#1. Social Media Listening
Apart from being a medium of staying connected, social media has also become a platform for branding and marketing. Customers talk about their favourite brands and share their experiences all across social media. Leveraging sentiment analysis of the data available on social media with the help of text analytics tools helps to understand the positive or negative sentiments of users towards products/services and the impact and relations of brands with its customers. Furthermore, social media listening can enable brands to build trust with customers.
#2. Sales & Marketing
Prospecting is a nightmare for a sales team. Sales teams make every effort to improve sales and performance. According to a MonkeyLearn study, 27 % of sales agents spend more than an hour a day on data entry work instead of selling, signifying critical time is lost in administrative work and not closing deals.
Text analytics techniques help reduce this menial work with automation while providing valuable and specific insights to nurture the marketing funnel.
To give you an idea: Chatbots are employed to cater to customer queries in real-time. Analyzing this data helps the sales team predict the likelihood of a customer buying a product, perform target marketing and advertising, and make product adjustments.
#3. Brand Monitoring
Businesses fight tooth and nail to establish and brand supremacy. Today, professionals are paid to write false or hype reviews across the internet and social media. Also, sometimes customers often write angry reviews in the spur of a moment. Such reviews often spread across the internet like wildfire and do unmitigated harm to a company’s brand image.
Negative reviews often drive away customers. Studies show, 40% of consumers are put off from buying a product/service if there is a negative review.
Visual web scrapers and web scraping frameworks in text analytics empower brand monitoring, comprehending one’s brand evolution, and pinpointing aspects affecting one’s brand in real-time, thus, enabling businesses to take necessary action immediately.
#4. Customer Service
Businesses constantly endeavour to facilitate seamless customer service. Much of the customer churn factors occur due to customer service flaws. With text analytics tools, you can scrape together customer concerns/queries and feedback to streamline customer service processes. Aside from improving responsiveness, this can also help automatically route tickets to reduce manual work and errors. To give an example: the algorithm draws a point ‘My order isn’t delivered yet’ out of customer queries – this will be compared and matched with a Delivery Issues tag automatically with the assistance of text analytics tools.
Additionally, text analytics tools will also help establish personalized customer services, employ the right person for the job, and set priorities efficiently.
#5. Business Intelligence
Although businesses can glean “what is happening?” with data analysis, they struggle to figure out “why this is happening?”. Applications of text analytics help businesses obtain context out of the numeric data and reason out why a situation has happened or is happening or what may happen in the future. Case in point, a large number of factors contribute to sales performance. While data analysis will provide one with numerical statistics, text analytics techniques will help determine why there is a drop or rise in the performance.
#6. Product Analytics
Text analytics not just helps in understanding customer needs, but also helps in improving the product. Analyzing customer reviews gives a clear picture of what exactly the customer is looking for vis-à-vis a product and what they think about the competitor’s product. It enables businesses and brands to build quality products that meet customer requirements.
#7. Knowledge Management
We suffer from an overabundance of data today. Processing this behemoth data to draw actionable insights in less time is hardly possible without sophisticated technology advancements. This puts time-sensitive professions like healthcare in dire straits. However, text mining or text analytics techniques can help sort through surplus data in a short time and provide valuable insights for real-time solutions and efficiency.
#8. Email Filtering
Text mining can help detect junk, spam, or malicious emails, preventing fraud and other kinds of cyberattacks.
Text Analytics in 2021
Text mining or text analysis is useless without NLP. It intends to deliver practical, persistent, and credible insights with machine learning. The key objective is to arm businesses with real-time insights that help them drive innovation as well as rack up customer service and profits. The rapid growth in the requirement of understanding the customer will result in an increase in text analytics tools.
References:
1. https://www.wonderflow.co/blog/text-analysis
2. https://monkeylearn.com/text-analysis
3. https://www.cmswire.com/cms/customer-experience/text-analytics-what-are-they-why-are-they-important-to-cxm-019073.php
4. https://www.predictiveanalyticstoday.com/top-software-for-text-analysis-text-mining-text-analytics/