Data management is crucial for businesses of all types to succeed and create the ideal user and customer experience. To effectively manage data, it's important to understand the different types of data you can collect and analyze. Two main types of data include implicit and explicit data, which can help you better understand your audiences and how they interact with your business.
Technology is making data management easier than ever, with AI-driven data management and integration automation likely reducing IT experts' needs by 20% in 2023. While data management may become increasingly efficient, you must collect and comprehend the right data properly. Otherwise, you won't be able to effectively use this data to optimize your company's performance.
Here we'll dive into explicit and implicit data, including their differences and the advantages they offer for businesses.
What Is Explicit Data?
Explicit data refers to information that is directly provided or stated, often through explicit actions such as filling out a form, responding to a survey, or providing personal information.
This data is typically intentional and deliberate, and is often provided with a specific purpose in mind, such as signing up for a service or making a purchase.
Examples of explicit data include a person's name, address, email, phone number, or credit card information that they provide when making an online purchase. This information is explicitly provided by the user and can be easily captured and stored for future use.
What Is an Example of Explicit Data?
Generally, explicit data is the raw information that you receive as a business. There is a deeper meaning that you can draw from this data, as it may have specific implications attached to it.
An example of explicit data could be the information that people submit on contact forms on a particular landing page. This includes the person's name, occupation, and available times to reach them. Based on this information, the implicit data would indicate what type of person interacts with this landing page and when you're most likely to be able to reach them. For instance, busy professionals might be the implied main demographic for ads leading to a particular landing page, and the best time to contact these leads would be on a lunch break or after work hours.
Other forms of explicit data could include everything from star ratings and reviews detailing experiences to upvotes or downvotes of a post. These clearly indicate how an audience feels.
Explicit data could also be information about your business that your employees gather, document, and share. Internal teams can then use this data to make any necessary operational changes and optimize performance.
Why Is Explicit Data Important for Businesses?
Explicit data is important for businesses because it provides a direct and intentional source of information about their customers. You can easily share this data across your organization via tools such as manuals and databases.
There are several benefits of collecting explicit data for your business, including:
The Ability to Improve Customer Service and Internal Connectivity
Collecting and sharing explicit data equips your employees with the information they need to communicate with customers and each other more effectively. Everyone on the same team has access to the same clear data and can be on the same page with it, which will facilitate better internal communication.
Meanwhile, customer support teams can use this data to communicate better with customers, seeing as they have access to the data they need without turning to others within the organization. Customers will relay what their specific issue is, which your customer support staff can use to determine precisely what to do to satisfy customers. If a customer completes a contact form, for instance, they can discuss the specific issues they're experiencing in-depth, which will clear up any potential confusion your staff might otherwise have.
Also, having recorded explicit data will help minimize the risk of internal mistakes among employees if they have access to information about procedures and policies. This will increase your business's efficiency while also helping boost your reputation when employees can take the proper steps to handle customer requests.
Develop a Knowledge Base for Internal Teams
Explicit data can also help businesses put together knowledge bases for their teams. These databases could include details about the company, products, and services and ensure that everyone within the organization has access to the same information. This centralized platform can then make it easier to train new employees, and you can make updates to it over time as you collect more explicit data and your business evolves.
Secure Internal Data
By documenting explicit data, you'll be able to prevent any type of loss from occurring. Otherwise, someone who leaves the company with critical explicit data may hinder your company's ability to use this data. Securing and sharing this data across your organization would create redundancy and avert potentially devastating loss.
Improve Offerings
Using helpful explicit data can give you some insights you need to continually improve upon and streamline your product or service offerings. Whether you learn from the analytical data you collect through various tools or the data that customers provide you via surveys or other touchpoints, you'll be able to grow your business and find new opportunities to expand.
With the help of explicit data, you'll have the chance to learn about what's working and what isn't, enabling you to take the correct course of action to improve internal operations and external communications.
What Is Implicit Data?
Implicit data refers to information that is not explicitly stated or directly provided, but can be inferred or deduced from other available data. This data can provide insights into attitudes, preferences, and other underlying factors that may not be immediately obvious.
Implicit data often derived through analysis of patterns or relationships within a dataset, rather than from direct observation or measurement.
For example, if a customer frequently purchases certain products from an online store, it can be inferred that they have a preference for those items, even if they have not explicitly stated this. Similarly, if a user frequently clicks on certain links or spends more time on certain pages of a website, it can be inferred that they have a higher level of interest in those topics.
Implicit data can be valuable for businesses and organizations looking to gain insights into customer behavior and preferences, as it can provide a more complete picture of user activity beyond just the information that is explicitly provided. However, it is important to use implicit data ethically and transparently, and to ensure that any inferences drawn are accurate and supported by the available evidence.
What Is an Example of Implicit Data?
Implicit data may not always be clear, but you can gain it by interpreting the explicit data you collect if you don't have a means of getting it directly.
For example, a social media user may post about hanging out with a group of friends at a popular local hangout. Specifically, this post might read, "Last night I enjoyed finally getting together with Max and Tom at the old cafe."
Based on this seemingly simple post, you can infer different elements that enrich it and provide some context. In this particular example, we can first determine that Max and Tom are good friends of the poster. Additionally, we can assume that the "old cafe" is a popular hangout that they used to frequent, to the point where the user doesn't even need to mention its name. This post also establishes that a cafe is the ideal setting for these friends, and it also makes clear that it had been a long time since these friends had gotten together.
You can also look at people's website activity for another source of implicit data. For instance, a user might appear to spend a lot of time on computer technology websites and educational sites for programmers. These behaviors could indicate that the user is a programmer or training to become one.
There's no shortage of implicit data that you can collect and use.
What Is the Difference Between Implicit and Explicit Data?
In short, the main difference between implicit and explicit data is while explicit data is information that people voluntarily provide, implicit data is that which you must infer based on other data. You can collect explicit data through contact forms, reviews, surveys, polls, and signup forms, among other sources. Meanwhile, you'll need to make use of multiple data sources to collect implicit data in addition to explicit data.
Collecting Explicit Data
When collecting explicit data, you can use some of the following sources:
- Surveys — One of the best tools to use to collect explicit data is a customer survey. You can ask website or app users about their experience, or you can conduct customer surveys to find out what they think of your products or services. You can also conduct these surveys in several ways, with the ability to collect this data directly through your app or website, social media channels, and other platforms.
- Signup forms — If you require people to sign up to become registered users, receive newsletters, start rewards programs, or simply contact you, signup forms offer an effective means of capturing explicit data. You can ask for basic contact details along with other relevant information. For instance, you might request users to submit data about how they found out about you, their occupation and specific role, income level, and more.
- Online reviews — When customers review your brand, they'll be able to include honest details about their experience. They may specify what they like or don't like about your offerings, and they can rate them on a scale. Using this information, you can determine what's working and what needs improvement to provide people with the best possible experience.
Collecting Implicit Data
If you want to collect implicit data that you can use in addition to explicit data, you can use methods such as:
- Website or App Tracking
On your website, you can gather a wide range of information about your users and learn how they interact with your brand. For example, you could find out whether a specific ad or mention on social media brought people to your website. This could help determine which platforms and strategies get the most traffic and conversions. In addition, you can see how long people stay on certain pages, along with certain drop-off points that keep people from moving along their journey. Based on these drop-offs, you can figure out what's causing people to avoid converting.
- Transactional Information
You can also gather and analyze transactional data when customers make purchases or engage in another type of transaction. This data could include purchases, payments, and returns as well as other more in-depth data. In addition to superficial transactional data, you might be able to see what terms people searched in search engines or on your website to lead them to your products, for instance. You could also determine whether people explored your website or app more before returning to the page and completing a purchase. You can use this data to determine what products or other offerings interest people the most. Also, you can track order history and make relevant product recommendations based on it.
- Social Media Activity
You can actually get a mix of explicit and implicit data from social media. The explicit data may include comments and reactions that you receive on your posts, which can indicate what people think. Meanwhile, implicit data may include inferences from private shares that your posts get, the number of views your posts get, and other analytical data covering engagement. Using these insights, you can decide on the right platforms to use and figure out ways to optimize your campaigns.
- Analytical Data From Marketing Tools
Different marketing analytics tools can also help you see how your marketing efforts are doing. You might see who clicks through your ads, the number of impressions, the time of day when people click on your ads most often, and the device people use to view and click through ads. Based on your goals, you can determine which metrics to track and gauge which channels and strategies are performing best.
Conclusion
Both implicit and explicit data are crucial for any business. If you want to enable your brand's long-term growth and get the insight you need for continuous improvement, you must collect both types of data.
If you're looking for a way to engage users and collect valuable data, you can use Storyly to collect a variety of explicit data on apps and websites. For example, you can use surveys, polls, and reviews that encourage users to voluntarily share all kinds of information. At the same time, Storyly can complement your app or website experience with engaging visuals and messages. With the help of tools like Storyly, you can get the most from your data to fuel your business's success.
