&gt; <i>It&#x27;s not terribly hard to make up data showing some kind of effectiveness, or just to misinterpret real data in a way that can convince others to let you keep doing it. For every marketing or advertising craftsman out there who builds something that works, gathers useful data, and interprets that data honestly, there are probably 20 people who have no clue and just keep churning out the same stuff because they don&#x27;t have anything else to offer.</i><p>Let me share a personal anecdote from watching a social media marketing company at works.<p>These marketing people got contracts to do brand&#x2F;site&#x2F;service promotion on everyone&#x27;s favourite social networking and image collecting sites. They wrote many posts, made interesting graphics, etc. Generally did a good, honest work at that. Then every month they had to write reports detailing the effectiveness of their efforts. The way they did it was like this:<p>1) gather metrics provided by social media platforms they used<p>2) put them in a DOC file<p>3) start with the conclusion that they did their job well and helped the marketed company tremendously<p>4) invent some plausible-sounding reasons to connect the data from 1) to conclusion in 3)<p>And mind you, this wasn&#x27;t intentional dishonesty. They simply have <i>no fucking clue</i> about the meaning of the data, or what can (and can not) be reasonably inferred from it, so they don&#x27;t even try. They don&#x27;t even know what they don&#x27;t know. But their clients don&#x27;t know anything too; it&#x27;s basically both sides not knowing what those colorful graphs and tables of numbers mean and bullshitting one another without even realizing it.<p>I guess one can&#x27;t generalize from one example, but mind this: social media marketing companies are not staffed by math PhDs, they&#x27;re staffed by social sciences undergrads who decided that, given current state of the job market, learning Photoshop is better than working at McDonalds. They may be good at making interesting content, but they have <i>zero</i> necessary knowledge for getting right conclusions from data.