Social Listening and Predictive Marketing Analytics 101

Kimberly Surico |
 01/22/19 |
5 min read

Social Listening has come a long way in a relatively short amount of time, particularly in the past ten years – and it’s come with a pretty steep learning curve for those new to the game. Although it offers incredibly cool insight in its own right, predictive marketing analytics have changed the social listening game. It shifts the paradigm from one of understanding consumers today to one where you can pretty reasonably predict what they’ll be expecting from your product line tomorrow. And if your stores are about to be mobbed and require a police presence to handle it all (more on that in a bit).

Oh, The Possibilities

Social listening powered by predictive marketing is the bees knees. There, we’ve said it. It’s the culmination of sentiment analysis perfected over time, and we’ve only just begun to unlock the potential it offers. Let’s take a glimpse at what’s available today to start:

Tracking Trends. Consumers are fickle, so although understanding what they’re­ interested in today is great – it doesn’t mean that’s where you’ll find them next week. You can make some predictions around future behavior by monitoring trends and setting up alerts. These alerts can be:

  • Triggered alerts – email notifications sent your way whenever NetBase detects unusual changes in mention volume.
  • Any Mention Alerts – maybe the volume of mentions haven’t increased in any odd way yet, but the way your brand is being mentioned has shifted. Email notifications sent at intervals that you specify when mentions that match a saved analysis are posted can be a lifesaver here. Great for brand health and crisis management – and anything requiring immediate notification when a specific type of post occurs.
  • Any Metric Alerts – here we have email notifications sent when a selected metric (maybe Potential Impressions or Net Sentiment) for a saved analysis matches alert configuration options.

Offering Exceptional Customer Service. As you’re tracking trends, you’ll undoubtedly notice patterns around things your current and potential customers love and hate – and you can be ready to address it. Not just with canned “we’ll look into it and get back to you,” but a “so sorry, Sarah, we have a replacement part ready to send today, along with discount off of your next purchase” sent immediately, without making Sarah wait two days for a reply.

You’ll know that Sarah is quite influential on Instagram and loves talking about brands – and you can reasonably assume she’ll be mentioning you next to her followers, which happens to be your target audience.

And you’ll know all of this because you were ready with info about the damaged item (from tracking chatter about your niche in general and your business specifically) and because you were able to quickly click around in NetBase’s sentiment analysis tool when Sarah messaged – and see something like this (from a quick scan for Valentine’s Day influencers):

Sourcing New Product Ideas. As you’re providing exceptional customer service and paying attention to consumer passion (good and bad), you’ll also see suggestions for new products or service offerings popping up. And some may even come to you organically as you gain better understanding of your user base at a granular level. What are they mentioning? How do they feel about it?

Next Level Competitive Intelligence. What if you could predict your competition’s next move and either learn from their plodding mistakes or beat them to the punch? With analytics you can. And yes, that’s a predictive bit of business as well. You can see who is talking where – and what they’re saying. And if it’s resonating – and if it’s resonating with the right audience. The options for delving deeply into the data are pretty limitless and expanding daily.

By how is all of this possible? And it seems like a lot to master, right? Let’s check out the predictive power behind it all.

Revealing the Man Behind the Curtain

The secret power of it all lies in sentiment analysis, of course, and these days it’s even more potent as sentiment analysis is powered by artificial intelligence (AI). And not just run-of-the-mil AI (that’s so 2018), but Next Gen AI, which we’ll detail in myriad ways in the coming months.

The variety of intel available appears intimidating, but it’s all about honing in on what’s important to your brand and being able to trust that the information you’re gathering is accurate. That’s key.

Really all you need to focus on right now is that predictive marketing is made possible by Natural Language Processing (NLP), Image Recognition and awesome Data Analysis capabilities that team up and offer:

  • Classification of known categories (tracking what you know)
  • Discovery of novel insights (finding out new things about your audience)
  • Learning, to customize results of Classification and Discovery (and make predictions)

And it’s probably easiest understood in the context of a case study. Unfortunately for Build-A-Bear, we have a ready example handy.

As mentioned in the intro, knowing ahead of time that your stores are set to be overrun with angry parents is predictive intel any retailer would love have. And it’s the stuff this stuffed bear maker undoubtedly wishes they’d had in hindsight.

The turnout for their “pay your age” promotion wildly exceeded expectations – to the tune of thousands showing up for an event with multiple littles to stand in line for 8 hours and leave with nothing. Nightmare.

“The turnout was simply more than they could have anticipated based on prior big promotions they’ve run. . . . Price stated explicitly that they had monitored social media and saw things were ‘winding up’ 24-48 hours prior to the event. She explained they put out a notice that lines might be long, and ‘worked with the malls,’ but it just wasn’t enough.”

Had they accessed accurate, in-the-moment data around this promotion and set alerts to trigger when reaching certain levels, they certainly could have anticipated the chaos and made real moves to alleviate lines and drama before they happened, certainly before the camera crews arrived! Instead, they were left dealing with a messy cleanup after-the-fact, and making their target audience very unlikely to participate in future campaigns. It’s a net loss for them and it was entirely preventable.

Your brand isn’t selling $80 stuffed bears for $2 so you don’t have to worry? Maybe not. But predicting and participating in the next Pokemon Go craze, or understanding your audience’s building frustration with your brand, or (even better) that of your competitor, is hot intel that doesn’t stay warm for long – not when you have so many businesses already wise to the predictive analysis game.

We predict you’d love it, if you saw a demo of it in action. Reach out and we’ll show you how it looks!


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