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The Difference Between Listening, Analyzing, and Attributing on Social

What is the difference between listening, analyzing, and attributing in the world of social marketing?

You’re Doing Social Wrong

The distinction might seem blurry and vague at first, but these are actually three distinct “data levers,” if you will, that your brand should be pulling to make its social engine whir — and they all provide different assets. Briefly:

Listening: Listening gives your brand visibility into your audience’s identity, location, and earned conversations across all relevant social channels so that you can produce the right content and post it on the right channels for maximum impact on awareness and engagement.

Analyzing: Analyzing gives you deep insight into the results of your owned social activities across all channels, uncovering the impact your campaigns have on audience engagement and allowing you to discover new ways to optimize for the best results possible.

Attributing: Social attribution allows you to attribute conversions to owned, earned, and even dark social activities, so you can optimize decisions about content and channels based on direct impact on business results like website clicks, opt-ins, and sales revenue.

In more detail:


Listening allows you to answer the following questions:

  • What are people saying about my brand? 

Trending TopicsThemes that can expose purchase intent and preferences for product “flavors”

Keywords that can tell you which terms people are associating with your brand

Sentiment Analysis that can tell you whether the commentary around your brand is skewing positive or negative right now

  • Who is talking about my brand and competitors? 

InfluencerIdentify influencers and activate them to grow your share of voice against competitors

Understand detailed demographics and psychographics so you know who your audiences are and how to better relate to them

  • Where are people talking and engaging? 

Identify regional or geographic trends in social conversation to better target campaigns


Analyzing brand activities means a thorough, ongoing analysis of the activities your brand conducts, like publishing content, responding to users, and promoting brand campaigns or initiatives.

Pinterest Scorecard

There are many types of analysis to be done around brand activities, including campaign execution, posting volume and frequency, content type, content attributes, network distribution, and audience targeting.

PinterestThe goal of analyzing brand activities is to help marketers answer several specific directional questions:

  • Are they executing to plan?
  • Are time and resources being dedicated to areas that are aligned with the insight and intelligence gathered during the planning process?
  • Can they bring these activity metrics into their audience engagement analysis as tactical baselines?

Social analytics needs to fulfill a specific use case here, helping marketers measure, compare, and optimize the tactics being used.


A solid attribution solution allows you to:

  • Identify how both your brand’s and your audience’s social media activities drive conversion metrics such as clicks to website, email opt-ins, purchases, or any other conversion metric you’re interested in.
  • Understand social impact in the terms your business cares about.
  • Determine attribution down to the post level: learn exactly which types of posts drive the best business outcomes in dollars and cents. 

Download our guide to owned, earned, paid, and dark social below for a deeper look at what key definitions around listening, analyzing, and attributing your social data mean.

Get everything you need to analyze the metrics that matter

Owned, Earned, Paid, and Dark Social: Definitions, and Where to Begin


Lucy Hitz

I’m the Head of Marketing Communications here at Simply Measured, where I'm responsible for our content program, social media marketing, PR, and comarketing ventures. I love yoga, The X-Files, peaty scotch, hiking, and poetry. If I were a social media channel, I’d want to be Instagram, but I think I’m Twitter.

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