Monthly Archives

April 2016

Be A Social Media Superstar: Your Cheat Sheet

By | How To | No Comments

We know that we process visual info much more rapidly than text (60,000 times faster in fact). This means that imagery is crucial to marketing strategies. In the past, we’ve shared how to make a post more shareable, and images are a big part of this.

But it’s not just about adding in images. In order to create the best ads, you have to know the proper dimensions for each platform. OnBlastBlog has created the ultimate cheat sheet for this:

Social Media Cheat SheetCredit: On Blast Blog

Then, don’t forget to track the success of the posts with our Most Effective Posts feature. Get started today!

Swimming In A Sea Of Data

By | Social Visualizations | No Comments

Data. We hear about all the data out in the world today. We’re swimming in a sea of it. Do we really understand how much data is out there or how to make sense of it?

Every day, we see:

  • 3.3B Google searches a day
  • 968 million people visit Facebook daily.
  • 500 million tweets sent a day
  • 75 million daily Instagram users.

But what does that actually look like? Take a look below, and if you need help making sense of your data, we’re here to help:

business intelligence

Use Your Words: How To Tweak Your Keyword Search

By | How To | No Comments

Last year, we shared our four main tips for tracking data with keywords. And this remains one of the areas we get more inquiries for. How do you make your searches more effective? How do you adjust the search? So, we’re here to help guide you to success!

Let’s start with the basics — what exactly is a keyword? A keyword is basically a search term. It doesn’t always need to be a single word. It can be a sentence; it can be a hashtag or a mixture of letters and numbers. When you start a keyword search, you begin searching all the available platforms for every mention of the term to be analysed and visualised.

Searches can get more advanced when you use a query. So, what is a query? A query is used to search social media and real-time data sources for mentions of your topic/project. Often to get the best results and pull in the most relevant and interesting data, one keyword is not enough. In this case, you may need to use multiple keywords, keyword filters or exclusions. So, basically, the full set of keywords and filters is known as a query.

Now, if you want to get more advanced, you can use a filter. A keyword filter allows you to filter your keywords through another set of keywords. This enables you to narrow down the number of mentions you are pulling in and look at more specific data. For example, if you wanted to look for all mentions of Nike trainers, your query would be the keyword “Nike” and you would put “trainers”, “trainer” and “sneakers” in the Keyword Filters section. This way you would only pull in mentions of Nike in the context of trainer conversation. Simple, no?

One final layer is a keyword exclusion. A keyword exclusion stops keywords coming into query results. Sometimes you may find a keyword brings unwanted data associated with another keyword. So, if you put a term in the keyword exclusion, it will stop mentions of your keyword in unwanted contexts. For example, if you are looking for mentions of Nike but don’t want to see any sales related conversation, your query would be the keyword “Nike” and you would put “sale”, “sell” and “deal” in the Keyword Exclusions section. This way you would only pull in mentions of Nike which are not related to selling items.

Now, that we have the basics down, let’s get to actually constructing your query. The best way to start is to ask yourself what are you really looking for. When constructing your query, it is generally best to have an idea of what kind of data you are looking for. Start with these questions:

  1. Are you looking for data around a brand, a product, a general topic or a specific campaign?
  2. If you are interested in a brand, do they use any specific hashtags or phrases in their social media communication?
  3. Does the name of the brand have other meanings?

Then you need to know how to choose your keywords. If you are looking for a specific brand, it is best to start with their social platforms. Here you can see how they refer to themselves on social networks and work out if they are using any specific campaign hashtags. If you put their exact account names in as keywords, you will pull in all the directed messages towards their account. You may find though that a brand’s name has multiple meanings, in which case you can always use keyword filters to narrow down your search.

Using our Nike example, you would first take a look on Twitter search; and you will see that all the mentions of Nike refer to the brand and that they have a large number of Twitter accounts outside the main @Nike Twitter account. So, as well as “Nike”, you might want to also add @NikeStore and @NikeLab to get a wider picture of the Nike conversation.

As with most things, the key to success is testing! So, we encourage you to test those keywords. The quickest and easiest way to test a keyword is to put it in the Search Twitter box on Twitter and click the Live tab. This way you can get an overview of what kind of content your keyword will pull. If you see lots of irrelevant data, you should consider changing your keyword or using keyword filters.

Now, on occasion, you’ll find that your query brings in irrelevant data. Not to fret. There are a number of ways you can deal with this. For instance, if you wanted to measure Apple, a brand whose name has multiple meanings not all related to the brand, you might find a lot of mentions of fruit. In this case, you will want to use keyword filters. As you will most likely want all mentions of Apple’s products, you can put “iPhone” and “iMac” into the keywords and the keyword filters so you get all mentions. But as you would only want mentions of Apple in the context of the brand rather than the context of fruit, you would put Apple into the keywords but put terms related to Apple such as “computer” and “Tim Cook” in the keyword filters so only mentions related to the brand are pulled in.

Sometimes a brand’s name may have other meaning in different languages. For instance, the baby milk brand SMA is a word in Indonesian. To prevent from bringing in lots of irrelevant Indonesian tweets, you can set the language filter to English and all the Indonesian posts will not be aggregated with what you’re seeking.

Then, we have what we all love — spam. Very often a brand can be the victim of sales spam, hundreds of posts from re-sellers. You may want to individually block problem users, or you can put key sales keywords such as “eBay”, “sell” or “sale” words into the keyword exclusions.

At the end of the day, setting up a query is simple if you have the tools and a little bit of knowledge. And of course, our team is happy to help at any point. Now, go forth and query!

business intelligence

The FitBit Generation: What We Can Learn From The Data

By | Social Visualizations | No Comments

Look around you — how many people are wearing a fitness tracker like a FitBit? One in five Americans own a wearable of some kind. And fitness trackers produce a lot of data. Lately, the value of that data has been questioned. Is wearable data useless? Do we need to expand upon what we track?

While the United States has 20% of the population using a tracker, there hasn’t been a huge improvement in the nation’s health. Individuals are rarely changing their behavior based on how many steps they are or aren’t taking. So, while we have this wealth of data, why aren’t we seeing a shift?

Data alone is never the solution. Data needs context. Data must be timely and actionable. When we view data in context and in a reasonable fashion, we can adjust the environment and outcomes. This goes for health and fitness all the way to business.

Humans have evolved to quickly understand and process info. We discard what’s not relevant or deemed to help us. In a world with more data than we could ever consume, our brains are working in overdrive. Unfortunately, this means we lose concentration generally after eight seconds. So, for us to process data, it needs to be deemed important and relevant.

With fitness, this means helping us learn how to change our behavior or putting that behavior in context. For example, being able to see that after Wednesday’s Trivia Night, we rarely work out gives us insight into our motivation. Steps and heart rate without that context doesn’t guide us. Incorporating that data with our calendars so we can see who and what motivates us (or steals that motivation) would.

And this is the insight we should keep in mind with all data points. Data becomes relevant and important when we design it in context and in a timely fashion. When you’re at work, are you presenting data in a way that separates itself out from all the other noise? If not, we can help.

*Image courtesy Vernon Chan with modification.

The (Social) Power Of A Superhero

By | Events | No Comments

Batman. Superman. Combine them and you get a pretty powerful social driver. Leading up its debut, “Batman v Superman” garnered over 180 million mentions. Comparing to other releases in the past year, it only trails “Avengers: Age of Ultron” and “Star Wars: The Force Awakens”.

Despite critic despair over the film, fans flocked to the theater to see it and then took to the web to discuss. Batman v Superman earned $209 million domestically and $538 million globally its first week. While trailing Deadpool (which is now the highest grossing R-rated film) on earnings, it did surpass it socially. During that week, over 1.4 million mentions of the film were generated, compared to one million of Deadpool on its release week.

This data shows that superheroes drive serious conversation. There’s a mix of nostalgia and hope in all these films. And studios have taken note. Over the next couple of years, both DC and Marvel are set to release a series of films around numerous superheroes. And the choice of actor matters. Is Ben Affleck the best Batman? Will Hugh Jackman stay as Wolverine?

So, to celebrate this (and keep us all informed), we wanted to share this lovely infographic highlighting all the actors who have played which superhero over the years. We’ll be interested to see which ones resonate most with the crowds.