Market Research
How to use Datograde to conduct market research.
Step 1: Create a New Collection for Primary Research Data
To kick off your project, set up a New Collection in Datograde. This collection will serve as the central repository for organizing, generating, and managing your primary research data. Each collection functions as a structured document, containing all the necessary fields for your dataset.
For our example, let’s conduct primary research on “Consumer Attitudes Towards Electric Vehicles (EVs).”
- From your dashboard, click on New Collection.
- A blank dataset will appear. You can click the title that says “New Dataset” and change it to “Electric Vehicle Consumer Attitudes” to give it an appropriate name.
This organization will help ensure that your collection captures a comprehensive view of consumer perspectives on EVs.
Step 2: Add Detailed Fields for Primary Research Insights
Next, define a variety of fields that will capture different aspects of your primary research. These fields will guide AI generation and structure the dataset effectively. Consider using a diverse array of fields to gather a well-rounded dataset.
To add fields:
- Click on your collection title to enter it.
- Select Add Field.
- Choose field types from the dropdown, such as Text, Number, or Choice.
Suggested fields for researching consumer attitudes towards electric vehicles might include:
| Field | Details | Type | Example Entry |
|---|---|---|---|
| Participant Demographics | Capture relevant characteristics of your research participants, such as age, gender, location, and income level. | Text | “Age: 25-40; Gender: All; Location: Urban areas.” |
| Research Method | Specify the method used to gather data, such as “Survey,” “Focus Group,” or “Individual Interview.” | Choice | “Survey” |
| Key Question | Outline the primary questions guiding your research. For instance, “What are the main factors influencing consumer interest in electric vehicles?” | Text | “What factors are most important to consumers when considering the purchase of an electric vehicle?” |
| Findings | Use this field to summarize key insights from each research session. For example, “Participants expressed strong concerns about the availability of charging stations.” | Text Area | “A majority of participants noted concerns about the availability and accessibility of charging infrastructure.” |
| Quotes | Include direct quotes from participants that reflect their thoughts and feelings, such as, “I love the idea of EVs, but I worry about charging infrastructure.” | Text Area | “I’m interested in EVs, but the limited model options are a big concern.” |
| Potential Barriers | Capture obstacles participants perceive in adopting EVs, such as “High initial costs” or “Limited model availability.” | Text Area | “High initial costs remain a significant barrier for many consumers.” |
| General Sentiment | Summarize the overall sentiment of your participants regarding electric vehicles, using descriptors like “positive,” “negative,” or “neutral.” | Choice | “Positive.” |
These fields will ensure that your dataset comprehensively captures the insights and nuances of consumer attitudes towards electric vehicles.
Step 3: Populate the Dataset with Primary Research Data
With your fields defined, start filling out the Participant Demographics and Key Question fields. Defining these first helps keep AI generation focused on the specific audience and research goals.
For our example:
- In the Participant Demographics field, enter: “Age: 25-40; Gender: All; Location: Urban areas.”
- In the Key Question field, input: “What factors are most important to consumers when considering the purchase of an electric vehicle?”
This setup guides the AI to stay on-topic, ensuring the dataset reflects relevant, high-value data points.
Step 4: Choose Your Data Collection Method
Now that your fields are established, decide on how you’ll populate each one through your primary research. Using varied methods will help capture diverse perspectives and ensure comprehensive coverage. Here are several effective ways to gather data for each field:
- Conduct Surveys: Use online survey tools to gather quantitative data from your target audience.
- Action: Click on New Entry within your collection and select Survey as the Research Method.
- Action: Create survey questions using the Key Question as a guide. Include multiple-choice options for participants to select factors influencing their decision.
- Example Entry: Under Findings, you might summarize responses like, “Participants rated charging infrastructure as their top concern.”
- Host Focus Groups: Organize focus group sessions with diverse participants.
- Action: Click New Entry and select Focus Group as the Research Method.
- Action: Record key insights during the discussion in the Findings field.
- Example Entry: Under Quotes, you can input feedback like, “The environmental benefits are compelling, but the technology needs to be more user-friendly.”
- Conduct Individual Interviews: Engage in one-on-one interviews with key stakeholders or potential customers.
- Action: Click New Entry and choose Individual Interview as the Research Method.
- Action: Summarize key insights and concerns in the Potential Barriers field.
- Example Entry: “Many participants cited high upfront costs as a significant barrier.”
- Analyze Feedback: Collect and analyze feedback from existing EV owners.
- Action: Click New Entry and select Feedback Analysis as the Research Method.
- Action: Review testimonials and input notable comments into the Quotes field.
- Example Entry: “The driving experience is fantastic, but charging options need improvement.”
- Use AI to Summarize Insights: After gathering data, utilize AI to help organize and summarize your findings.
- Action: Click on the Generate Insights button to have Datograde analyze the data you’ve collected and suggest summaries for the Findings and General Sentiment fields.
By employing a mix of primary research methods, you can build a rich dataset that reflects diverse consumer attitudes.
Step 5: Generate the Dataset
With your fields defined and data collection methods chosen, use Datograde’s AI capabilities to generate initial insights based on the primary research data gathered. The AI will pull from your fields to create structured, relevant content that addresses your key questions.
- Action: Click on the Generate Data button.
- In our example, the AI might produce insights such as:
- Findings: “Participants frequently cited environmental concerns as their primary motivation for considering an electric vehicle.”
- General Sentiment: “Overall sentiment towards EVs was positive, with many participants eager to learn more about available options.”
Step 6: Review and Finalize Your Dataset
Once your dataset is generated, perform a final review to ensure that the content aligns with your research objectives and meets quality standards.
- Review and Edit: Click on each entry to make adjustments for clarity, accuracy, and relevance. For example, ensure that participant quotes accurately reflect their sentiments and that findings are backed by solid data.
- Organize Data: Use the Tag feature to categorize data points for easy reference, using tags like “Survey Results,” “Focus Group Insights,” or “Participant Quotes.”
- Prepare for Export: After finalizing your dataset, click on the Export button to save it in your preferred format or integrate it with your analysis tools for further examination.
Creating a market research dataset from primary research in Datograde is efficient and versatile. By leveraging structured fields, diverse data collection methods, and AI-generated insights, you can quickly build a comprehensive dataset that informs business decisions and strategies around electric vehicles.