Social listening was once a novel technology, even as recently as two years ago.

Today, there are dozens of social listening and social monitoring software providers, each touting capabilities that vary wildly and generally sound like black-box, secret-sauce voodoo magic.

But once you understand the underlying framework behind each of these tools - data collection, normalization and natural language processing - it is surprisingly easy to distinguish between the value of different tools.

And from there, to embed them into strategies that drive marketing organizations further through research and analytics.

Social listening as a tool for data-driven growth

The most common question I get when talking with people about social listening is “What do I do with this data?”

The answer is:

  • Understand your audience.
  • Care for your audience.
  • Activate your audience.
  • Benchmark against your competition.
  • Optimize your campaigns.

Research is, after all, the beginning of better marketing. 

Yes, it takes a bit of creativity to apply social listening data to real business problems. That’s why I’m writing a blog right now.

First, a definition:

Social listening, sometimes called social monitoring, refers to technology that has the following properties:

  • Scans major social networks for instances of a keyword or key phrase.
  • Scans other sites - blogs, forums, news, etc - for instances of a keyword or key phrase.
  • Analyzes the results of these scans with Natural Language Processing (NLP) for sentiment.
  • Analyzes the results of these scans for various actionable insights, including major topics and key influencers.

Capabilities vary widely among tools. Many social listening platforms are not worth the money they charge, others are reasonably priced.

Prices, by the way, range between $10 and $10,000 per month - or higher for custom and volume-based pricing.

We will be discussing the ‘Enterprise Social Listening’ tools on the higher end, between $1,000 and $10,000 per month.

Understand your audience: Market research & product research with social listening

Most social listening tools scan hundreds of millions of websites for mentions of certain keywords.

This means that the results you’re looking at are really a sample set of the entire 'social web'.

So if you want to know what people online think about 'smartphones' - or if you’re a product manager for Apple and you want to know what people think about 'iPhones' - a quick scan with the right tools will tell you:

  • How many people or sites discussed iPhones/smartphones.
  • How the volume of iPhone/smartphone discussions trended over time.
  • Where the iPhone/smartphone discussions happen.
  • How people feel when they discuss iPhones/smartphones.
  • What they are saying - over all time and at specific intervals - in the context of iPhone/smartphone discussions.

As a market analyst, the information is useful for correlating with sales, stocks, etc. - and for understanding macro trends in order to anticipate the near future.

As a product portfolio manager, the information is useful for understanding customer satisfaction.

Care for your audience: Customer service with social listening

In fact, customer service is one of the major applications of social listening technology.

Tools like Sprinklr and SparkCentral are designed to power customer service for enterprise organizations.

By observing real-time lists of unhappy customer data, organizations can react quickly to address customer concerns, as well as observe major themes that arise from dissatisfied customers.BIS

For example, remember #Bendgate? That crazy thing where iPhones could bend? Yeah, that all started in September 2014. See this chart displaying over 450,000 mentions between September 20 and 30. 

The mentions are either of #bendgate (green) and “iPhone NEAR/5 bend” (purple; NEAR/5 is a Boolean search operator that will only allow results where the second word is within 5 words of the first):

Courtesy of Infegy Atlas - our preferred social listening tool.

Notice that things don’t really pick up until about the 25th, but the mentions begin streaming in on the 23rd.

Before the hashtag really caught fire, mentions of iPhones bending were higher. In fact, there are mentions of iPhones bending as far back as the 21st (though it’s not visible on this chart because of low volumes).

Savvy use of a social listening tool would allow those who manage customer satisfaction to watch this theme of bending iPhones unfold before it went viral.

You can beat the press to the punch with social listening.

Activate your audience: Targeted advertising and influencer activation with social listening

Top-tier social listening tools should provide you with unique IDs of social users, where possible.

Typically, this is only feasible on Twitter and Instagram, and sometimes other less-used social platforms like Reddit and Weibo.

For example, see this list of targeted Twitter users developed using ManageFlitterCMOs in Boston.

Once you have unique IDs of targeted users - especially ones who have strong affinity for your brand - you can do two things:

1. Deliver advertising to fans via Custom Audiences

Twitter and Facebook both offer advertising solutions that involve bulk uploading unique IDs of users in order to deliver advertising to only them. These are called Custom Audiences.

Say you develop advertising attribution software and are trying to sell to marketing execs.

You are based in Boston - or are boosting sales efforts there - so you want to develop awareness by placing your message in front of marketing execs in that area.

With that “CMOs in Boston” list I generated through ManageFlitter, you could deliver advertising to these users. If your list isn’t large enough (over 500 users), then you could broaden your search to include other qualifying terms.

If you have users signifying positive sentiment - or are using more sophisticated NLP software that looks at purchase intent - you could pull the user results from Twitter and advertise upsell products to them.

DISCLAIMER: According to Twitter's Terms, exporting lists from searches such as the one described above in order to upload them to Custom Audience for advertising targeting is not viewed favorably. Legal ramifications may result.

You can read more about it in the comments below.

2. Activate influencers

Most social listening tools have some level of focus on telling you who your “influencers” are.

These are the power users - the ones who advocate strongly for your brand and who have a good degree of visibility online.

Much like Custom Audiences for advertising, you can act on the user lists generated by these tools to encourage influencers to talk more about your brand.

Some brands offer these influencers special promotions in exchange for posts; others invite them to exclusive events.

Benchmark against your competition: Landscape analysis with social listening

Share-of-voice is a common measure of competitive standing among major brands. With the right tools, you can develop macro SoV insights, as well as SoV by geographic segment, channel segment (News, Forums, Blogs, etc.) and demographic segment (gender, age, etc.).

You can also develop sentiment benchmarks. Perhaps your brand is getting largely negative feedback, so you develop campaigns designed to encourage positive sentiment online.

You can set incremental measures of success so that, in six months or a year, you’re on top of the positivity game.

Marketers can also use social listening to track negative press about competitors.

In one instance with a higher education client, we knew about a disastrous press situation for our client’s competition before our client did. Many social listening tools offer alert functions that make this possible.

Optimize your campaigns: Real-time monitoring with social listening

Content marketing for enterprise is often focused around key phrases, tag lines or hashtags.

Social listening tools allow you to track the spread of these beyond your own paid/earned/owned efforts to promote them.

You can also measure the saturation of your hashtags and campaign terms among the overall buzz about your brand.

For example, for a major telecom client we were able to see the points at which their online conversation was dominated by a new hashtag they had launched.

This allows them to optimize their content based on the apparent efficacy of these times.

And finally, you can deploy social listening tools to measure the efficacy of your campaigns not only in volume, but also in sentiment.

After all, what good is buzz if it’s bad?

Where to learn more about social listening tools:

Evan Dunn

Published 2 November, 2015 by Evan Dunn

Evan Dunn is the 14th most influential digital marketer on Twitter and Director of Marketing Services for Transform, Inc. in Bellevue, WA. You can follow him on Twitter or connect via LinkedIn.

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Comments (6)

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Lance Concannon

Lance Concannon, UK Marketing Manager at Sysomos

Great article Evan. I just wanted to add a couple of things that people might want to consider when they're looking at social media monitoring tools:

1) Does the tool you're considering allow you to search through a comprehensive historical archive of social conversations for any keywords or topics that you're interested in without additional charges? With a lot of tools, you're limited to a preset number of search terms which you cannot change, and there's no access to historical data because the system only collects the results you've told it to, rather than archiving absolutely everything.

2) Can your social media monitoring tool find your company's logo inside Twitter and Instagram pictures, even when those images are not tagged by the user? Most tools cannot, but some (such as Sysomos) now use image recognition algorithms to identify your logo/brand in photos and to provide useful contextual information about what else is in those images.

almost 3 years ago

Evan Dunn

Evan Dunn, Digital Marketing Research & Analytics at Transform

Lance, thanks for jumping in!

1) I agree that historicity is important for some initiatives - typically those focused on Market Research. Many tools boast impressive historical capabilities - Infegy Atlas goes back to January 1, 2007 and Pulsar back to 2006. However, Campaign Monitoring and "War Room"-style social listening - which are often major use cases for CMOs - do not require this. As one client put it: "Back beyond 2 years often ceases to provide actionable insight for us."

2) Image recognition is definitely a sexy capability - props for that! Notice I didn't go into detail about the various capabilities of different tools, so your second point is missing the purpose of this post, and pretty salesy, though I realize you head up sales for Sysomos.

If we were to do a line-by-line comparison of capabilities, then from what I recall, Sysomos lacks the Natural Language Processing prowess of systems like Infegy Atlas (Purchase Intent, Cost Sensitivity, Health, Taste, Anger, Trust, Joy, Anticipation), the scope of Pulsar (sentiment analysis capabilities in more than 120 languages), deep NLP like what Relative Insight can provide, and I remember some concerning elements regarding your sentiment analysis approach, as well as an overemphasis on Twitter data (which is sadly an industry-wide problem).

We did an audit of Sysomos and over 30 enterprise-facing social listening suites, and the top performers were Infegy Atlas, Synthesio, Pulsar, DataRank (now part of SimplyMeasured), and Brandwatch. Crimson Hexagon's emphasis on scalable Machine Learning is also appealing.

almost 3 years ago


Siim Sainas, GM at STATSIT

Great article Evan. Thanks for sharing and impressive ground work on the article.

A few thoughts:

1. What you're suggesting for Custom Audiences is quite a slippery slope for big brands and I would not advise to anyone who is slightly more concerned of legal precautions. Twitter's T&C says that exporting lists like that is not allowed, unless those people have opted in themselves. So if you use a client's CRM base and reverse lookup for social profiles, then you have a case, otherwise going in to the social data straight up can result in a lawsuit. Sure, everyone knows about this in the industry and no-one has seen a case in a court, but with MNCs that would not be an advised approach. Im almost certain FB's terms say the same thing, but haven't checked recently. We where on this bandwagon heavily when we prototyped some tools for reverse lookups and building custom social panels for clients, so this is not just my opinion.

2. I've somehow just came across you now, but what you seem to be doing with Transform is great. We've been so much focused on getting to the nugget of insight that so many opportunities with utilisation of the data have been missed, but I guess thats what every small company needs to deal with - choose your battles. All the best!

3. Also just a relevant thought here... Im sure you have also noticed that the vast majority of social data is useless. Either its spam, bots, ads, contextually random mentions or something else, so its key to get to that relevant sample. Volume of buzz doesn't indicate relevance yet

almost 3 years ago

Evan Dunn

Evan Dunn, Digital Marketing Research & Analytics at Transform

Hi Siim,

Thanks for your input. I apologize for the unseemly advice regarding Custom Audiences. I will discuss this with eConsultancy's editorial team in order to revise the post with that in mind. Thanks for bringing it to my attention. Sadly, it is a use case that would actually increase the value of Twitter for customers when used correctly (better targeting = less annoying ads).

FB doesn't permit access to individual user IDs/names/emails as readily as Twitter does by account searches, so I imagine they just don't have to deal with it as much. And now they've put a premium on everything of this nature via PYLON.

2. Thanks for the compliment! I'd love to talk further. I'm interested to learn more about STATSIT. I'll reach out via other channels where possible, or you can email me at

3. Thanks for adding that in - it's true. I'm pretty pleased that most tools do a good job of surfacing useful content - Infegy Atlas, for example, offers context term filters based on relevance, not just volume of mentions.


almost 3 years ago


Rick Rudman, CEO at Tracx


Really enjoyed the article - a good contribution to the ongoing discussion and education process surrounding social. While reading I had these thoughts:

1. I may be getting caught up on semantics here but I think monitoring & listening is the first stage of social business, and that analysis and actionable insights is the second stage. Some social platforms really just listen, and some customers are happy simply to get that stream of mentions so they can see what's being said and reply if necessary. I think going forward it will be important to speak more specifically about the stages of listening, analyzing, routing, recommending, predicting and tying social directly to customer specific business outcomes.

2. As you point out, social listening is still relatively new. I think that the broader idea of "social business" is truly in its infancy, and will clearly be one of the most - if not the most - important ways a company does business in the coming years. There are many more innovations to come in the social business revolution.

3. "Understand your audience" to me implies you know who your audience is and want to know them better or you want to understand the demographics of your ideal customer. I would add "identify your audience" to the definition list to mean identifying specific people to try to engage. Of course you might argue those are one and the same.

Keep up the great work!

almost 3 years ago

Evan Dunn

Evan Dunn, Digital Marketing Practice Lead at Transform, Inc.

Hi Rick,

Thanks for chiming in.

1. I think what you're saying makes sense, but maybe was a bit outside of the scope of this post. Listening necessarily comes before action (and then more listening and then action, etc etc etc). I agree that, as brand understandings of social listening increase, more specificity will be crucial for vendors like us to stay relevant. At this point though, posts like this - which deal solely with what it is and what it can be (broadly) used for - are necessary to get brands' imaginations going on how it might be applied. The application of social listening is so varied that I still have to go back to the basics in a lot of client conversations to explain how it works and help them see how it might fit their business case specifically.

For example, a lot of B2B brands don't garner enough brand mentions online for brand monitoring to be a useful activity, and their competitors are in similar situations. They sell to companies, and companies aren't really social entities, so they're not out there saying "Yeah we just deployed Cisco for our networking IT" and responding "Oh I hate Cisco" etc. But that doesn't mean there are other use cases for social listening tech with topics and audience insights. It just takes more work to get there.

I think you're definitely right though that transforming brands into ones that are agile enough to live in the social web, and not take 2 months to pivot in response to social intel - that's a whole 'nother beast to tackle.

2. Per my last paragraph, I agree. We're just beginning to see orgs try to implement cross-departmental policies that streamline social activity. Part of what hurts a lot of them is the huge volume of useless fluff floating around from consultants and bloggers and thought leaders who don't really understand how to apply social tactics at scale. Hyperfocusing on tiny segments ("Vine!" Really? Vine?) or on meaningless pivots ("Blog more!") or outdated tactics ("SMS!") - these kind of habits have saturated senior levels of many brands and we're seeing the fruitless yields.

3. Yeah I'd probably argue those are too similar to distinguish in a short article. :) You may be referring to a useful distinction thought for B2B vs. B2C when it comes to audience ID. B2B needs to know individuals - begin with the finest grain (one person) and work upward (organizations). B2C less so - begin with largest grain (regions, major segments, etc) and work downward (near-individual level). At least, that's how I'd work it.

I'd love to hear more about Tracx sometime!

over 2 years ago

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