Types of data collection

What is data collection?

In a business setting, data collection is the process of gathering detailed information for further analysis to help make decisions. It involves companies collecting information based on targeted variables or specific data points and using that information to answer questions, measure performance, and create strategies to guide the organization.

Critical to any data collection effort is the accuracy and consistency of the information. Without this, businesses risk drawing inaccurate conclusions or misunderstanding their strategic landscape. Leaders need to understand the data they collect, the goals they have for it, and the process to follow to maintain consistency.

Data can be gathered by a number of different methods, including first-, second-, and third-party collection. Whether companies collect data directly from users or access information through partners or vendors can affect the data quality and quantity.

The highest quality data will always be gathered from users or customers by the company itself, and it can be done through a number of different channels. We’ll dive into this more below, but some common examples include digital surveys, transactional tracking, online visitor tracking, and interviews.

Types of data collection

Quantitative vs. qualitative data

Quantitative data is information that has a numerical quantity or can be counted, such as financial costs. Benefits of this data collection type include that it’s:

• Easier to collect than quantitative data
• Faster to analyze, as it deals with numbers
• Less likely to involve bias since it reports on figures rather than features
• Useful for drawing business conclusions across a broad scope

Qualitative data applies to observable attributes that can be evaluated but not objectively measured, such as descriptions or reviews. In contrast to quantitative data, it can:

• Give users more detailed insights into when, where, and why a behaviors is impactful
• Go beyond the basic impact it has or how much is impacted
• Lead to a better understanding of consumer experiences and opinions to provide more value.

Primary vs. secondary collection

Primary data collection refers to information gathered firsthand by the company or a researcher. An example would be a survey put out by an organization to its customer base directly. Analysts for this data can be sure the information is reliable since they know the source and control the collection methods. However, this method can be time-consuming and cause delays for projects where faster data would be more beneficial to meet deadlines.

Secondary data is information procured through other sources where the collection has already taken place. This data can sometimes be older or less relevant since the circumstances around its collection were not controlled by the company using it. However, it can provide insights beyond the source to which a business has direct access.

What are the benefits of effective data collection?

Data can be highly valuable for businesses, but only if it’s collected effectively. Effective data collection involves the curation of a series of data points that align with specific questions or areas of analysis, helping leaders make predictions and investigate trends.

Ineffective data results from poor collection processes that lead to issues such as duplication, inaccuracy, or incompletion. When reviewed, this information does not tell leaders a story they can use to make informed decisions.

With accurate and relevant data, leaders can:

• Improve precision when targeting customers
• Find new customers
• Understand customer behaviors
• Reduce errors
• Enhance or refine marketing efforts like market segmentation

Effective data collection drives smarter decision-making and organization-wide improvement, influencing everything from product sales to customer service. It can increase operational efficiency, consistency, and transparency while boosting the bottom line.

What techniques exist for data collection?

There are a number of different data collection options available to businesses, depending on their needs, resources, and goals. Traditional information-gathering techniques include surveys, observations, and interviews, but today data is often collected from online activity.

Surveys

Surveys are best when you want a sample of specific responses across key groups. The same questions are presented to everyone polled, who provide consistent answers that can be easily totaled and compared for analysis. Digital surveys are more common today, and they can be used to gather both quantitative and qualitative data.

Observations

Data can also be collected in a series of observations. Business analysts can observe an occurrence, or a series of occurrences, and then determine patterns or variables to inform decision-making for a particular issue.

Interviews and focus groups

Similar to a survey, interviews and focus groups present a series of questions to a set of people and record the results for tabulation and analysis. Focus groups include multiple people at a time who are urged to interact with one another while forming their opinions. Interviews typically are one-on-one sessions that allow the observer to gather specific data and ask follow-up questions.

Online tracking

Many companies employ online tracking to collect data on customer and prospect behaviors. Using tactics like tracking cookies, businesses can monitor user behaviors and collect information, including clicks, shopping preferences, device use, location, and search history.

Forms

Online forms are one of the easiest ways for companies to collect user data. While the best forms are streamlined to only collect essential details, many companies use them to collect additional details or progressively fill out customer profiles along the way. The Adobe Real-Time Customer Data Platform (CDP) helps companies collect user and account profiles in real time.

The importance of accuracy in data collection

The data-based decisions that leaders can make are only as good as the quality of the data they have available. Managing and curating accurate data leads to improved results when making predictions or identifying trends. Businesses can rely on integrated data to define strategies, but only when that data is reliable.

Data inaccuracy takes many forms, including:

• Incorrect data entry. Imprecisely entered information can result in mistakes or an inaccurate understanding of target audiences.
• Non-standardized data. Poorly formatted data can make it difficult to identify patterns and summaries findings effectively.
• Duplicate data. Redundant information can misguide leaders when reviewing datasets.
• Outdated data. Old information can be inaccurate, so data should be refreshed and procured regularly to provide real-time, relevant decision-making support.

To avoid these pitfalls and maintain accuracy when collecting data, leaders need to:

• Use reliable data sources. Gather data firsthand and control the fields and inputs allowed to ensure consistency.
• Understand what to collect. Evaluate the information collected against internal strategic decision-making goals.
• Reduce bias. Make interfaces easy to use and gather information as objectively as possible across representative population samples.
• Consider automation. Look to automate data collection and input for increased efficiency and additional insights into customer behaviors.

Best practices in data collection

Let’s take a look at some of the best practices for data collection, including storage and security.

Exercise transparency

Be open with customers about where and how the data collected will be used and allow them to opt out easily if they prefer. This can go a long way in building trust with customers and prospects while avoiding legal problems.

Write in plain English

Use easy-to-read language when explaining data policies to improve transparency and allow individuals to understand both your goals and their rights.

Ensure data is correct

Use the right tools to streamline data collection to ensure consistency and accuracy across all input methods and for every technique.

Protect your data

Make sure your data is secure by following industry standards like using backups, encrypting data at rest, and running antivirus software — to name a few.

Adobe Real-Time CDP includes security features, such as policy tools and data usage enforcement, to help users at all levels follow best practices for data collection

Getting started with data collection

By now, you’ve learned about the benefits of collecting data, how to manage different types of data collection, and best practices. Now it’s time to put this knowledge to use. Here’s a brief step-by-step guide to getting started with data collection:

1. Identify the issue. Clarify what should be deduced or solved by collecting data for a particular initiative.
2. Understand the requirements. Confirming the information to be collected will give you the data you need to guide decision-making.
3. Determine methodologies. Make sure the data needed can actually be collected and extrapolated successfully.
4. Set a scope. Confirm which population size and type will give unbiased, detailed results for the goal in mind.
5. Decide on a format. Choose how to house the data so that analysts can access, display, and evaluate it most effectively.
6. Finalize a plan. Create a data collection plan that includes operational definitions, scope, limits, methods, tools, strategy, steps, and formats.

Data collection tools

To capitalize on these steps, marketers and business leaders need to build out a robust toolset that supports the automation and collation of information collected.

How Adobe can help with data collection

How Adobe can help with data collection

One thing to keep in mind is how you plan to unify and review the data collected across a series of disparate tools. Adobe Real-Time CDP offers a centralized platform for leaders to collect and review company data across channels. Built-in options for data cleansing, such as deduplication, help keep information streamlined. And advanced dashboards provide insights into the data to make it actionable in ways that do not require IT intervention.

Adobe Experience Platform also supports integration with a number of client-side sources, helping users enrich and transform data into usable information. Data can be collected from web-based applications, as well as mobile apps and over-the-top (OTT) applications.

To learn more about Adobe Real-Time CDP, watch the overview video or take a product tour today.