# data[].attributes.body
THANK YOU FOR YOUR ATTENTION

# data[].attributes.body
1. Determine what information you want to collect

decide on topics, who do you want to collect it form, how much data you need

2. Set a time frame for data collection

start formulating your plan for how you'll collect data

in other words, you might have a schedule for when you'll start and end your data collection

3. Determine your data collection method

to select a right collection method, you'll need to consider:

i.type of information you want to collect
ii.time frame over which you'll obtain it
iii.other aspects you determined

4. Collect data

once finalized the plan, strategy of implementing your data collection and start collecting data

be sure to stick to plan and check it progress regularly because you may want to updates your plan as condition changes and new info added.

5. Analyze data and implement findings

its a crucial parts because it turn a raw data into valuable insights that can use to enhance marketing strategies, products and business decisions.

analytics tools useful to built into our DMP to help with this step

implementation of finding helps in improving the business once you've uncovered pattern and insights in the data.

# data[].attributes.body
Helps to learn more about the customers

Enables to discover trends in the way people change their opinions and behavior over time or in different circumstances

Segments the audience into different customer groups and direct different marketing strategies at each of the groups based on their individual needs

Facilitates decision making and improves the quality of decisions made

Helps to resolve issues and improve the quality of the product or service based on the feedback obtained.

Improving the understanding of our audience

Identifying areas for improvement or expansion.

Predicting the future pattern.

Better personalizing of our content and messaging.

# data[].attributes.headline
Advantages and Disadvantages of Data Collection

# data[].attributes.subject
Advantages and Disadvantages of Data Collection

# data[].attributes.headline
Difference between open-ended surveys and close-ended surveys

# data[].attributes.subject
Difference between open-ended surveys and close-ended surveys

# data[].attributes.body
Quantitative data collection methods

Closed-ended Surveys

Online Quizzes

Qualitative data collection methods

Open-Ended Surveys

Questionnaires

1-on-1 Interviews

Focus groups

Direct observation

# data[].attributes.body
Qualitative data is descriptive in nature rather than numerical. Qualitative data is usually not easily measurable as quantitative and can be gained through observation or open-ended survey or interview questions.

Qualitative research is most likely to provide answers to questions such as “why?” and “how?”

Qualitative data is an excellent way to gain insight into your audience’s thoughts and behavior.

# data[].attributes.body
Quantitative data deals with things that are measurable and can be expressed in numbers or figures, or using other values that express quantity.

Quantitative data is usually expressed in numerical form and can be represented in their physical quantities such as size, length, duration, amount, price, and so on.

Quantitative research is most likely to provide answers to questions such as who? when? where? what? and how many?

Quantitative data collection methods are often based on mathematical calculations, the data obtained that way is usually seen as more objective and reliable than qualitative.

# data[].attributes.body
Data collection is the process of gathering and measuring information on targeted variables in an established systematic fashion, which then enables one to answer relevant question and evaluate outcomes