How good data leads to happy customers (and more revenue)
It's no secret that data is among the most valuable assets an organization can own. After all, data-driven organizations are also nearly twice as likely (162%)1 to surpass their revenue goals. But, not all data is created equal.
Let’s start with a refresher on the two kinds of data: unstructured and structured.
Unstructured data is in formats such as text files, documents, PDFs, emails, and in images, videos, and sound files.
On the other hand, structured data flows into predefined models and formats. Because of the consistency and relational structure of the data, it is easier to ingest, easier to analyze, and more scalable—all characteristics that transform its utility and value.
However, unstructured data is continuously viewed as a blocker for organizations because it requires more time and resources to make it digestible by downstream systems.
It’s a no-brainer that the longer organizations put off digitization of processes that produce or rely on unstructured formats, the issue of poor/inaccessible data will continue to multiply.
Good data = Good business
Data isn't some kind of magic pixie dust that can be sprinkled over business processes to improve results. Quality matters more than quantity, and bad data is worse than no data: in fact, poor-quality data costs organizations an average of $12.9 million each year2.
To deliver value, data needs to be relevant, accessible, and, above all, actionable. And, it needs to be all those things at scale. From 64.2 zettabytes in 2020, the amount of data being created, captured, copied, and consumed globally is projected to almost triple by 2025, topping 180 zettabytes (that’s 180 billion terabytes)3.
As data continues to proliferate, the need to structure it becomes increasingly urgent.
Unstructured data = Growth roadblock
It’s estimated that 80% of an organization's data, on average, is unstructured4. And while it may have inherent value, that value isn't easy to extract.
For example, banks rely heavily on paper-based processes, one of the biggest sources of unstructured data. And, while you probably already transfer money, deposit checks and even apply for a credit card on your mobile phone, there are hundreds of processes at banks that are still manual, and cause frustration for employees and customers.
Let’s look at an uncommon and circumstantial process a customer might have to go through at a bank: setting up or changing their Power of Attorney.
Not only is this experience time-consuming, it’s also error-prone and likely leaves clients feeling frustrated and dissatisfied. By digitizing and updating the process, not only can the bank turn something that will take days to complete into a real-time exercise, it also frees up resources to work on higher-impact activities that generate revenue.
But, instead of just doing marginal improvements over time, converting unstructured data into structured formats from the start can improve a company's ability to access and use it.
Let’s take a closer look at the digitized Power of Attorney process:
This process is much more pleasant for customers, easier on bank staff, and reduces manual, error-prone work. And, best of all, it can be developed by business users—without IT involvement—to address key challenges involved in collecting and sharing structured data.
When data can be ingested and used across the organization, it supports the delivery of a highly personalized, seamless customer experience.
From data laggard to data leader
Organizations that are committed to delivering a best-in-class CX have to commit to increasing the ratio of digital experiences instead of manual ones. Personalized customer journeys that recognize each customer's unique context and needs can't exist without good data.
Post-pandemic, the importance of personalization is even greater. Customers are relying more and more on digital touchpoints and will be fatigued by manual processes they must wade through in order to get what they need.
Fortunately, it's easier than ever to evolve from data laggard to leader, even in legacy technology environments. Technology solutions in varying combinations can all be layered over existing legacy systems to help organizations structure data at the source, driving customer satisfaction and sales.
Sources and credits
1How a data catalog can help your business reach new heights. Database, Jan. 2021
2How to improve your data quality, Gartner, July, 2021
3Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2020, with forecasts from 2021 to 2025, Statista, Sept. 2022
4Search and unstructured data analytics: 5 trends to watch in 2020, Accenture, Jan. 2020