Generalizations are Broad Guidelines, not Gospel

Let’s get something straight: generalizations are not gospel. I’ve seen too many blog posts and articles lately which use broad generalizations to show how to be successful with social media, particularly Facebook.

For example, analyzing when your brand’s Facebook page community is most active (time of day, day of week) is incredibly valuable. This can help you time your own activities to catch the most people at the exact right time. But writing posts at noon because you read a blog post that says that’s when people are most active is lazy.

Studies like that look at Facebook brand pages across industries and categories. Their core consumers are likely vastly different, and each page likely has very different fan bases. Averaging these numbers doesn’t tell you anything for your own brand. It tells you the average time of day people across 30 different Facebook pages are most active.

Depending on the methodology of the study, these numbers can also be incredibly skewed by communities with large volumes. If you’re just starting out, do you really want to use what works best for Starbucks? Please, don’t say yes. They have a much larger (and likely more diverse) audience. Emulating their success won’t happen by copying their every move.

Many of these analyses can be fairly easily performed for individual brands, but instead many marketers seem to prefer using generalized studies. And it seems lazy. Take the time to research and develop customized results. You’ll be glad you did in the long run.

I have done quite a few of these Facebook analyses myself, and I can tell you that no two communities have ever been exactly the same. No two communities have even had similar results.  Just recently I found one client to have a very active community around lunch, while another was most popular around 4 p.m. If I’d used one of those studies, I’d likely be telling both clients the same answer, and I’d be wrong 50% of the time.

Read generalized studies as a guideline for your own research, not gospel. Read them to learn about methodology and technique. Find new metrics and measures to help build your own success. Don’t read them as a free pass or end-all solution.