In Data 101 for Marketers, we’ll cover the basics of data you might encounter as you seek to take control of your data, improve your analytics, and get more value from your MarTech investments. This includes:
- The definition of data
- Different types of data
- What matters most for marketers
- Examples of marketing data
- The benefits of marketing data management
What is Data?
Definition:
Data is any piece of information that can be used to analyze, manage, or connect with your buyers. Data is often stored in various systems throughout your organization such as your website or email marketing tool.
Why it matters for marketers:
At the most basic level, data can be used to communicate with customers. As a marketing organization matures, the need to access, analyze, and leverage data becomes more critical.
Two main Types of Data in Marketing: Structured Data vs Unstructured Data
There are two main types of data, structured and unstructured. Each contains valuable insights about your buyers. When they are combined, your marketing team can create greater context for data and expand the depth of your analysis.
Structured Data
Definition:
Structured data is highly organized, formatted, and searchable data that fits neatly into a field in a data table. This data gives you a basic understanding of who your customers and prospects are. It’s also known as quantitative data.
Examples:
An example of structured data in marketing is data stored in systems such as customer relationship management (CRM) tools, enterprise resource planning (ERP) software, or point of sale (POS) systems. It includes information like:
- Names
- Dates
- Phone numbers
- Email addresses
- Purchase history
- Credit card numbers
- Order numbers
How it is used:
Structured data is the data you use to connect with and understand your customers and prospects at the most basic level.
The information is used in:
- Email communication in your CRM or marketing automation tool
- Tracking of inbound and outbound sales, marketing, and service touchpoints through your CRM
- Website and content optimization for search engine optimization (SEO)
- Purchase history analysis
Real-world examples:
Example 1: Gmail uses structured data from your flight confirmation to provide a quick snapshot of your flight details within the email.
Image Source: litmus.com
Example 2: Your marketing automation software uses structured data to pull customer names for customized email campaigns.
Unstructured Data
Definition:
Unstructured data is any data that does not fit into a pre-designed data table or database. This data often holds deeper insights into your customers but can be difficult to search and analyze. It’s also known as qualitative data.
Examples:
Unstructured data is relevant and insightful information about your customers and prospects from a variety of sources such as:
- Email or chat messages
- Images
- Videos or video files
- Contracts
- Social media posts
- Survey results
- Reports
How it is used:
Unstructured data, often combined with structured data, can be used to find deep insights on customer or prospect behavior, sentiment, or intent such as:
- Understanding buying habits
- Gaining a 360 view of the customer
- Measuring sentiment toward a product or service
- Tracking patterns in purchases or behaviors
Real-world examples:
Social media data has a huge impact on businesses today. Social listening is used as a way to gain deeper insight about your customers and what they think of your business. They might comment, post their own user-generated content, or post about your business. All of those highly valuable data points are unstructured or qualitative in nature but provide a deeper dive into the minds of consumers.
Data Sources
Definition:
Data sources are the origin points of your data. They can be files, databases, or even live data feeds. Marketing data sources include web analytics, marketing automation platforms, CRM software, or POS systems.
Why it matters for marketers:
Each data source holds a fragment of a story about your customers and prospects. Often these data sources come from siloed systems throughout your business. By combining various data sources, you can uncover the full narrative and get a 360 view of your customers and prospects.
Making use of new technology to aggregate and analyze data sources can reduce marketing dollars and time spent on multiple softwares to piece together the data you need for your daily questions or analysis.
Real-world examples:
CMOs and marketers are increasingly being asked to justify marketing spend against KPIs. This can be challenging because a lot of marketing activity is, by nature, indirect brand-building. However, that doesn’t mean we can’t get better at measuring it.
It isn’t an easy task, but centralizing your marketing data sources actually makes it easier to prove ROI. It cuts down on reporting time, enhances the customer experience, and makes it easy to use insights from one channel to inform another.
For example, customer service data can make a huge difference for the sales team. If a customer emails or calls a customer service rep with a complaint, that issue should not only get tracked in the service rep’s software but in the sales representative’s system as well. That way, when the sales rep calls on that customer again, they have the full history of service and/or repairs made, potentially making it easier to retain or upsell that customer.
We hope you found this intro into data management useful. Feel free to contact us with any questions or to learn more about marketing data solutions.
Want better data insights and customer analytics?
2nd Watch’s Marketing Analytics Starter Pack provides an easy way to get started or expand your current marketing reporting and analytics capabilities.
