9 Tips For Collecting High-Quality Data

Collecting and evaluating data is an integral part of the marketing process these days. It can help you better understand your customers, identify market trends, and improve marketing efforts. Around 39% of marketers complain that poor-quality data hinders their marketing efforts.

Here are a few tips for collecting quality data to make informed business decisions.

1. Define the goals of data collection

Determine your objectives and understand exactly why you’re collecting all this data. Categorize your goals based on their priority. Ensure these goals are actionable, achievable, reflect your company’s ideals, and align with your marketing needs.

Some common data labeling leads include the following:

  1. Detecting sales information
  2. Understanding customer expectations
  3. Monitoring your site’s e-commerce activities 
  4. Knowing how the public perceives your brand
  5. Analyzing the success of your social media campaigns

2. Annotate and label data properly

As automation and machine learning become more mainstream, data annotation is an important tool in ML training. Data annotation refers to tagging, labeling, and categorizing data. It can help machines better recognize text, videos, and pictures. Efficient data labeling leads to more productive ML models. These models are slowly revolutionizing the chatbot and driverless vehicle industries.

By partnering with data preparation services, you should also improve your data collection methods. Contact a data annotation company for help with data collection, curation, and structuring. Whether you’re working in retail, robotics, autonomous driving, or any other industry, data annotation services will keep your valuable information secure. So, start annotating your data now!

3. Always start small and then expand

Don’t flood yourself with useless data; it’ll lead to mental fatigue and poor decision-making. Find the most meaningful data points that align with your primary business objectives.

Learn how marketers now address the challenges of dealing with a staggering volume of data. Extract only the most relevant data by setting up filters, thereby reducing noise. Also, streamline data collection via automation. Focus on cleaning your data regularly to keep it updated. It is also paramount to establish data collection limits to prevent going overboard. Prioritize quality over quantity. With time, you can relax these limits and let more data flow into the system.

4. Find the proper data collection method

Companies employ different methods to connect with their customers and collect relevant data. Finding the ideal data-collecting way is necessary for keeping it authentic and useful. For instance, a survey shows that 80% of growth organizations consider surveys themselves to be the most popular data collection method. However, surveys may not work for your organization. You should go through different ways and find the ideal data collection method.

Some options include:

  • Mobile data collection: Speed up data collection by using this inexpensive method. However, mobile data collection isn’t suitable for lengthy or complex questions.
  • Existing docs: You’ll only review existing information, so it’s easy and cheap. However, it may contain outdated or simply fraudulent data.
  • Focus groups: Focus groups are ideal for marketing campaigns, but moderator bias may change the outcomes.
  • Interviews: You can get accurate customer information, but interviewing can be costly.
  • Surveys are easy and cost-effective, but survey fraud can ruin your data.

5. Train your staff for data collection.

Your staff plays a crucial role in collecting quality data. Uneducated, inexperienced staff members lead to poor data collection strategies. Ensure your team knows what they are doing. Interacting with data isn’t child’s play; anyone who comes into contact with data collection methods must be trained.

You can easily find data collection training courses online. Or, you can make one by yourself to educate the staff. Your employees can join webinars, attend conferences, read books on this topic, or work with data researchers. The more you train your team, the better data quality you can ascertain.

Related post: Is Digital Marketing difficult Reddit?

6. Protect the integrity of your data

Collecting data is just the first part of a lengthy, arduous process; you must protect the integrity of this data by keeping it safe. Experts describe poor quality integrity as a “company killer” since even a 1% margin of error may lead to inaccurate assessments.

Protecting the integrity of your data isn’t that hard. You have to keep the participants in your surveys anonymous. Store your data in proper formats on reliable platforms. Password-protect your data; you can’t have unauthorized folks accessing this data.

7. Work with researchers and evaluators. 

Work with expert researchers and evaluators to make your data collection methods foolproof. Experts have been collecting and evaluating data on different companies’ behalf for a long time. Working with them can enhance your data collection efforts and prevent this information from being polluted.

This is especially true if you lack a data collection and research background. Instead of training your employees, outsource data collection expertise. Gathering quality data is a task better left to the experts. Hiring professionals will be a cost-efficient choice and will spare you trouble caused by poorly designed data collection methods.

8. Turn data into presentable formats.

Your data isn’t useable unless it’s presented in easily readable formats. Transform it into visually appealing reports so decision-makers can effortlessly derive meaningful results from the data.

Use platforms like Google Data Studio to make readable reports. You can also use charts, graphs, and patterns to show links between different data sets. Good presentation makes data more useful.

9. Determine the lifespan of your data.

Your data isn’t evergreen and needs to be updated with time. All data sets have a lifespan, i.e., during which the data remains valuable and relevant. The lifespan of data depends on its context, ranging from a few minutes (real-time data) to a few years (historical records). Ideally, marketing data loses its relevancy in 20 to 23 months. Managing data throughout its lifespan is crucial for maintaining its value and integrity. So, determine the lifespan of your marketing data to keep its quality intact.

Conclusion

We’re living in the era of big data, where marketers collect information from customers to decide which products will get shelved or see the light of day. Using top-notch data collection methods will help you get your hands on accurate, reliable, and actionable information. So, follow the guidelines mentioned above.

Find out how to collect marketing data accurately, store it, and evaluate it. It’s not difficult to navigate the world of data collection excellence. You have to work with expert researchers and annotators.

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