, you are currently spending far too much on identifying the messages that you need to respond to.

As humans, we unconsciously extract the essence of everything we read and hear. It’s complicated. We detect signals from the express words, the sentiment, the tone and complexity of the language used; the context and punctuation all give clues, too. Innately we recognise irony, sarcasm, passion and spot flags that something is intended as a statement of fact, intent, joke or a threat.

Essencient’s proprietary and patent protected technology identifies many of those same signals. It allows us to automate the of assessment of the “hidden signals” in communications, and to process the combination of those signals to identify the essence (and, therefore, the importance) of a communication. Put another way, Essence Mining clears out the 95% noise leaving you with the 5% of mentions that matter. Your team can efficiently handle those important communications, without wasting time on the noise, and your analysts can transform the noise-free communications in to meaningful business intelligence. The result: better business performance at lower cost.

Which signals we monitor and how we combine them into a holistic view are a part of our “secret sauce”. But the proof is in the tasting – and we are confident that nobody can match us when it comes to delivering the essential part of the social conversation into your workflows and analyses. It’s our single, absolute focus, and the reason we have named our company “Essencient”. If you want to take up our challenge just contact us …