Πέμπτη 13 Δεκεμβρίου 2012

Using social media monitoring to find where your influencers are

Social media monitoring is a complicated industry, populated with hundreds of different tools, varying from the dirt cheap to the shockingly expensive.

The versatility of these tools also means that there are countless uses for them, and keeping track of just which tool you would want and why is understandably a headache for many.

To help you navigate this maze, I’m going to lead you on a journey through some of the key ways employing a monitoring tool can help you and your business.

Identifying influencers

To kick this series off, I’m going to get the hard one out the way first, though it's split into two parts. It’s still a major part of the social media zeitgeist moving into 2013, but tracking down influencers and working out different definitions of influence remains crucially important to a variety of industries.

You could be:

  • A PR company looking for key bloggers to send out free products to in order to gain increased exposure and favourable review.
  • A market research company seeking to isolate pivotal figures in a particular niche to find suitable focus testers or for targeted customer feedback/product development.
  • A campaign planner trying to work out who their content has resonated with and who they should seed upcoming content to.
or, of course, any other number of other types of people interested in looking for influential people in a specified field.

Influencing fish

The first step however, will always to be define what it is you’re looking for. There’s a significant difference between a brand advocate (high volume of relevant tweets, often smaller network size) and an expert (low volume of relevant tweets, often large network size) for example, so make sure you know what you’re looking for before you being your search.

Where to look

Some monitoring tools will work on a keyword basis, though the better ones will have exclusion and inclusion options to varying degrees. The very best will offer a suite of operators so you can refine your search with incredible accuracy.

You should be first defining the terms and phrases you’d like to find. Let’s say we are a cruise ship company and we’d like to find influential bloggers to distribute special content to.

First we would select a handful of key terms, like cruise, tour and ship, but it would also be sensible to contextualise these terms. We could determine that they must be on the same page as holiday or vacation, for example.

Next we can refine the search to look for a particular conversation type, such as tracking words like review, recommend, best, dream, ideal ‘which operator?’ and other contextualising aids.

Detecting influecers

Eliminating spam and irrelevant mentions can be somewhat laborious, but it’s well worth the time to produce a useful list of exclusion terms and to come up with clever ways to get rid of mentions you’re not interested in.

It may be a case of using more granular and complex operators, like narrowing the search from AND to NEAR, meaning the terms must be much closer together textually. Perhaps it’s excluding specific sites, authors or words, but getting rid of this extra data will definitely help you in the long run.

You can also narrow the search by region or by language in most tools, which is the next step if you’d like to focus on just one area.

Finally, you may wish to consider other filters in your search, such as searching by page type (are you looking at just blogs, or would you like social networks and news as well?), demographic, site credibility (MozRank) or other variables.

However, my recommendation would be to leave this data in your search, as all good tools will leave you in a position to filter these variables later on as you dive deeper into the data.

So you should now have a carefully tailored pool of data that is specific to the sector you’re most interested in, as well as an unambiguous set of aims as to what you are looking for.

Clearly the next process is sorting and selecting the influencers you’re most interested in from your data set, which is something I’ll be discussing in my next post – so stay tuned!


by Joel Windels
http://econsultancy.com/gr/

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