How to use AI machine learning for brand sentiment analysis

@IE University

Brand sentiment analysis lets companies know exactly what they’re doing that is beneficial to their brand, and what they’re doing that’s impeding growth. This helps them improve their offering and provide a more personalized service.

Let’s play a sentiment analysis game. In the sentence below, which phone does the speaker prefer?

“I think that Phone 1 is better than Phone 2.”

That’s quite simple, right? It’s clear they believe the first phone is better. But let’s try it again.

“I think that Phone 1 is better than Phone 2, but I’d recommend Phone 2 if you work in business.”

As a human, you can tell that the person is changing their preference depending on the situation. But for a machine, it’s not quite that simple—and it’s taken huge advances in AI to be able to do such complicated brand sentiment analysis.

Advertising Brand Sentiment

Brand sentiment analysis: what’s the big deal?

Brand sentiment analysis is very important. Just like us in real life, brands want to know what people are saying about them. And it has nothing to do with self-esteem or just because it’s nice to hear nice things about yourself. For companies, it lets them know exactly what they’re doing that is beneficial to their brand, and what they’re doing that’s impeding growth. This helps them improve their offering and provide a more personalized service.

But let’s think about this logistically for a minute. While any particular brand may be active on a number of channels and across social media, the scope of their exposure is unlikely to end there. People could be talking about a brand on private forums, Amazon reviews, or… anywhere really. With so many virtual places, how do you possibly monitor what people are saying about you? And even if you manage to do so, how do you then use the information to improve your service or product?

How to use brand sentiment analysis

AI is pushing the boundaries of what’s possible in almost every sector. Here, we’ll walk you through the main steps in running comprehensive brand sentiment analysis.

Communication and Digital Media IE University

Step 1: find where you are

The internet is a big place—like, unfathomably big. With so much information out there, it’s easy to get lost. This is where keywords come into play. Say you’re looking to find out what people are saying about you on Twitter; it makes sense that they will have to mention your brand.

Companies like Hootsuite have tools that let you plug in the keyword about you and you can immediately see what people are saying about you. With more complete software, this can be done across different platforms and review websites at once, so you can be where the action is.

Advertising Brands Sentiment

Step 2: filter positive, neutral, or negative

Ok, so you’ve found all these people talking about you. But there’s a problem—there are lots and lots. Too many to read. And yet you need to know if they’re saying good things about you or not.

In the introduction, we did some simple brand sentiment analysis to show how difficult it can be if you’re a computer to understand if a statement is positive or not. Of course, this is the basis of all analysis and if you can’t figure out whether it’s positive or not, there’s no point in doing it.

Advertising Brand Sentiment

But, that’s the beauty of modern technology! Based on machine learning, the AI system will then filter the comments telling you whether they’re positive or negative. If they’re unable to identify them, that’s no problem, they simply go into a third, neutral category.

Step 3: analyze the information

With some easy-to-use software, you’ve both found where you are and if people are saying positive or negative things about you. Now, you need to analyze the information, which is easier said than done.

It’s not enough to just know if they’re positive or negative. You also need to know the who, what, and where. It may be that the positive mentions are all coming from your particular target audience and the negative ones are all from outside your target. That’s not necessarily a bad result. Then again, you could find that an important influencer in your niche has given a negative mention that could influence (hence the name) a lot of other people against your brand.

Whatever AI-powered software a company uses, it will let them analyze the information according to different filters. This helps companies get the most important insights and alerts exactly when they need them.

Step 4: prevent crises

Imagine you own a popular restaurant in a large city and you’re on Tripadvisor. It’s just another day and you’re busy working online when you get a notification from your brand sentiment analysis software. Someone has left a review about your restaurant saying the food was terrible, the service was a joke, and they found a hair in their soup.

Branding Brand Sentiment

What do you do?

Really, you have a few choices:

  1. Publicly apologize and offer a voucher
  2. Defend yourself

The most important thing is time—which is exactly what the software has given you. Reviews like this can snowball online and the more people who see it before you reply, the worse it can be. With any good AI brand sentiment software, you are notified immediately.

AI-powered software is transforming how we conduct business. These new tools are as fascinating as they are useful, and represent huge potential for anyone entering the digital sector. Keeping an eye on and using emerging technology will help you stand out from the competition and turn recruiters’ heads in your direction.