Text Analysis for Business Intelligence : An Outlook

Every business leader would outright agree that data is currency. However, few might be aware of the challenges of processing this data into actionable information. In business, finding out what other people think is a critical part of the decision-making process.

And there are growing opportunities for mining opinion-rich data from sources like personal blogs, social networks, news websites, and industry publications. But this data keeps changing every minute, and it’s unorganized, unstructured, and extremely hard to process with software intervention. Yet it contains critical business intelligence that could shape business direction.

Thankfully, businesses can employ text analysis software to help them sift through the endless textual data streams and extract quality information. ClicData shares a detailed outlook on the process. It includes text analysis examples that businesses can employ to improve the clarity of their decisions.

What is text analysis?

Text analysis uses AI-based technologies to extract valuable information from volumes of unstructured data. The software tools exploit machine learning and natural language processing (NLP) to make sense of this data. Text analysis software is more efficient than humans because it can read and interpret web data from multiple sources.

What is sentiment analysis?

Sentiment analysis allows business leaders to keep an active ear on the ground to make informed business decisions. Rule-based machine learning algorithms read the emotional context from text scoured on social networks and review websites and provide real-time reports and insights. Marketing executives, for example, can use this information to improve their brand positioning or sales strategies.

How it works

Machine learning and NLP are advanced artificial intelligence (AI) technologies that extract meaningful insights from review websites, news blogs, and social media posts. Natural language processing grants computers the ability to comprehend textual data like any human being. And machine learning studies newly acquired information and uses it to solve complex problems, improving accuracy every time.

Data collection

Text analysis starts with data extraction. Text mining is used to extract large volumes of unstructured data for analysis. Because it structures the data according to trends, keywords, and concepts, making it easy to perform qualitative analysis.

The data can come from:

• Internal sources like customer databases, sales reports, CRM software, email communications, chat apps, and feedback forms
• External sources like social media, news publications, review websites, and more

External data is a critical ingredient when building actionable business intelligence (BI). It can be collected using application programming interfaces (APIs), nodejs web scraping tools, and off-the-shelf software.

Language detection

Language detection is a convenient tool for text classification. It allows us to categorize and sort information while adding or removing bits of language-specific artifacts. You could skimp on it if you have software designed to work with a specific language by default. But NLP engines like Google Cloud Natural Language could be of great help if you’re building intelligence on a global scale.

Text preparation

Text preparation involves: 

• Removing unworkable items such as symbols, punctuations, and pseudowords
• Defining crucial vocabularies that will be scanned from the text
• Determining the grading categories for the predefined vocabulary and saving it to file

Sentiment detection and classification

Prepared data goes through algorithms that pick out vocabularies and order them into topics. The software scans the sentences and extracts and sorts keywords for classification. Grading algorithms classify the opinions to derive the overall context. For example:

• Feelings – Happy, Angry, Sad
• Experiences – Positive, Negative, Neutral
• Intentions – Interested, Not Interested

Reporting and presentation

Text analysis software helps with quick business decisions, thanks to its ability to process data faster than humans. The data can be visualized using charts, graphs, and pictograms. ClicData offers multi-format data visualization tools and customizable dashboards on its platform. 

Because executives have to act on up-to-date and relevant information, reporting systems need consistency. And it can be achieved through automation, with the system churning out daily, monthly, or weekly reports according to business requirements.

Text analysis examples for BI

Decision-makers have to grapple with massive data flows from different sources like social media and customer review websites. Here are two practical examples of how text analysis leads to informed decisions:

Social media monitoring

You can’t understate the importance of social media in the modern business world. As of 2021, 82 percent of the American population had a social networking profile. Globally, the number of users crossed the 4 billion mark, or half of the world’s population.

Millions of users rely on these platforms to connect with friends and entertain themselves. But many businesses have also been nurtured and grown because social media is a perfect place to find, review, and purchase products. 

Because the platforms are heavy on content, an infinite amount of data is shared every minute. And it’s hard for the human mind to analyze all this data, which is why we need text analysis software. It browses through millions of comments looking for brand mentions and customer sentiments. 

Monitoring the social networks is perfect for crisis prevention. We can pick up keywords that imply negative feedback and customer complaints and react quickly with a solution. One could also use it to observe the market trends and develop products that meet the changing customer needs.

Marketing intelligence

Businesses need to keep an active ear in the market to gather what people think about their brand/service. And text analysis can be used to connect business performance to what’s happening in the market. For instance, when trying to find the reason for poor sales performance, executives can use sentiment analysis to extract customer complaints and opinions from the internet.

Text analysis can also be used to gather competitor information. You can find out what users are saying about their products and use it to improve your offering. Sales and marketing executives can use the technology to qualify for leads and gain information on potential markets. 

How to leverage that text-based data to improve your marketing strategies

Many marketers grapple with eliminating guesswork from the marketing equation by studying the markets. Data sources have increased exponentially over the past few years, increasing the learning opportunities for business executives. However, crunching the massive volumes of data can hamper productivity. 

Textual data holds the key to transforming marketing decision-making across all industries. It allows marketers to be more strategic in their initiatives by acting on new market insights. Indeed, business executives who understand their customers have everything they need to keep them coming back for more. 

Executives can leverage text analysis to improve their marketing strategies in many ways:

Multichannel strategies

If you’ve invested in promoting your products on multiple channels, you’d want to identify the ones with the best results. In the old days, you would need to get this information from customers after a purchase. But today, the number of channels has exploded, making it hard to analyze and attribute traffic sources without technological assistance.

Leveraging technology, you can centralize and combine data from different sources in a data analytics tool to create a unified source of truth about your customers’ feedback. You can use it to track user sentiments, identify top-performing communications, and optimize your digital campaigns.

Another super handy feature is the ability to differentiate topics and prioritize issues. The software can interpret urgency in text messages and tag information according to predefined contexts.

Exploiting visualized data

Many people relate data visualization with graphs and charts, but these are just the tip of the iceberg. Having collected thousands of text communications from multiple sources, analyzing the data remains an overwhelming task. Even for seasoned professionals, it’s a strenuous activity that steals their attention from more crucial duties.

Text analysis allows you to make sense of data with visualizations and automated dashboards (real-time data). The visualization displays information in an easy-to-understand format, helping you to observe trends and isolate unique ideas. For instance, the data can map brand satisfaction to the historical performance of the service desk team. It can also reveal hidden causes of poor sales and more.

Real-time brand reputation management

Social media have propelled many unknown brands into profitability, but they have also been responsible for the death of many. Negative information spreads faster than good news. It is why many customers rush to social media when they need to vent out their anger over an unpleasant experience.

Sentiment analysis plays a huge role in controlling your brand narratives on digital platforms. A good platform lets you set up alerts when negative sentiment runs high on the internet, allowing for swift reactions to customer complaints. Marketers can also set up alerts for brand mentions to gain real-time insights on customer awareness and general attitudes towards the brand.

Unlock the value of your text-based data today

Text analysis is a time-saver tool that businesses can use to understand their customers and make informed decisions to improve profitability. It allows your management team to focus on more productive goals by relieving them from cumbersome text analysis tasks. ClicData is reinventing business using AI solutions that empower decision-making and performance at all levels. 

Our software connects with other platforms and:

• Collects data from different sources and collates it into a data warehouse
• Manages, processes, and reports on data using visualized dashboards and multi-format reports 
• Provides a collaborative platform for multiple teams

Our platform offers a high-level look at the hidden data affecting business, helping you capitalize on the missed opportunities in the market. Sign up for a free trial on ClicData and learn from our text analysis examples.