Find Out What Your Customers Really Think With Sentiment Analysis
What is it?
“Sentiment analysis is a brand of Natural Language Processing (NLP) which identifies, extracts, quantifies and studies affective states and subjective information” – Microsoft
In basic terms, it’s an algorithm which gives you insight into the attitudes of people interacting with your business, trawling through social media feeds to do so. Businesses can use it to understand how customers feel about a product or service via social media – hence the term sentiment analysis. It has also been coined as ‘Emotion AI’, ‘Sentiment Tracking’ and ‘Opinion Mining’.
As a business, sentiment analysis is a surefire way to see what people are saying about you.
How does it work?
NLP processes computer systems that process human language, apply meaning to statements and then ranks the statements. The ranking works on a 1-10 scale, defined by Negative, Neutral or Positive.
The tone of messages are then ranked as Negative, Neutral or Positive on a 1-10 ranking scale.
In short, Natural Language Processing is the way computers understand and manipulate human language. It’s a goldmine if you want to know what your customers are saying about you. And what brand doesn’t want to know that?
Sentiment analysis may be considered by most as the domain of data analysts and scientists, however that’s not necessarily the case.
Why should I do it?
Well, you do want to know what your users are saying about you, right?
If you found out your product was making users frustrated whilst they were using it, you would likely want to make reparations. This is exactly what sentiment analysis enables you to do. See what’s going wrong in the user journey and why, and make improvements. Your customers will love you even more for it.
How can I do it?
Perhaps surprisingly, you may already have access to the right tools in place to set up and conduct your own sentiment analysis.
Through 3 Microsoft products, you can set up, track and visualise customer sentiment:
– Microsoft Azure cognitive services: this runs the algorithms to get out the results
– Microsoft Flow: extract Twitter feeds and connect with Azure Text Analytics and insert data into Power BI
– Power BI Stream Analytics: easily visualise data
To find out how exactly to set up sentiment analysis, take a look at Microsoft’s TechNet guide here.
Unless you are experienced with setting up APIs and using the above mentioned tools, I strongly recommend you seek out assistance from an expert when setting up your own Sentiment Analysis tracking.
What else can I use Sentiment Analysis for?
Sentiment analysis isn’t just limited to monitoring brand or product sentiment:
Customer service is becoming increasingly automated thanks to IoT, data analytics and online tracking. Algorithmia explains how customer service agents can use sentiment analysis to sort user emails into ‘urgent’ and ‘non-urgent’ buckets based on the sentiment of the email. This helps them proactively find frustrated users.
Drive business solutions
Although it might lift your mood to see a spike in your Twitter mentions, sentiment tracking may actually show to you that the spike is caused by customer dissatisfaction with your product. Having this knowledge can drive changes to your business model or products.
Measure Campaign ROI
Tracking customer sentiment can help you measure your ROI on marketing campaigns. Tracking likes, comments, followers or retweets can work towards measuring your campaign success. Positive and negative discussion can give you data to scale the real ROI rate of campaigns.
This is one for your sales team! By improving customer relationships, product quality, and adjusting marketing campaigns as a result of sentiment analysis, you should be able to increase leads. In today’s connected world, happy customers are your best tool for good PR. They are likely to share to the world their enjoyment of your product, acting as brand ambassadors. This can help draw in new leads.