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.

You Answer to Nobody But Yourself

When I was young and impressionable (and still trying to make an impression), I believed – foolishly – that I had to answer to people. Whether that was my boss, colleagues or peers, I was under the impression I had to answer to them in all I did.

Now, before folks get the wrong impression, yes, it’s definitely important to have some form of hierarchy to get things done. This doesn’t necessarily mean a boss/employee relationship, though – think of it more like expertise and the wisdom to make the right things happen.

But the idea that you have to answer to someone because they say you have to? Screw that.

Just like trust and respect needs to be earned, so does answering to someone. You want me (or others) to listen to you? Show me you know your shit, and show me you’ll use that knowledge to do things the right way.

Which brings us back to the opening statement.

People in positions of power may feel you have to answer to them, because their job title says so. But here’s the thing – people don’t stay in companies for 25 years or more anymore.

People also see through BS faster, and know that – thanks to social media – it’s easier to be connected to someone that can help them make their next move than it was just five years ago, when an old boy network and a good suit was the “in” to a new position.

What this means is that employees don’t need to take the kind of shit anymore that they used to stay silent about. Nor do they have to worry about a damaged reputation, since the truth always comes out. Always.

Instead, now people can choose what really matters to them – respect, reputation, family. Instead of answering to those that don’t deserve it, you now answer to those that truly matter.

Which, at the end of the day, is where the real rewards are anyway…

Introducing the @JugnooMe Tweet Visualyzer – Buzz Visualized

Over at Jugnoo, one of the things we’re spending a lot of R&D time on is natural language, and how conversations and people truly connect to each other.

It’s all well and good having a social monitoring platform that pops up keywords and alerts for you to track, but without the context of what these words mean and the bigger picture around them, then monitoring continues to be purely reactive.

To help us move toward our goal, we’ve just released our Tweet Visualyzer (or Buzz Visualized – your choice!).

So how does it work?

There are seven tabs – What, When, Who, Word, How, Group and Tag Cloud. Each tab offers a different view, with information that can be broken down into individual tweets, words, platforms and more.

1. What

The first tab shows what’s being said and shows the top five topics as sorted by groups. As well as the groups showing the top five topics, it also shows you the people talking within that group. This can help brands identify who they should be connecting with for a promotion or outreach program, amongst other things.

2. When

The second tab shows the time of day of tweets shared. The great thing about this is it allows you to see when the most popular time for certain topics are which, again, can help businesses determine when they need to be on Twitter to reach a certain audience.

3. Who

The third tab shows the most active tweeter on a certain topic. For many businesses, knowing who’s most active helps filter down Instigators – perfect for identifying potential partners for a promotion, or connecting with brand advocates who are already promoting your brand.

4. Word

The fourth tab is where things really start to get interesting. As I mentioned at the start, Jugnoo’s looking to show how conversations and people relate to each other, and the context behind these conversations. By using the Word tab, you can now see how people group around a certain word. Highlight more words, and you’ll see which of these people roam between conversations. The likelihood of these people being the glue that ties all these interconnected groups of people together grows, and lets you see who you should be connecting with.

5. How

The fifth tab is a simple and quick way to see how people are tweeting. The reason we included it in the visualyzer is simple – by knowing what people are using, you can define your approach better. If you see a lot of people are using mobile browsers, then it can determine whether you need to concentrate more on mobile campaigns, or optimize your website for mobile visitors.

6. Group

The sixth tab complements the Word tab, and gives you a quick look at how people split into sub-groups around similar words. Again, this can help brands identify where conversations are taking place around keywords in their industry, and where people are drifting in and out of that conversation at a given time (if the keyword changes, for example).

7. Tag Cloud

The last tab gives you a look at all the words associated with your original keyword or hashtag search. This cloud is made up of people, words and any hashtag associated with that search. You can highlight as many words as you wish, which will the show you the Twitter users connected to these conversations. From there, you choose to view a new tag cloud that drills deeper into the new search. Again, this is ideal for really understanding the perception people have of you and your brand.

While it’s still a work-in-progress, we’re really happy with the way the Tweet Visualyzer is driving us to where we need to be, as far as context, conversations and natural language goes.

Even in this early build, we’re already seeing how it can connect the dots between the various pieces of an online conversation. As we evolve it, we’ll be adding other platforms to the mix too, and it’ll become a fully-fledged part of our monitoring and lead generation solutions (which I’ll be sharing more of in the near future).

The Tweet Visualyzer is currently open for everyone to use while we’re still in beta, so hop on over and try it out with your own searches – I look forward to hearing your feedback!

Note – once we come out of beta in the next month or so, we’ll be making the visualyzer a core part of our platform. You can sign up here (it’s currently free to use) to make sure you get full access to our suite of products.

How Much Listening Does Social Media Listening Really Offer?

Social media listening.?Social media monitoring.?Social media tracking.?Social media intelligence.

There are many descriptions of how we can use social media as a listening tool, to complement (or replace) our more interactive approach where we converse too.

While the idea behind social media listening is cool ? after all, who doesn?t want to know what?s being said about them, by who and when? ? the current tools don?t easily offer the kind of listening that would be really useful.

Listening Data is Still Keyword Driven

Whether it?s free tools (Twitter Search or Google Alerts) or premium offerings, the main issue with social media listening is that it?s still (primarily) driven by keywords.

So, for example, if you wanted to know about your brand, you?d type in something like ?brand name?, or ? if you want to filter a bit ? ?brand name + brand service + brand product reviews.?

The latter filter means you can narrow down the keywords to include the types of products or services you sell directly, or just the industry you?re in. This helps you keep tabs on competitors as well as customer pain points.

But it?s this approach where things fall down.

People Are Not Scripted Robots

In an ideal world, we?d be able to search for these keywords in social conversations, and they?d lead us to the Holy Grail of sales. After all, it works for Google on Search, right?

The problem is, people are not conducive when it comes to creating an ideal world for brands to operate in. We?re too human, for a start.

That means we don?t play nicely with scripted conversations and perfect keywords.

Instead, we talk naturally the same way we do offline, and in conversations that ? at first glance ? have nothing to do with the keywords that we may have keyed into our listening tools filter.

For instance, say my furnace breaks. If I wanted to find someone on search, I?d type in ?HVAC companies in my hometown.? That would help me find the right people to get my issue fixed.

However, I?m not necessarily going to go onto Twitter and ask, since my followers probably don?t live in my town, so would struggle to advise me of a reputable company near me.

So, if I?m an HVAC company using listening tools to find new customers, a search for ?broken furnace? may or may not be productive for me.

However, if I was smart and could look for natural conversations, I?d be much more likely to gain the lead.

Speaking Comes Naturally

Using the HVAC example, let?s say instead of using the term ?my furnace is broken? on Facebook, we?re (as in my friends and I) having a conversation around the topic, but not coming out directly and saying it.

Instead, all I?m saying is ?I hate having a cold house, I?m going to have to wear extra long johns!? (or words to that effect).

Having a cold house immediately suggests a heating issue: do I have heaters, can I not afford to switch them on, is my window broken, is my furnace broken (a-ha, the furnace!)?

By filtering a social search for these natural conversations, I?m zoning in on the real issue, versus what I?m hoping someone will be talking about.

I can then reach out and say, ?Hi, USER X, we hate cold houses too! Anything we can help with (we?re out of blankets though!)??

It?s a gentle way to join the conversation, and immediately asking for the sale if there?s a potential sale there.

By ignoring the obvious and scripted keywords, and instead being more intelligent and tracking the natural conversations, we can access so much more information (maybe even the Big Data that everyone is swooning over at the minute).

Additionally, we?re not limiting ourselves to one pain point.

Looking at the results, it could be an opportunity to provide heaters in the first place (retailer), help manage finances better (financial advisor/bank), or fix the window (glazier).

Four opportunities to get involved from one search? Yes please!

Is It This Simple?

It can be. Even without the advanced algorithms that these types of natural searches need to really decipher the content, you can put the legwork in to start identifying the true conversation behind the words.

The trouble with legwork is that many companies and business owners don?t have the resources for that. Nor do they have the finances to pay a solution provider the kind of money these smart algorithms would cost.

But this could be a wake-up call for vendors. After all, if you can provide this kind of smart learning that really benefits all sides (and not just those doing the listening)? Well, that?s the gold right there.

Challenge on.

This post originally appeared on Waxing Unlyrical.