How many typed words are out there? Trillions?
What about all of the words in text messages, chats, surveys, reviews, call center logs, one-to-one emails, legal documents, bank records, health records, loyalty program data?
Text. Text. Text. Text. Text.
It’s everywhere. And it’s out there floating in a murky abyss, seemingly impossible to grasp its true massiveness.
While digital technology like social listening can help us harness the vast universe of online conversations from consumers, there is just as much, if not more, offline text out there wandering aimlessly, waiting for smart researchers and brand teams like you.
There are billions of data points hiding in that abyss, but, until recently, there has been no clear and effective way to mine them for key insight.
How do you capture a billion unicorns, let alone one?
Text analysis technology has changed the game. Now, businesses of all types can harness the trends and insights hidden within unstructured text from anywhere and everywhere. They can use it for predictive analysis and to understand consumers, customers, clients, patients and employees.
Here are just some of the teams that leverage text analytics that we will cover in this article:
- Customer Experience
- Human Resources
- Mobile Apps
- Polling and Politics
- Call Centers
- Law Firms
- Financial and Banking
Let’s peel back the curtain to see text analytics in action and lay out how you can leverage this data for your team.
What is Text Analytics?
Text analytics is the a.i.-driven process of translating unstructured text from any text-based property into data outputs that can be used for predictive analysis in a number of different ways.
Through a process called Natural Language Understanding, text analysis systems can learn and understand the intent behind any text and turn that into insight.
All text analytics platforms work a little differently. For our tool, InfegyIQ, we’re able to process any text-based data and accurately analyze it for sentiment, topics, emotions, themes and behaviors.
This process happens instantly, in a matter of seconds. And as you’ll see in this article, the types of text data that can be analyzed include chat and call center logs, medical or legal records, surveys and review sites and many more.
We broke down this process in a more detailed white paper about how text analysis works here.
Text analysis opens the door for businesses to gain unprecedented insight into what customers think about their experience.
You can quickly quantify and understand the massive amounts of unstructured customer feedback from any number of sources.
With so many ways for people to give you feedback about their customer experience, text analytics software makes harnessing that feedback simple.
It gives you an avenue to get to the heart of that feedback, truly understand the pain points and needs of customers, and help lead your team to address that feedback with the right solutions.
Restaurants and hotels, for example, ingest huge amounts of reviews and surveys about the travel experience and dining experience.
Instead of thumbing through thousands of individual customer comments, text analytics solutions can quickly analyze the words of guests to gauge experiences with a brand to:
- Learn what makes a customer loyal or disloyal
- Read all reviews online; search for specific terms related to the customer experience
- Find out if there is an emergency that higher ups need to be aware of like, “I got food poisoning”
- Benchmark a brand to another brand with food items, products, and other things like speed of service
- Understand the drivers behind predictive statements like, “I’m never coming back” or “I can’t wait to come back!”
You can use text analysis to diagram that mountain of feedback that is provided at any point in the customer life cycle. Text analytics can process all of that incoming feedback, process it and store it so you can contextualize and understand it all in one place.
The customer experience feedback data that can be analyzed includes but is not limited to:
- Point of sale data
- Social data
- Call center data
- Loyalty programs
- Review sites like Yelp, Rotten Tomatoes or IMDB
- App data
- New item/product/service surveys
- Email feedback
- Focus group data
Using this technology, your team can fully understand people’s customer experience at scale, learn what the consumer experiences are and address problems or take advantage of opportunities you never knew you had.
Text analytics software is used by marketing teams to process and understand what consumers think about the brand, the products, their needs, wants and pain points.
If you’re on a marketing team, this analysis provides vital details about these important customers and audiences to help you learn what they think and feel. This technology will help you get into the minds of consumers to better understand and predict their expectations.
Here are some examples of how marketing teams use text analytics:
What types of content and messaging should brands and companies be reaching their customers and target audiences with?
Text analysis can help tune into billions of online conversations, emails, messages and other text-based communication to listen and hear what consumers think and want. Using that information, your team can create the appropriate content that meets their needs, answers their questions and addresses their pain points.
Email subject line/copy predictions
Text Analysis could be incorporated into marketing automation and email systems in order to read, analyze and predict consumer responses to emails and use that data to inform future correspondence. Did that email subject line resonate with the recipients? You don’t have to sift through responses one-by-one. Instead, text analysis can find those answers for you.
Similarly as with email marketing, advertisers could leverage text analytics to understand consumer expectations and create appropriate communications for their target audiences.
Text analysis could be used to research and understand consumers to help build accurate buyer personas so that targeting is more accurate.
Then, ad copy and effectiveness can be gauged based on those personas in order to help advertisers improve both their targeting and messaging. Your advertising team can then use text analytics to analyze any interactions, communications, sales data or survey data that stems from the specific campaigns.
Perhaps no other marketing technology best utilizes text analytics for insight than social listening platforms. These platforms can read and analyze the billions of unsolicited online conversations from social media, web comments, and other online dialog to help brands and businesses gain an understanding of consumers.
We explored how social listening uses text analytics for actionable insight here.
If you work for a healthcare company or pharmaceutical brand, you know all about the challenge of trying to understand the the patient experience, as well as their needs, pain points, and satisfaction with treatments.
All healthcare companies have a ton of unstructured data from various places filled with information about these patients and consumers. What to do with all of these records, surveys and reviews?
Using the right technology, this documentation can be combined and analyzed for a more holistic view of the patient and their experiences.
Text analysis is beneficial to understand both:
- The healthcare-patient experience
- Patient Health Journey
Here’s a brief look at how text analysis solutions can be used for each:
Healthcare organizations, providers and companies can understand the life-cycle of the patient and their interactions within the healthcare system.
Analysis of records and documents about the patient experience are a crucial element that could be useful these teams. Patients fill out surveys about their experience, with either the healthcare, hospital, doctors, nurses, treatments etc. which can be processed by text analyzers.
They can receive in-depth details about patient experiences with everything from their ailments to treatments to hospital and medication.
Healthcare and pharmaceutical organizations can monitor trends in patient health, ailments, symptoms, specific medications, side effects and alternative medicines.
This could cover the whole patient journey, from symptom to consultation to treatment and afterwards.
- Chat transcripts with online nurses and other healthcare providers
- Doctor/nurse notes, text within online portals, transcripts from dialog with online doctor visits
- Doctor advice, notes about patient or lab results or patient commentary
- Documentation of what medicines have worked or haven’t worked and any side effects
If you’re on a team in the insurance industry, text analytics can help you do a number of important tasks that relate to helping customers manage their insurance situations, understand their needs and pain points, and discover instances of fraud or other insurance-insurer obligations.
Insurance teams can use text mining and analytics software for:
- Fraud detection
- Understanding consumer pain points and needs
- Claims management and analysis
- Insurance call center notes analysis
- Property and Casualty damage false claims and indicators of sinister activity
If you’re on a human resource team, you know the challenge of keeping track of employee experiences, sorting through resumes and job applications, and managing internal employee situations.
The cost of hiring and turnover is astronomical. How can you better understand the employee journey and their experiences?
HR is on the front lines of understanding the entire employee lifecycle from application, to interview, to hire, to employment and post-employment.
Here’s how human resource teams can use text analytics:
- Employee surveys combined with Glassdoor or other online data
- Discovering what employees love the most, what they don't like, what their companies can
- improve about their experience
- Scoring resumes/cover letters to find the best candidates
- Exit Interviews and documenting important information about how employees felt about their time while employed there
Text analytics helps you put together a clearer picture of the entire employee lifecycle from hiring great talent, understand what keeps employees engaged, and how to learn and close the loop with exit interviews.
Mobile Apps Developers
Mobile app teams can use text analytics in a number of ways to improve their app systems, discover bugs and other problems, understand consumer thoughts and sentiment and address specific feedback.
Here’s how mobile app developers can use text analytics:
- Phone makers like Android, Apple or LG, can sort out app reviews to zero in on issues and bugs that need immediate attention. Is there a particular version of the software that is seeing specific problems?
- App makers can process and analyze in-app messaging and customer feedback. For instance, a tax filing software like TurboTax could analyze the chat function to learn more about customer experiences in the app
- A team that works for a rideshare app like Uber and Lyft could document the customer feedback and complaints or notes sent from customers about their experience
- Food delivery app teams from companies like DoorDash and Postmates could analyze all of the “special instructions” sections to find common threads and better address customer needs
Poll the audience! You can get answers from people that matter, whether that is customers, voters, subscribers or any other polling participants.
Rather than sending out a multiple choice question through an online poll or a Tweet, you could get real, detailed information from those people by analyzing questionnaires and surveys quickly with text analytics.
Here are some of the polling capabilities of text analysis:
- You can understand how people and specific groups of people feel about politicians, policies, and elections
- For election campaigns, you can address issues that matter to the electorate with precision and a complete understanding
- Media teams can understand how people feel about candidates and politicians and how breaking news, controversies and voter sentiment are framing political campaigns and the national or regional conversation
- You can employ social listening platforms to analyze and monitor the web of online conversation for key analytics and trends
Call center teams from organizations of all types can leverage text analytics to learn more about the customers’ experiences that are documented over the phone.
For example, if a person calls to complain, the call center rep could instantly research to find they have had a previous bad experience on a survey but also are a member of a loyalty credit card. This person is a high-level person to keep happy. Utilizing text analytics within a CRM, a call center agent could quickly uncover this important information.
Call centers can use TA in various ways:
- Quickly access key customer information from past interactions with the company
- Analyze chats from social, phone, and web based platforms
- Combine their call data with other data brands/companies have on customers
- Get a broad overview or in-depth analysis of customer satisfaction and sentiment
- Discover and document key customer pain points, complaints, needs or reviews
- Discover and document important caller information such as insurance claims
- Monitor and analyze call center employee performance
- Predict call center needs, performance and successes such as: call volume, call timing, staffing obligations and scheduling and how to best handle customer calls
Your law team likely has figurative filing cabinets filled with documents, notes and communication. On top of that, each legal case comes with the deluge of research in order to build and support that case.
The fact is you quickly need to find the key information buried in all that paperwork to provide the best service for your clients. How do you find a needle in a haystack?
Here’s how law firms can use text analytics:
- Legal research: find, learn and understand previous documented cases quickly
- Electronic discovery: find and analyze relevant and important information about past cases and clients
- Contract review research to pinpoint key details
- Search through large sets of data to find trends or cases involving specific themes.
- Quickly find dated or older information from previous cases
- Get or find feedback from past clients and understand client satisfaction or case success
Financial and Banking
If you’re on a financial or banking team, you can use text analytics for many of the previously mentioned features such as customer experience and satisfaction, call centers and records.
But there are a few more ways to use the technology for your company or institution.
Here other instances of how financial and banking teams use text analytics:
- Credit Scores documentation and following up with those who’ve checked their credit score
- Record customer use cases or life cycles of taking and repaying loans
- Real-estate tracking and record keeping
- Search for instances of bank or financial fraud
- Using social listening for predicting financial markets and business opportunities
To see how text analysis solutions can benefit your team, you can get a free, personalized demo of our text analytics tool, Infegy IQ, today! Click here.