Chief revenue officer of Chatmeter.
getty
Many estimate that 80% to 90% of the world's data is unstructured.
Marketplaces have existed for as long as humans have engaged in buying and selling. The markets of the past, including agoras, bazaars, souk, mercados and so on, are no different than the ones today in their quest to beguile customers to buy goods. However, in the modern marketplace, that act of enticement is often performed through the veil of cyberspace, which adds layers of complexity to what once was a wholly human negotiation.
Every year marketers spend hundreds of thousands of dollars on research, analyst reports, focus groups and carefully crafted persona-inspired messages to improve CX and drive customers to their brands. But as the chief revenue officer of a company that offers listing and reputation management solutions that leverage voice-of-the-customer insights, I believe that process frequently overlooks the virtual treasure trove of straight-from-the-voice-of-the-customer insight that could help them take CX to the next level: unstructured data.
Our world runs on structured data that live in relational databases and data warehouses powering our enterprise resource planning (ERP) and customer relationship management (CRM) systems and enabling the most mundane of daily activities, such as making reservations or processing credit card transactions.
Unstructured data is all the unorganized chatter dispersed across emails, social media, online reviews, images, photos, emojis, customer service calls, chats, messages and more. Approximately 80%-90% of your customers' conversations are captured in unstructured data. At Chatmeter, we believe that companies should work to surface unfiltered voice-of-the-customer insights and trends for creating a total customer experience. It is in unstructured, emotion-based data where you can find the clues that help reveal your blind spots, misplaced assumptions and incorrect assessments about the human beings you call your customers.
Mining massive amounts of unstructured data from an increasing array of sources is a daunting prospect. However, companies can also leverage machine learning, natural language processing and AI to tackle the task by scraping millions of online reviews and comments and analyzing relevant keywords, prevailing topics and the sentiment expressed.
Turning Unstructured Data Into Actionable Insights
Sentiment analysis reveals repeated themes—positive or negative—that give businesses intelligent information to inform decisions and pinpoint issues before they get out of hand. For example, if mentions of "cleanliness" linked to one-star reviews begin emerging as a negative theme, you can drill down into the data to determine the specifics. Is this a hyper-local problem at a single location or a recurring issue across your brand? Is it in the dining room or the restrooms? Is it something employees are doing? Is it happening in the parking lot?
Testing New Products Or Services Through Unstructured Feedback
Tapping into unstructured data is one way companies can test changes with new customers. You can track keywords across all location reviews and social channels to determine if customers mention the change. Businesses can use unstructured data to test the market and quickly assess consumer response.
Identifying Blind Spots By Combining Structured And Unstructured Data
Measure the themes emerging in structured feedback against raw emotional unstructured sentiment from customers. For example, if a hotel chain notices comments on TripAdvisor and Google about lengthy check-in processes, it can explore the issue via structured sources of customer feedback, such as by retooling its customer satisfaction survey questions to probe for the check-in issue.
Three Steps To Harnessing The Power Of Your Unstructured Data And Choosing The Right Solutions
1. Determining How You Want To Use Your Unstructured Data
Are you looking primarily to perform text analysis across social media, online reviews, surveys and so on? Or do you want a single connected solution that combines all aspects of online reputation management? Are you a multi-location business that wants to understand and compare customer sentiment across 10 or 10,000 locations over time? Or, perhaps you're a single enterprise in need of a data science platform primarily for building predictive models.
2. Selecting The Solution That Best Meets Your Needs
From Excel and Google Sheets to open-source data analytics platforms that demand data science engineers and experienced coders, there are myriad tools in the marketplace offering solutions for every level of complexity and engagement. Consider these questions to help you on your decision-making path:
• Do I want a straightforward solution covering all my reputation management needs, or do I want a solution for a specific use case?
• Do I need a highly customized solution or a generalized one? How much data do I need it to process?
• Am I looking for a low-to-no-code tool or one that our coding and technology teams can manage?
3. Establishing Internal Rules And Reporting
Determine onboarding technical and training requirements and establish the team who will interact with and support your chosen unstructured data analytics solution and report out. Identify and schedule customized, location-specific reports to distribute across departments, locations and regions to ensure that everyone has visibility throughout your enterprise, from the boots on the ground to the C-suite.
The Connection Between Customer Satisfaction And Business Results
According to a 2020 report from Qualtrics, "Of the respondents who rate their company's [experience management] as 'significantly above average,' 89% report better revenue growth than competitors in the previous year." It's important to develop more human-centered, authentic relationships with consumers. It can lead to the kind of champions who readily and freely share their brand love and spend their dollars.
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