# Hacking Into the World of Big Data on Social Media

- Link: https://chatterblast.com/blog/hacking-into-the-world-of-big-data-on-social-media/
- Published: 2017-11-01T18:27:24-04:00
- Author: chatterblastteam

It’s no secret that social ads and analytics have become the most valuable asset
in digital marketing. [Data is giving rise to a new economy](https://www.economist.com/news/briefing/21721634-how-it-shaping-up-data-giving-rise-new-economy)
that relies on audience participation feeding the knowledge machine we rely on, 
to get results.

Now data may not seem like the sexiest topic in the world, but I’m here to tell 
you it can be with the right perspective. Do all-star conversion rates make ya sweat?
Does the idea of every person your ad hits clicking turn you on? Exactly. Big data
can get you there.

Whether you’re [just getting started](http://chatterblast.wpengine.com/the-perfect-holiday-recipe-for-social-media-advertising/)
or you’re triggered by the words “a/b testing,” social advertising is a force to
be reckoned with.

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Image via Venrock

Every single move you make online leaves a trace ([Incognito Mode](https://support.google.com/chrome/answer/95464?co=GENIE.Platform%3DDesktop&hl=en)
ain’t saving ya), and by collecting and analyzing those patterns, companies are 
able to get a more accurate picture of who their content is reaching and how their
audience is interacting with it.

**For example:** Say I’m more likely to click “going” on a Facebook event than my
coworker Grace, as she’s more interested in watching videos on her timeline. Facebook
will start targeting me with more event response ads while directing video view 
ads at her. Serving Grace an event ad would be a waste of budget, as she’s not very
likely to make that final conversion (i.e. click “going”). Analyzing this behavioral
data is one way platforms can refine targeting and ensure results.

## **So in short, why is data valuable to your company’s digital marketing efforts? **

Well, among many, many other things, big data allows us to see detailed demographics
about the people who engage with our social channels. Think: Age, race, gender, 
location, income, device used to view content, job title, relationship status, hobbies,
interests.

It also includes **audience behaviors **compiled through collection techniques like
[Facebook Pixels](https://www.facebook.com/business/help/952192354843755). A pixel
is a piece of code that can be placed on a webpage to track what kind of folks file
through. After months of data collection, the information collected by the pixel
can then be used to form **retargeting ads**.

Have you ever placed something in your cart on Amazon and left the web page without
making a purchase? Of course you have, I mean Amazon is like the digital version
of walking into Target. You end up with everything except the item you came for.
Now how many of you have logged onto Facebook later, only to see an ad for that 
_exact_ product in the right hand column of your newsfeed? That’s a retargeting 
ad in practice and Facebook will keep on sending them to you until buy.

[[

You know they are out here mining for your data. Image via David Parkins/The Economist

Data allows us to place tangible value on our marketing efforts in an unprecedented
way. It can be difficult to convince people of the value of social, and analytics
give us the hard numbers we need to make a case for the value of  advertising in
this space.

Before the rise of big data, marketers would cast out advertising campaigns and 
cross their fingers. Now we can see _exactly_ how many people viewed or interacted
with our content, something previously impossible. When advertisers place messaging
on billboards and in magazines, they can only make rough estimates–based on highway
traffic or circulation numbers–of how many people their ad would reach. But now 
we know not only how many people our messages reached but what elements of an ad
they responded to as well.

The way I see it, targeted social advertising doesn’t have to be a bad thing. As
long as there’s transparency about what is being collected and when, I don’t mind
Facebook diving into my data and doing the work of finding trendy [e-tailers](https://en.oxforddictionaries.com/definition/us/e-tailer)
that fit my style, for me.

As the importance of big data continues to grow, so will the scale and attention
to detail of the collection techniques.

So how could these data collection techniques possibly become more intelligent?!
You’ll have to wait for part 2, dropping later this week.