Data Collection 101: The Complete Guide to Collecting Data

Data collection is a pivotal process for many industries in today’s global business landscape. Since organizations rely on data to ensure day-to-day operations, from executive decisions to marketing strategies, everything starts with data collection.

The method through which organizations collect data, and to what extent and goal, can be detrimental to the organization’s business success. This article offers a comprehensive insight into the data collection process, how it impacts a company’s marketing strategies, and many other aspects.

What is Data Collection?

At its essence, data collection is a process involving pulling data from a distinct source with the intent to gather insight into a particular topic of interest. From a user standpoint, the process of data collection was deployed through different data collection methods, including surveys, interviews, and focus groups as part of the field and market research.

However, as industries (and demand) advanced, so did data collection practices and end goals. In the past 20 years, collecting data has encompassed automated data collection with the internet, apps, and devices as the main sources.

Today, data collection stands as a crucial element in the process of data analytics and research. In that context, data collection delivers information that’s used to analyze a business’ performance or other crucial outcomes, as well as predict future trends, actions, etc.

Understanding Data Collection Basics

In general, data collection is the process that combines gathering and analyzing information involving relevant variables in a methodical, predetermined manner. Data collection can help businesses answer particular research questions, examine specific hypotheses, and, ultimately, assess results. Data collection can be qualitative or quantitative. The process of collecting data can be deployed at various levels when it comes to businesses. For example, IT companies collect data on customers, sales, employees, and other relevant aspects on a daily basis.

Companies of other business profiles are collecting data through surveys, polls, and other data collection methods, as well as tracking social media to gain insight into their customers’ feedback. Subsequently, data engineers, data scientists, and other data professionals use the collected data to analyze it and make decisions.

First-party vs. Second-party vs. Third-party Data Collection

There are three main methods of data collection: first-party, second-party, and third-party data collection. The first-party data collection (also known as primary data) is the data that the company directly gathers.

Second-party data refers to data collection performed by another company and is then shared (or sold) to another party, usually a non-competitive partner. Regarding third-party data, the process involves a data-collection company that harvests the data and then shares it with interested parties.

The golden rule of data collection states that the closer you are to the collection of data, the purest data is, aka, the higher the quality.

The longer the time between collecting data and its use, the greater the chances of data becoming outdated and irrelevant. In summary, first-party data is inarguably the most reliable and one-of-a-kind information coming from your sources. Second-party data is shared with reliable partners and can be less accurate and of lesser quality. Third-party data is the most unreliable data coming from unknown sources.

What makes data quality utterly important to businesses is the ability to use that information for vital business decisions you could not make otherwise. High-quality data is reliable, accurate, and wholesome.

Quantitative vs. Qualitative Data Collection

Quant data, as it is also referred to, comprises numbers and can be automated for digital analysis. On the other hand, qualitative data, also known as qual data, consists of words that require a more manual approach involving processing and interpretation.

Quantitative Data

The majority of data that modern-day businesses collect is quantitative data. Information like website visitors, transaction records, and conversion rates are all quantitative data.

The process of collecting, storing, and analyzing large volumes of quantitative data is pretty affordable and streamlined. This is the main reason most businesses rely on quantitative data.

Qualitative Data

As opposed to quantitative data, qualitative data revolves around customer behavior and the motivation behind it. Since it offers a more detailed (and valuable) insight, it costs more than quantitative data collection. Additionally, qualitative data also requires more effort. Interviews, market research, and focus groups need a human approach; hence, there are more costs regarding travel, facilities, and so on.

However, with the technological breakthroughs, qualitative data is becoming more accessible. Businesses can run virtual focus groups or interviews that deliver the same insight minus the overhead costs. In that context, qualitative data collection is rendered more affordable, easier, and faster to complete.

The Data Collection Process Explained

A well-rounded data collection process includes several vital steps to a positive outcome. Collecting data begins with identifying a business or a research topic. In this context, it can be beneficial for businesses to assess their capabilities from an internal and an external point of view. The reason behind this is that it delivers a better understanding of your business operations.

Collecting data includes several steps, such as ensuring you meet relevant data requirements and identifying data sets that can deliver relevant information. You should also create a data plan, including the data collection methods you wish to employ. The most important steps of the data collection process include collecting data and preparing it for analysis. Lastly, you are in a position to use the results to create an action plan.

Maintaining the integrity of data is as important as working with high-quality data. Data integrity refers to the accuracy, consistency, and reliability of data and is a vital element in the process of data management.

To ensure data integrity, some of the best practices include:

• ensuring that data is accurate and free from errors or inconsistencies
• data is protected from unauthorized access, tampering, or breaches
• data is consistent throughout different databases or data sources, etc.

The Role of Data Collection in Marketing

In the advertising and marketing industry, data collection is everything. It’s an asset that helps businesses gain a better understanding of their customer’s purchasing behavior and preferences. Most importantly, data collection is the tool that helps businesses of all scopes and sizes create meaningful, optimized campaigns.

Before anything else, data collection enables marketers to get to know their customers on a more personal level. In other words, marketers gain insight into customer demographics, behaviors, and interests, which translates to businesses being able to modify the campaigns and messages they send out to their customers. This personalized marketing tactic drives engagement and conversion.

With the right data results, businesses can create and deploy marketing campaigns that truly appeal to the potential customer.

Data Collection’s Impact on Marketing Strategies

Instead of going for a generic approach, data-driven marketing strategies allow businesses to market a product or a service that truly resonates with their targeted audience. By adopting such an approach, businesses make room for higher conversion rates and enhanced customer satisfaction.

Nothing yields tangible marketing strategies quite like quality data. Using such an asset empowers marketers to tweak their marketing tactics and gain a competitive edge. Additionally, the company is in a position to capitalize on emerging opportunities.

For instance, if a small business collects third-party data, it is not in control of what type of data it has gathered and is also not certain if the data is relevant to its line of work. On the other hand, collecting first-party data ensures the information is closest to its original source and is relevant to the collector. In terms of marketing strategies, real-time data enables businesses to create products and services that matter and appeal to their customers, addressing the most relevant pain points.

An E-Commerce Data Collection Success Story

Let’s take a company in the e-commerce sector as an example. A small but promising e-commerce company wanted to improve its marketing efforts by targeting specific customer segments. The decision-makers wanted to approach the issue by creating personalized offers and recommendations but were unaware of their customers’ preferences.

Initially, the company had access to a large amount of raw customer data but needed a strategy to make the most of it. Here is where data collection came into play. The company gathered data regarding customer demographics, browsing behavior, purchase history, and customer feedback. Data operators filtered and processed the raw data, removed duplicates, handled missing values, and unified the data formats. Ultimately, the company segmented customers into separate groups based on their attributes and customer behaviors. Data operators analyzed every segment to gain a better understanding of the customers’ distinct traits, preferences, and requirements.

Based on the analysis, the company created a personalized marketing tactic targeting each customer segment. For instance, it created custom email campaigns, product recommendations, and appealing discounts to motivate customers to engage.

Enhancing Customer Experiences

Knowing what your customers need is the first rule of business, but it is an insight that isn’t easy to attain. With data collection, businesses —both big and small—can effectuate raw data to the extent it delivers insight into different customer segments. For example, if you’ve previously gathered information regarding poor customer experiences and are willing to better that segment of your business, you can use data collection to address that pain point.

Once you collect the right data, you should give it proper thought, i.e., take a corresponding action. Make sure you focus on the WHW rule: What, How, and Why.

• What can you do with this information?
• How can you use it for best results?
• Why should you use it?

Additionally, you can use diagrams and charts to boost the significance of the information and present it to relevant decision-makers. This process will help you transform data into meaningful customer experience data.

The Power of Insights: Decision-Making and ROI

Decision-making is an inevitable process, no matter how big or small of a business you run. In today’s data-driven world, successful businesses are focusing on making data-driven decisions as a way to maximize their data. By doing so, businesses are leveraging resources and identifying ROI opportunities in the most effective way.

Data-driven decision-making rests upon analyzing collected data utilizing an array of collection methods. This is done to ensure relevant questions are answered, and the best business decisions are made. In this context, decision-makers — executive or operational — are able to compare, judge, and determine the right modus operandi and define an overall strategy.

Regardless of whether you’re the Head of marketing or sales, you rely on marketing tactics to drive ROI up, and in that context, data collection empowers you with the right tools. When you employ the right marketing strategy by addressing the main pain points of your customers, your business is on its way to increased ROI.

Customers are able to find exactly what they’re looking for, and your return on investment is bound to go up.

Privacy and Ethical Considerations

Where there is data, privacy and security issues are inevitable. Data governance is an important process to protect the customers, and it should be a top priority for every business handling data.

To ensure the ethical guidelines are respected, companies that rely on data analysis should clarify their intentions before their customers. For instance, if your business develops apps, make sure you inform the users of your data collection practices. It doesn’t matter if you collect customer data as a first or second party. You are solely responsible for maintaining customer data protection. When your business collects, interacts, and/or stores data, you are committed to protecting that data from malicious actions or wrongdoings.

The Future of Data Collection in Marketing

As technology advances, the potential for novelties in data collection increases. For instance, AI-driven analytics and predictive modeling can clean data and optimize its quality. Predictive data modeling allows for larger volumes of data to be fed into data systems, including customer-centric operations. In this context, businesses gain a more accurate forecast of their actions.

In the marketing industry, one of the fastest-growing industries today, predictive modeling is used to identify different customer trends and behaviors, including purchasing habits, demographics, and customer preferences. Subsequently, this will allow businesses to optimize their marketing strategies and improve their ROI.

Leveraging Rivery for Data Collection

When handling data, Rivery is at the front and center. As a fully managed SaaS platform, Rivery provides a cohesive platform that unifies different data processes, including data ingestion, data transformation, and data orchestration.

Rivery’s user-centered interface makes it a suitable choice for non-technical users to reap the benefits of data processes, but it is also a robust tool for professional data operators. Thanks to its no-code rivers and highly-rated customer support, users won’t have a hard time getting Rivery up and running.

With Rivery, users get the following options:

• An extensive library of pre-built data workflow templates for seamless data pipeline creation;
• The tool handles the backend, empowering data operators to spend time more effectively and prioritize tasks rather than maintenance;
• Full scalability;
  Adaptable to multiple environments, allowing users to construct and clone custom environments for specific teams or projects;
• Reverse ETL features to automatically send data from warehouses to marketing clouds, CPDs, business applications, and more.

Data Collection: The Ins and Outs

Without insight into data, businesses cannot fully optimize their marketing strategies and leverage their valuable resources to reach a predetermined business goal. Since everything runs on data, data collection stands as the ultimate process that makes or breaks businesses.

Whether you’re a small business owner looking to reach a wider audience or a global corporation looking to optimize massive loads of raw data, data collection is the logical step. One of the many advantages of data collection is that it is a versatile process that can be applied in many industries, from marketing to healthcare.

With the right data collection tool at hand, you are ensuring you extract the most value from data and use it in the most profit-yielding manner.