The world is changing, and customer expectations are getting higher. Customers want to get an answer to their questions faster and more accurately than ever before. They have become more demanding, proactive, digitally savvy, and vocal about their experiences.
Companies need to adjust their business models accordingly to stay competitive in the market. Businesses need actionable insights from every available data source to outperform the competition. Then, analyze previously unused data sources such as the voice of customers, employees, and images in an automated way.
What Is Unstructured Data?
Unstructured data is any data that does not have a predefined structure. It is prolific because unstructured data can be in media, images, documents, audio, sensor data, and much more. This information is often difficult to analyze because it doesn’t contain a standard format or schema for automated data processing and analysis.
Why Are Unstructured Data Sources Gaining Importance?
Data sources are growing exponentially, and this trend is likely to stay the same for a while; for example, more than 80% of data collected by companies is unstructured; that’s not just text but also images, video, and audio files.
Unstructured data allows businesses to capture customer experiences in their entirety — not just what customers say about products or services through surveys but also how they use them. The data helps companies improve products and services, anticipate future needs and develop new capabilities.
How Can You Gain Actionable Insights from Unstructured Data Sources?
Unstructured data is a critical information source for actionable insights. Traditionally managed in silos, unstructured data combined with structured data sources creates a holistic view of customers across multiple touchpoints. This view will empower you and your employees to track customer journeys, improve customer experience (CX) and capture new business opportunities.
Unstructured data comes in many forms, such as social media posts, email threads and chat transcripts. These sources provide context that traditional data sets don’t access — but it’s difficult for computers to parse this information into something more usable by humans.
Unstructured Data Sources for Improving Customer Experience (CX)
The number of unstructured data sources available to a business has exploded recently. At one time, the primary source of customer data was transactional or CRM. Today, the options are nearly limitless.
They originate from multiple sources, such as:
- Channels
- Devices
- Interactions (through emails, websites, social media, and other touchpoints)
- Touchpoints (online and offline)
For example, suppose you’re trying to improve customer experience. In that case, embracing an omnichannel mindset is one of the most significant shifts you’ll make in your business thinking. It goes hand in hand with prioritizing CX.
Customers use a range of offline and online channels to connect with brands, often switching multiple times. However meandering and unpredictable, every part of the journey must be consistent and connected.
The Modern Customer Journey
Understanding that the customer journey is more than one touchpoint, certainly not linear. Customer experience should be like an interactive storyboard, with the user making choices and interacting with various brand elements using additional resources on their journey.
In other words, you need to create an omnichannel strategy for your brand to win over today’s and tomorrow’s customers.
How to Use Customer Data to Improve CX
Your goal is to use the data you have to create a personalized experience for each customer. Knowledge gleaned from the data empowers your employees, gives them insight into customers’ needs and makes it easier for them to help people when needed.
For example:
- Leverage customer data to improve the customer journey by creating a centralized track for customers to interact with your brand
- Empower employees with customer data to help your teams create presentations to clients and prospects
Improve CX with Unstructured Data Source Analysis
Now is the time to take a deeper look at unstructured data sources.
For example, consider customer reviews on TripAdvisor and Yelp. These sites allow customers to offer feedback about restaurants, hotels and other businesses in your portfolio. Use review data for actionable insights on product quality or service – the reviews also work as brand advocacy.
More sources provide valuable information about your customer’s experiences with your company. Consider using chat logs with customer service representatives (CSRs), customer engagement and brand mentions on social media posts and customer survey data.
All these sources offer unique insights into how people feel about your experiences with you thus far—or what they might expect from future interactions with your organization. By combining information from multiple sources, you can gain insights that help you improve service quality, reduce churn rates, and increase customer loyalty.
Use Unstructured Data to Empower Your Employees
Employees can leverage data science and analytics tools to unlock insights from unstructured data to help them make decisions. Previously, information in unstructured data; for example, customer service call data, was challenging.
A next-generation platform integrates this information with other sources. It ensures that it is available to employees while also ensuring its accuracy.
Provide employees with access to the resources they need
Employees often know what unstructured data may be but need help finding it or how much data there is. For example, an employee looking for refund information would need to search multiple files and folders to see it, thus losing focus on their day-to-day tasks.
However, with ‘inquiry labeling,’ they can search quickly by filtering the relevant inquiries by labels such as “refund.” This helps other employees know what to look for and quickly narrow down their search results.
Structuring unstructured data can help companies perform root cause analysis of customer issues. For example, a surge in returns for a product may be due to poor instructions on how to use it or a misleading listing description of what it does.
Provide employees with the tools and opportunities to spend time with customers
AI-powered audio transcription allows employees to spend more time listening to customers and less time typing notes into a computer. This solution makes calls searchable and easily digestible with a quick read.
Converting audio into text is time-consuming and often results in inaccurate transcripts. AI can help automate the transcription process by using algorithms to listen, understand and transcribe audio files with minimal employee effort.
Personalized employee experiences for increased customer satisfaction
A one-size-fits-all approach to customer service results in a highly impersonal experience for your customers. Treating everyone equally and delivering impersonal experiences alienates them, reducing brand loyalty and business.
Unstructured data contains nuggets of mineable, leverageable information, which is helpful for personalized customer experiences. Website visitor location, for example, enables employees to interact with customers and prospects personally.
As AI and machine learning capabilities improve, employees can use them to predict the reasons for customer inquiries and suggest resolutions to problems.
In the future, these capabilities may enable machines to perform sentiment analysis, proactively alerting employees if a customer is very angry or delighted.
Employees who work in teams are more effective than those who work alone
Data silos can create friction between teams and departments in a business context. When your employees don’t collaborate because of data silos, their teams are not innovating or solving problems in new ways. They may even burn out!
A customer dealing with many employees, each of whom has their view on the issue, experiences frustration and disconnection. Removing data silos and putting all your data in one place unifies employees and teams. Based on a single data source, teams can confidently make decisions together.
Knowledge sharing can improve the quality of a company’s products and services
A unified customer database makes it easier for employees to learn from one another. When someone has a question about a customer, they can easily find the answer by searching through your system. That way, everyone working on the project is up-to-date, and no one is stuck trying to remember their last customer chat or email.
Unified customer databases also make it easy to find what customers want. Easy access to sales history allows your teams to offer superior customer service.
Take Action
The customer experience is changing. Customers are more empowered than ever and expect brands to act accordingly.
They want to be listened to, valued and treated like an individual. When it comes down to it, customers want their voices heard – but how can businesses do this when they’re drowning in data?
How can brands offer a seamless customer experience through unstructured data? The answer lies in personalization: anticipating customer needs and desires so that interactions with your brand feel natural, intuitive, and human.
Author Bio: Gunalan is in Strategy Marketing at CINNOX, a comprehensive digital transformation for businesses by converging digital and traditional channels, AI and human intelligence, as well as data from different sources on a single platform. With a passion for sharing know-how with businesses, and helpful information with creative professionals, he also writes on Medium, e27, and Linkedin.
Stefanini Understands the Power of Data Analytics
Whether you need assessment, expertise, training or ad hoc support, our global teams offer various ways to guide businesses with data-driven strategy.
Modern businesses have access to more data than ever, yet many organizations miss out on their data’s potential. Businesses that cannot properly collect and analyze data will likely struggle to provide consistent and relevant customer experiences. Gathering data isn’t enough. It’s easy to become overwhelmed with information and struggle to identify actionable insights.
Done correctly, data analytics allows businesses to embrace a strategic approach based on genuine insights.
- Create new products
- Identify new market opportunities
- Improve customer experience
We use advanced artificial intelligence (AI) technologies, natural language processing (NLP) and machine learning (ML) techniques to help clients monitor product and brand sentiment in customer chats, call centers, social media posts and more. When a business wants to understand where it stands and what its customers need, this analysis technique delivers results.
If you are ready to grow, Stefanini is the ideal partner with solutions that help you know your customers and audience. Reach out to an expert today.
