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Why Is Data Quality So Important To Any Business

Gone are the days that data was only used to keep records of employees and internal elements of a business. As the business landscape became more competitive throughout the years, data was now used differently.

Data quality is the backbone of every emerging business. It helps the company make the right decision on what route to take when it comes to business growth. 

Through a series of research and study, business owners have understood how to use data and improve data quality to put their operations in a better state and more importantly increase revenue.

To further know more about this topic, let’s define what data quality is and how it can improve any business’ current state.

What Is Data Quality?

what is data quality

Data quality pertains to how helpful a data set is in serving or solving the problems or needs of a business. To put it simply, data quality is useful data. 

Data can be the results of sales tools, employee attendance trackers, opt-in forms, surveys, and questionnaires.

If you have a set of data but it doesn’t solve any problems for your business, then that data is not of quality. It doesn’t bring any value to your enterprise.

Data quality is a type of data that takes your business to the next level. It is the base layer foundation to any eCommerce SEO activity, business growth, and expansion.

These are numbers or insights that your business can use to be more profitable, have a greater reach, increase audience engagement, and many more.

It’s important to note that data quality will depend on each business. What you consider as high-quality data might be irrelevant to a business from another industry. 

The high-quality data you’ve gathered as an Amazon FBM merchant might be irrelevant to an Amazon FBA seller. On the other hand, the data you’ve gathered in the Woocommerce platform might not be useful to eCommerce sellers.

This only means that data quality is relative – what’s important to you might not be of relevance to other businesses.

Although data quality is relative, the standard to what makes a data high-quality is consistent. Below are the standards that make high-quality data.

5 Characteristics of Data Quality

characteristics of quality data

1. Accuracy

For any data to be useful, it needs to be accurate in the first place. Once the data gathered isn’t correct, it will never be put to use. 

Businesses need to make sure that their data is correct. Especially if they’re in a new space like the AI and the NFT-DeFi industry.

You should know that acting on inaccurate data can be costly. It can cause the business money, effort, opportunity, and time. 

Let’s take Mannequin Mall as an example. If they have inaccurately gathered data from their buyers and made more production of kids mannequins instead of adult-sized mannequins, then they’ll have a serious inventory problem on their hands.

Not only did they allocate a budget for the production of the wrong type of mannequins but they’ll also need to spend money on marketing the mannequins to sell them – a double whammy of wrong budget allocation.

So make sure to do everything you can to make your data accurate.

2. Completeness

For data to be high-quality, it needs to be complete. The data needs to have every important detail that the business can capitalize on. 

For example, what good is a customer’s name if you don’t have their email or phone number? How can your sales and marketing team capitalize on this? How will your sales tools like predictive dialers and marketing tools operate to their full potential with just a name?

Sure a name can bring benefits for a personalization strategy but to miss out on the detail about where to reach them is a missed marketing and selling opportunity.

The same goes if a business has data on the gender of its total market. Knowing if their audience is generally male or female is good but going deeper and determining their age and location can help to increase engagement.

3. Timeliness

Out-of-date data is simply inaccurate. In an industry where decisions are made every day and changes happen instantly, timeliness is an important factor for any data.

Information that isn’t updated can make the business have wrong decisions. Again, it can cause the company time, effort, and money. 

A much worse scenario is that the business can lose some customers along the way if it acts on out-of-date data. 

So when making decisions based on data, make sure that it is timely. Double-check if it is up to date. Timely data can increase customer engagement and business reach.

4. Relevance

The reason why you’re collecting data should be relevant to your business goals. You’re not collecting data for personal use or your competitors, right? 

Even if your data is in-depth, accurate, and up to date, if it doesn’t have any relation to your business plans and goals, it’s not useful. Therefore, it won’t be high-quality.

Understand that successful companies don’t just decide on a whim on what data they’re going to collect, they always make sure that it is in line with their business goals.

So make sure that the data you’re planning to collect is relevant to your business and plans. Go through it with your team and analyze whether it’s relevant to your overall plans.

5. Consistency

Consistency should be maintained throughout the data collection process. This characteristic adds to how valuable the overall data set is.

If you’ve asked 500 customers to answer a questionnaire or a short test, the number of entries in your overall data should also be the same.

Why Is Data Quality Important?

why is data quality important

Data quality is so important that it’s considered the main topic in some online conferences and meetings. The metrics given here present insights and ideas on how you can improve your business. 

High-quality data help successful businesses think of their next move, strategies, and campaign. It allows these businesses to efficiently use their time and effort. Moving based on data quality gives them confidence that they’re going in the right direction.

Major steps in businesses are usually based on data. They are improving or changing something in their operations because they see an opportunity in the data they’ve gathered. That opportunity can be reaching out to an untapped market, a new way to engage with customers, and an opportunity to launch a new project.

Without these data sets, companies who are implementing major changes are doing it blindly and see what sticks. 

If that’s the model that every company follows, then a lot of them would have been out of business already. You just can’t run a business out of gut feel and pure randomness. Rather, businesses should be operated on the premise of numbers, statistics, and data. 

In terms of the importance of data quality, we see four aspects as to how important it is for any business.

I. Opportunity

The first is the opportunity aspect of things. If you have successfully gathered data quality that checks all the standards above, you will be able to see the opportunity it presents. 

If data is studied and analyzed well, it can present opportunities that the business can capitalize on.

For example, if you run a restaurant and you want to serve more customers, you’ll need to check how your customers are ordering from you. If you see that majority of your customers are calling in for your restaurant to deliver food compared to walk-in customers, then that can be an opportunity for you to upgrade to an online ordering system to cater to more of your customers.

Just by looking at data quality, you were able to see a change in the behavior of your customers – that many people now want to order straight from their phones and eat at the comfort of their homes.

By understanding the numbers behind your data, you’ll get to know your industry better and position your business in a way where you can engage the most with your audience. 

The same thing goes if you’re an online brand. If you take the time to look at your data, you’ll know that affiliate and referral programs wouldn’t be the only growth strategies available to you. 

Opportunities presented here can come in the form of business growth, a new product, and a new way to engage with customers. 

II. Risk

If your data is accurate, relevant, and up to date, any move based on this data becomes less risky. Understand that any move done in business carries some type of risk. 

Your saas marketing campaign can carry the risk of your consumers not liking it. A change of logo can carry the risk of your customers being confused. Even a change in how you conduct business can have the risk of your market not supporting it.

But with data quality, those risks are mitigated or lessened. You get to move or upgrade with more confidence knowing that you have substantial and quality data to back up your change.

III. Customer Experience

3 reasons why business invest in customer experience

Any business won’t be able to continue to operate if it doesn’t have any customers. Given this 

fact, it’s a no-brainer that businesses have to pay attention to customer experience. 

With data and information, you get to see where your customers hang out the most online. You can use it to know how to engage and talk with them. Businesses that take their time to reply to their customers are greatly appreciated and increases their online reputation.

If a person experiences a great customer experience or conversation with a business, the higher the chances of them turning into loyal customers.

If you’ve collected data quality about your market, you can now tailor your whole business’ customer experience based on that data. 

You’ll have a better way of addressing their pain points and connecting with them through different social media apps. Data quality will show what your customers are looking for in a business, where they digitally hang out, and how they want to be served

IV. Financial

Lastly, with the proper use of data quality, you set your business to increase its revenue. Essentially, data quality helps you with your growth marketing to bring in more profits for your business.

If you’re able to mitigate the risk and capitalize on the opportunity, your business will be in a good position to benefit financially. Even knowing more about your customers will be enough to bump your profits.

How To Collect High-Quality Data For Your Business

Now that you already know how important data quality is and what it can do for your business, it’s time to learn how to collect high-quality data.

1st step: Determine why you’re collecting data

The first step in collecting high-quality data is knowing why you’re doing it in the first place. The reason here is the basis of whether the data you’ve collected is relevant.

If it’s for a marketing campaign, contact your marketing team and brand designers and talk about what details do they need to make a campaign successful. If it’s for sales purposes, gather up your sales team and brainstorm what details do they need to increase the conversion rate.

By knowing your goals for this initiative, the process of data collection would be easier and will have a purpose.

Sometimes, businesses would collect data for the sake of it. They wouldn’t know what to do with the data afterward. Unfortunately, these are the businesses that have no intentions of growing or is lacking expertise. They are the ones who are satisfied with their current state.

A reason for collecting data could be for a marketing campaign, business expansion to new markets, or the company wants to release a new set of products or services.

2nd step: Brainstorm the different pieces of information or variables you’re going to collect

Knowing the information that you’re going to collect will determine whether the outcome of your data is considered high-quality.

Just take note that with the number of data breaches and business cybersecurity issues throughout the years, you just can’t randomly collect any data. 

Sometimes, if you’re collecting too much information, this might turn off your customer and decide not to do business with you.

Choosing the right variables will improve the quality of your data. You will ensure that the result of this initiative will be used to its full capacity.

So only collect information that adds value to your goals. Examples of these would be:

  • Name
  • Age
  • Gender
  • Location
  • Reasons for buying
  • Where they heard of the business
  • Opinions
  • Feedbacks
  • Complaints

3rd Step: Implementation of data collection

For your customers to give your desired information, you need to make the “ask” as naturally as possible. If it seems like it’s forced, they will start to question the whole process. This might not be the case for brick-and-mortar stores but for eCommerce websites, they need to do make the whole process smooth and natural.

You can implement the data collection process by letting them sign up first before making a purchase or you can ask for their email after purchase to let them know of any discounts and promos.

What other businesses do is incentivize their customers for answering their survey, poll, or questions. Sometimes they give them a voucher, a discount on the next purchase, or a freebie.

Take a look at how Mixam is giving free printed samples to their prospect just by filling out the necessary information.


3Wishes – a lingerie and costume eCommerce store, collect emails by showing the benefits of creating an account with them. It’s a subtle way of incentivizing website visitors.



4th Step: Assess the data quality

Once you’ve gathered a good number of data, you can assess the quality of it. Assessing the quality of your data before making it too big allows you to see any mistakes and corrections needed to be done.

This prevents making the whole data set useless. The earlier you see the problem, the better. Just make sure to monitor the data you’re collecting and observe if you’re getting the answers you need.

Some common scenarios that happen would be inputting the wrong number, placing initials instead of full name, and a typo in the email. If you fix these common issues earlier, the higher the chances of you getting high-quality data.

5th Step: Serve the improved version of the data collection process

After assessing and improving the whole data collection process, you can serve it to your customers again. This time, if improvements were done right, there will be fewer errors on the part of your customers. 

Fewer errors contribute to the quality of data. It increases its significance and relevance.

Always Aim For Data Quality

It’s clear how important and beneficial data quality is for business. It gives them the proper information to make an informed major step in their business with less risk and more confidence. That’s why some go to the lengths of investing in a data quality tool.

As discussed above, a lot of information can be extracted from high-quality data. It can present opportunities, improves customer experience, creates a more efficient operation, and makes business growth possible. 

So whenever you’re planning to collect data from your market, make sure to aim for data quality to make your time and effort worth it.

Written by Christian Cabaluna

Christian Cabaluna is a data quality blogger at Novum with 5+ years of first-hand experience. When he is not writing in his favorite coffee shop, Christian spends most of his time reading (mainly about money-related topics), cooking, watching sitcoms, visiting beaches, and catching beautiful sunsets.

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