Making assumptions and marketing, part 2

A couple of weeks ago I talked about marketing assumptions or, in the vernacular, "drinking the Kool-aid."  It's been rolling around in my head and I thougt I'd take it a little further, especially since this is this week's lesson for my tribe.

 The lack of accurate data is the source of failure for most companies and social media programs.  The good news is adopting effective social media practices solves the bad data problem for both.


Most companies begin with some good data that assumptions are based upon and direction is decided.  What causes failure is when ll future assumptions are based on the original data and subsequent anecdotal evidence that validates the original assumption.  That's a recipe for failure or, in the least, a continually contracting market.


It used to be that companies would invest in some level for real market data, but falling revenues at all analysis firms shows that time has come to an end.  For about the past decade, most companies coming to me with market data to back up their claims admits the data they have came from a former company who bought it up to 10 years ago.  The information floats around the Internet and people pick it up as though it is recent, just because someone reposted it a month previous.


Now that might have worked when the data was two or three years old, but when it get's past that time it has the aroma three-year old lunch meat.


In the same way, social media efforts based on those same assumptions make the efforts useless.  Audiences growth plateau as the market realizes the content is just rehashed brochure material and they move on to find something valuable, and executives wonder why they are wasting time on the effort.  


It is still possible to get encouraging data from a bad social web effort, if you continue measuring web stats as they were done 10 years ago -- eyeballs and downloads.  But modern social approaches to web-based information have found those metrics to be completely useless.  Spiders sweep pages for search data and are measured as as though a real human viewed the material.  Much of the content downloaded is never read, and often downloaded multiple times by a single person who keeps forgetting where the put it.


What truly counts is the identity and engagement of the audience.  It is possible with social media to learn who exactly, not generally, is reading your content, what they think about it, whether they consider it important enough to share it and who they invite to the party.  Measurement for this effort, will not be based on numbers, but on the participation, or engagement, of the audience.


In social media, there are a bunch of tools for measuring, producing and improving engagement are one in the same.  I've been finding some excellent result from products from Apogeeinvent, Crowd Factory and Arkayne that provide the data necessary to measure engagement and drive the engagement deeper.


However, from the outset, establishing an arbitrary "goal" for certain numbers to indicate success is not efficient because it will take time to establish a true baseline.  Success is determined by an organization's ability to adapt to the demand of the market, not drive it where you want it to go.  That's the value of assumptions based on real data.