A key to any good game is knowing how you won, and the key to understanding a victory in the realm of gamified content is in the analytics.
Analytics are key to understanding your audience: who they are, what they like, and how to tweak your content to better suit them. This analysis can allow for a deeper connection with readers/users, as well as show you how to expand your audience while still appealing to your pre-existing fans.
Analytics are so important that there are services, like Parsely, entirely devoted to them. Parsely also allows for predictive information about what content to publish and when, which can definitely give you an edge in your marketing plans.
But what should you measure? What is out there to help you measure it?
Everyone’s strategy is going to be different, but this will hopefully work as a starting point to begin integrating better analytics into your marketing strategy.
What Should You Measure?
Knowing what to measure out of all of the potential data that can flood you is important.
When it comes to social media, sites like Facebook are relatively simple. If you have a page on Facebook, extra tools aren’t massively necessary because they provide in-built analytics.
If you’re creating video content, definitely use YouTube for your distribution if analytics are your big concern. Not only is YouTube the place where the biggest video-viewing audience goes, they are also the second-biggest search engine in the internet. Why do you think Google bought YouTube? Not only has Google enhanced the search effectiveness to YouTube, they’ve added all manners of analytic tools to the site to help users know who is watching, where they are, and how much of your videos they watch before clicking away.
When it comes to a site like Twitter, there isn’t yet a centralized center of data to work with, so add-ons can become key.
Tools of the Twitter Trade
In addition, pre-scheduling services like Buffer offer data and analysis as a part of their service. With Buffer’s recent expansion from just Facebook to other services like Twitter and Orkut, there is a lot of potential out there for concise analysis within an already incredibly useful tool.
As far as Twitter goes, there are a variety of Twitter tools beyond the previously mentioned Parsely out there to help.
Sites like SocialBro allow you to see who is following you in terms of location, gender, even their native language. Knowing who is following you, or who is not following you back, can help you to modify your strategy and then monitor how those modifications have taken hold. Constant maintenance can be key to a marketing plan at its start and tools like this can tell you what is and is not working.
TweetReach allows for something even simpler: seeing where your tweets are going. Retweets and quoted tweets allow your words to reach a wider audience than just your followers, expanding out, possibly even exponentially. In addition, some Twitter services allow people to see users’ favorite tweets, so knowing who is favoriting your work can also come in handy.
There are even analytics for Twitter-friendly link-shorteners like Goo.gl, which allows you to track information from shortened links using the power of Google’s search tools. Bit.ly allows similar analytics tracking and is already integrated into several Twitter tools like TweetDeck and Buffer. Hopefully, Google will follow suit quickly with Goo.gl.
Perfect Data is Impossible
While data is great, it isn’t perfect. The idea of perfect data is a bit of a fallacy, especially considering the flawed origins of any data: humans.
Also consider that the amount of data you might get back from the variety of tools implemented can smother you with too much data to properly analyze. Again, knowing your strategy – knowing what you need to know – is absolutely key.
Trial and error might sound basic, but knowing you can go back to the data and keep working through will definitely help. Don’t be afraid of false assumptions. See where the data can take you and, if necessary, go back and start again.
Also know that sometimes data isn’t perfect. Systems are susceptible to glitches, like complexly networked senior moments. Being able to cope with potential data failures is important to consider. Don’t get too deep into the weeds! There is a forest beyond the trees! Maybe buy a book of Zen phrases like these. Deep breaths!
What’s your favorite social analytic tool?