by Sherod A. Williamson
In every business decision, data is crucial. It is the responsibility of enterprises to perform the collection and interpretation of data. Subsequently, they can leverage the findings to determine the next steps they need to succeed. With large volumes of data accessible for many companies, the problem lies in using the right data.
Data comes in a variety of formats, but it gets divided into two categories: Structured data and unstructured data. Each concept interacts differently with customer experience (CX). Therefore, it is integral to manage data that impact customer perception and eventually affect their decision. This article dives deep into these concepts highlighting the difference between them when it comes to customer experience.
What is Structured Data?
Structured data is quantitative data in the relational database. Okay, but what does that mean? Structured data is measurable, discoverable, and definitive in a SQL database or file such as an .xls or .csv with defined columns.
A majority of companies are familiar when it comes to the navigation of this type of data. It is often highly organized in a database to be understood and interpreted.
To give you an idea, here are the most common examples of structured data:
- Phone numbers
- ZIP codes
- Customer names
- Product inventories
- Point-of-sale (POS) transaction information
If these things sound familiar, it’s because the forms you fill out in checkouts or sign-ups constitute much of the structured data companies have on customers. With vital customer information and sales statistics structured in an orderly fashion, they can be analyzed thoroughly. Data scientists rely on platforms, including spreadsheet, Customer Relationship Management, Enterprise Resource Planning, and Point-of-Sales Systems, to manage and study large data sets.
Benefits of Structured Data
As mentioned, most IT experts and data scientists recognize structured data because it has been the standard over the years. Here are more of the advantages of structured data concerning customer experience (CX):
- Seamless Integration to Machine Learning Algorithms
Since structured data is comprehensive and organized, professionals can easily manipulate and query large volumes of data at a given time. When the process streamlines, services are much quicker.
- Small and Medium-sized Businesses Find it Easy to Navigate.
Structured data offers a straightforward configuration process, which makes it easier for small and medium-sized enterprises. They can leverage large datasets without having to deliberate their relationship with other data. Simply put, structured data is more accessible and manageable.
Structured data has the competitive edge considering that it has been around longer than unstructured data as an asset. This competitiveness indicates that more tools get developed for managing this type of data. These tools have been tried and tested over the years to ensure that the results are accurate. In other words, companies can have more tools to choose from, which means they can quickly scale data up and down.
What is Unstructured Data?
Unstructured data refers to the volumes of data that cannot get processed through established tools and methods. It is often categorized as qualitative data since it cannot get organized in relational databases.
Thus, unstructured data gets managed by non-relational or NoSQL databases. A non-relational database such as MongoDB, and Couchbase are more fluid, flexible, and non-tabular than traditional relational databases. These are used for large amounts of diverse data in different formats.
It can also be handled raw, placed in a flow of data lake. A data lake is best defined as a large amount of raw data with an unknown purpose compared to a data warehouse that has large amounts of data that has been processed and filtered for a purpose.
To give you an idea, here are the most common examples of unstructured data:
- Mobile Activity
- Social Media Activity
- Satellite Imagery
- Surveillance Data
Benefits of Unstructured Data
Although unstructured data is not immediately usable for finding valuable information, when you use an Experience Analytics Platform (especially one powered by Smart AI™ like Stratifyd offers), you can uncover those insights to make informed decisions and take action. The insights hidden in unstructured data offers many benefits for CX teams in terms of improving customer experience, including:
- Improving Customer Relationships
Companies can leverage unstructured data to obtain an in-depth picture of their customer journey. They can analyze the volumes of data to figure out the practices that customers perceive well. Creating hypotheses to improve customer relationships backed by unstructured data offers fruitful benefits. From finding areas of improvement to backtracking the actions that made a difference over time, data delivers accordingly.
Companies began gathering unstructured data to determine the levels of customer satisfaction. This information can help them understand the reason behind their sales over the past and what they can do to improve. Many businesses also utilize unstructured data to evaluate customer service agents and how their responses impact customer satisfaction.
Structured Data vs Unstructured Data: What’s the Difference?
- Type of Data
The most apparent difference between structured and unstructured data lies in the type of data managed. Structured data holds definitive data that can be quantified and analyzed. Each piece of information is placed in rows and columns to get mapped into pre-determined categories. In contrast, unstructured data is collected and analyzed in its raw format.
- Storage Location
Another noteworthy difference between structured and unstructured data is their storage location. Large volumes of structured data remain in data houses, which refers to structured data’s endpoint. It goes through an Extract, Transform, & Load ( ETL) pipeline before reaching data houses. In contrast, unstructured data gets stored in a data lake, which is the repository for maintaining data in its original format. Data that gets backed up often goes to a data lake. Although both storage locations are accessible via the cloud, structured data occupies significantly less space than the latter.
- Format: Predefined vs Varied
Structured data often have a predefined format composed of texts and numbers. On the other hand, there is a variety of formats available for unstructured data. It may come in different shapes and sizes, from audio, video, and imagery to email and sensor data. Since unstructured data gets stored in its raw format in a data lake, it has no predetermined data model. Simply put, managing this data set does not require any transformation.
- Ease of Use
Ease of use is integral for small and medium-sized businesses that cannot afford the expense of acquiring the expertise needed with managing unstructured data. Structured data is relatively easier to handle, making the integration of machine learning algorithms much more manageable. On the contrary, analyzing unstructured data is more complicated. Data managers are required to process volumes of data before they can analyze the data collected. Not to mention that this type of information is tougher to configure due to the lack of a predefined data model.
Although there are already many tools for analyzing unstructured data, most of them are relatively new and still in development. Most data experts are more familiar with mining and arranging structured using professional tools and software. As a result, it can be more challenging to handle unstructured data such as rich media, blogs, social media data, and customer communication.
But the advance of artificial intelligence is closing the gap between structured and unstructured data. As AI becomes proficient at finding patterns and trends and anomalies in a company’s unstructured data, a much richer picture of the customer experience will be at hand.
Uncover the Value of Your Unstructured (and Structured) Data
For CX and contact center teams, the unstructured data they retain has long been an underutilized asset. With the advance of business-user-friendly Experience Analytics Platforms powered by Smart AI, the insights hidden within the world of unstructured data (alongside your structured data) is ready to move from the data lake to the executive dashboard.
Learn how Stratifyd can help your company excel (pun intended) when you sign up for a demo today.
About the Author
Sherod A. Williamson is a Sales Engineer at Stratifyd and serves as a critical link between our business and our clients, helping to discover business requirements and articulate technical solutions that meet our clients' and prospects' needs. When he's not doing that, he's practicing Jiu-Jitsu and building super computers for digital currency mining.