Analytics & Insights, Science

Getting to Magic: Facebook’s Negative Feedback Data

I’ll never stop harping on looking deeper into analytics for deeper insight. Too often we just look at positive triggers (Likes/Comments/Shares) as an indication of how well content is performing. But wouldn’t it be nice to know how often people Unliked or Hid our content too, to get an idea of how well it actually resonated?

Enter: Negative Feedback. This is every Hide, Report as Spam, and Unlike for the page, and if you have access to the New Insights is found under the Reach tab:

Where to find Negative Feedback.

Where to find Negative Feedback.

And here’s what the graph looks like:

Negative Feedback Graph

Negative Feedback Graph

If you don’t have access to New Insights, pinging your Facebook Account Manager should get it for you, otherwise it’s buried deep in the data extract Excel sheet (columns BB to BG in my report).

Going Up-Data

Per the post on the Criticality of Great Analytics, the question I’m typically trying to answer with this data is “Which Posts are Resonating Best?” If I had access to web data, I’d make this “Which Posts are Adding the Most Value?” by tracking the entire clickstream to the site, conversion points, etc, but for now we’ll keep this purely in Facebook.

Thankfully, Facebook gives us some great datapoints to make this a largely math-driven equation. We basically want to measure Net Reaction divided by Net Reach. In order to do this, we simply do:

((Daily Comments + Daily Likes + Daily Shares) – Daily Negative Feedback) / (Daily Total Reach / (Daily Total Reach – Daily Count of Fans Online))

There are some simpler ways to do this, that may be just as valuable, but I like to do Net Reach because it factors in how many people were online on Facebook that day. Ultimately what math like this (typically done in Excel) should show is how people are responding to your content day by day. If you run this at Post level, and compare it to content types or narrative arcs, you can also see how your audience is responding to various types of content.

The last time one of my clients had a significant spike in Negative Feedback Rate, we produced content and then segmented it out by audience to try and see which audiences were driving NFR, and found that all folk under 35 skewed negative, while those over 35 skewed positive. This data led towards a market survey which fundamentally changed the positioning for the brand.

Conclusion

Great data is always hard, but now that Facebook is exposing this data directly via Insights, making use of it is easier than ever. Though, to be fair, building Macros into the Data Export will yield some pretty epic data too. More on that in a future post!

Think I’m off base, just like Dave? Let me know in the comments belowwww.

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2 thoughts on “Getting to Magic: Facebook’s Negative Feedback Data

  1. I think the only improvement I would consider in your formula is the value of a comment, like and share. Same with Negative Feedback elements. In your formula your valuing them all equally. There’s a couple of ways to evaluate each and I think it’s a little too simplistic to treat them all equal.

  2. Jeremy Wright says:

    Colin, great point. This is why the question is around “Resonating Best”, not “Driving the Most Value”. If the question was around value, then you’d have to assign values to various points of the customer funnel, leads, leadgen, and conversely to items that lead down-funnel (click is better than Share in a funnel).

    For the purposes of customer resonance, the fact that people are taking any positive action vs a negative action is, to me, the point (volume vs volume). But, it is possible I’m looking at this too simplistically. When doing value-driven reporting, I always assign CRM and funnel values to actions…

    Feel free to disagree 🙂

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