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Week 2: Marketing, a feelings game
large scale telepathy
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Welcome back!
We hope everyone’s year is off to a great start! This week, we’re talking about superpowers. Ever wish you could read people’s minds? Well, sentiment analysis allows you to read customers’ minds on a grand scale, analyzing text from a variety of digital sources to classify sentiments at varying degrees of complexity. When it comes to marketing management, sentiment analysis is crucial for managing your brand’s reputation, detecting potential crises, and making use of feedback.
Let’s dive in! 🏃♂️🚀
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Messy feelings
There are 4/5 main forms of sentiment analysis, which range from basic to advanced.
The first is Polarity-based— it’s the simplest form, categorizing feedback as positive, negative, or neutral.
In reviews, positive might look like “I love this new phone! It’s so fast and the camera is amazing.” Neutral may be “The product arrived on time and works as described.” A negative sentiment would be something like “This app is terrible! It keeps crashing and I can’t get anything done.”
Emotion-based sentiment analysis adds a layer of complexity, categorizing sentiments into actual emotions, like happy (“I’m thrilled with my new car!”), angry (“This customer service is infuriating!”), or excited (“Can’t wait to try out my new coffee maker!”).
Third, there’s urgency-based sentiment analysis, which prioritizes feedback by degrees of urgency— separating more general feedback from feedback requiring more attention.
A message like “My account has been hacked— need help ASAP” would be flagged as high urgency, whereas a message like “Wondering when the new product line will be released” would be low urgency.
Intention-based sentiment analysis tries to understand the customer’s overall goal— are they an interested buyer? Are they offering product suggestions? Or do they pose a major churn risk?
Finally, there’s aspect-based sentiment analysis, which breaks down feedback into specific aspects of a product or service and assesses sentiment for these respective aspects. A review like “The food was delicious, but the service was slow and the prices were too high” may be broken down into the food aspect, service aspect, and price aspect.
Houston, we have a problem
In a hyper-fast-paced digital world, a PR crisis can explode in the blink of an eye. Sentiment analysis can act as an early warning system, giving a heads-up before things go south.
United Airlines, for example, became infamous for an incident where a passenger was forcibly removed from an overbooked flight. With recording devices and social media in tandem acting as a megaphone, negative sentiments went soaring.
The company’s crisis team monitored the situation in real time using sentiment analysis tools to gauge just how bad things were and how much better things got following their responses. So, how can you apply it yourself?
First, choose a social listening tool with sentiment analysis capabilities.
You then have to set up keywords to detect the sentiments associated with your brand. These include your company name and common misspellings, product names and variations, slogans and taglines, and names of key executives or spokespersons if they’re well-known.
You can also use keywords for industry-specific terms, like technical jargon related to your products or services and buzzwords frequently used in your sector.
Review and refine keywords on a consistent basis to add new product names or campaign-specific terms as they launch, or known vulnerabilities in your products if they emerge, as well as names of major events or sponsorships you’re involved with.
From there, you have to establish a baseline to create alerts. Do this by monitoring sentiment for an extended period (for example, three months) and noting normal patterns, like the typical percentage of negative mentions (e.g, 5-10% of total), average sentiment score, and normal mention volume (ex. 100-500 per day).
Then you can make alerts for these categories, such as negative mentions exceeding 25% of total, sentiment score dropping below -0.5, or mention volume spiking much higher than your typical volume. For the last one, this might also be a good indicator of a recent highly successful campaign.
Consistently monitoring sentiments makes it easy to recognize when negative sentiments jump up, allowing companies to respond more quickly before issues spiral.
At the same time, monitoring scores can also point you toward the campaigns and marketing strategies that are most effective and impactful.
Sentiment and segmentation
Other than averting crises and identifying your best campaigns, you can also use sentiment analysis to segment customers based on their emotional responses and use targeted advertising for different response groups.
The first step is obviously gathering sentiment data— collecting feedback from multiple channels, between social media, reviews, surveys, and support interactions.
Sentiment analysis software will usually help you clean and organize this data, removing irrelevant information and categorizing it by keywords, features, and demographics. You can choose how you want to split up customers based on overall sentiment scores.
So with this information, what kind of strategies can you use?
For the positive sentiment segment, focus on loyalty programs or exclusive offers.
For neutral or slightly biased sentiment, focus on boosting engagement with targeted marketing encouraging customers to, for example, create user-generated content.
For negative sentiment, focus on proactive outreach addressing vulnerabilities in your product and easy avenues to get assistance, with quick access to support.
Setting up automated responses for these categories (like automatic support tickers for customers with consistently negative sentiment) can streamline and simplify implementation.
With the right keywords and set up for your analysis, you can identify which features customers value, don’t care about, or hate— and the same goes for ad campaigns. This way, you’re not wasting development spending or advertising that yields minimal or negative returns, and it can be hard to identify which products and campaigns are causing customer reactions without sentiment analysis.
Looking Ahead
Armed with an understanding of the emotional undercurrents in customer feedback, marketers can optimize campaigns to resonate more strongly with customers aligning closest with their ICP, taking the guesswork out of what your target customers like. When you’re developing your brand, reputation is everything, and one crisis can seriously set you back. That’s why being proactive and sniffing out negative rumblings with sentiment analysis can stop reputational damage in its’ tracks.
If you want to automate your marketing processes to grow faster, click here to learn more about how Loopgenius can help you.
Stay tuned for next week, when we’ll look at adapting content based on marketing data!
Data-driven Marketing
Week 1: Predictive analytics for campaign optimization
Week 2: Sentiment analysis (this week)
Week 3: Data-driven content strategy
Week 4: Hyper personalization
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