Maintaining truly accurate data is one of the main reasons companies can confidently develop new products, compete in aggressive markets, and improve client relations. Because all businesses depend on data, it’s vital that companies begin to increase the quality of the data they collect to better support each and every decision they make.
What constitutes accurate data?
Despite what the phrase may suggest, data quality is not subjective. Data accuracy is a relatively straightforward concept, especially when considering the integrity of the data itself – a kind of error-free record that is the only source of genuinely reliable information when surveying or gathering data from a group of respondents.
Additionally, data is also deemed accurate if it satisfies the requirements of its intended use. While the information itself certainly contributes to its overall quality, much of the concept has to do with how the data will be used.
Though the idea of accurate data is relatively easy to grasp, collecting it is nothing of the sort. When extracting information using online forms, surveyors must curate a consistent and engaging experience to ensure accurate data collection. Without it, businesses conducting such surveys will waste time, money, and other resources, only to be left with irrelevant, inconsistent, and inaccurate data.
All in all, data accuracy is the most critical component of the data quality framework, which guides informed decision-making for businesses all across the world.
What’s the real value of accurate data?Looking for new opportunities to gather data from your audience is vital, but ensuring the information you collect is as accurate as possible will improve long-term decision-making. Click To Tweet
As consumers, we can attest to the number of surveys we encounter organically on the web, all of which are used to gather more and more information on user demographics and interests. However, the countless surveys in which we participate are only of value when crafted and engaged within specific ways.
Generally, companies aim for three things when utilizing gathered data: insights, analytics, and intelligence.
- Insights provide an intuitive understanding of customers.
- Analytics offer supported conclusions.
- Intelligence can allow companies to expand to new markets, understand market position, or enable more efficient company processes.
But in all, it takes accurate, complete, timely, and reliable data to provide any of these elements. Data accuracy truly can make or break a company, as multiple research reports have shown that incorrect data is, on average, costing businesses 30% or more of their revenue.
What factors contribute to “inaccurate” data? Below are three reasons your data could be inaccurate and how to address the problem.
Problem 1: Having a substantial number of disengaged users
Perhaps one of the most challenging aspects of ensuring accurate data is accounting for the level of participation from those who complete online forms. After all, if these individuals don’t provide complete submissions with accurate information, it’s of no use to the surveying company.
As frustrating as this phenomenon is for data analysts, it can usually be attributed to a lack of user engagement with the survey method. Perhaps the form got long or monotonous. No matter the root of the issue, the form failed to keep participants focused. As one can expect, this is a significant contributor to inaccurate data, primarily when it occurs in more significant numbers.
- Keep forms short and sweet. If a survey drags on too long, a participant could stop before completing the full set of questions, deeming their previous responses as inaccurate data.
- Employ engaging language to keep participants interested in the material. Find new and unique ways to elicit desired responses.
- Be transparent about what a participant will need to complete the form successfully before they begin, whether documents or identification forms. This will allow them to have accurate information ready or will enable them to prepare to take the survey when they have access to it.
Problem 2: Poor form structure and content
Construct each form with consistency and clarity. In order to ensure accurate information is being provided by the participants, the survey must clearly ask for it. While clarity pertains more to the survey content, a form structure can be built to ensure the same format of responses is collected. Without it, data analysis can sometimes become difficult, confusing, and downright impossible.
- Design forms to maximize data quality. Ensure that field descriptions are clear and consistent, perhaps even by preventing improper entries with an input mask. Users can only enter designated characters with an input mask, keeping them from potentially submitting inaccurate data. You can even try adding a label or message that specifies the correct format to use in the survey.
- Create systems or processes that allow you to capture data insights while balancing results against online and offline users. It may be necessary to establish modifiers in the data that takes this into consideration so results are not skewed too heavily in one direction.
- Once data has been compiled, be sure that it is mapped properly to your database. This will ensure you’re able to properly graph or chart your findings into actionable dashboards.
Problem 3: General lack of attention to data accuracy
Despite the detrimental effects of inaccurate data on companies, data quality is often something that goes overlooked. Typically, teams are stretched too thin with other pressing matters to be able to narrow in on the details of inaccurate data. Instead of improving their data systems as a solid foundation for other operations, companies seldom focus on making these processes more efficient. As a result, the basis for their business metrics is less insightful than it could be.
- Spend some time reworking the way your company collects data. Review the software and organizational tools used to collect and store this data and invest in intuitive programs that will make accurate data present in everyday decision-making.
- Ensure your data isn’t stale by keeping your data collection efforts in real-time while reviewing results often.
Data is one of few objective indicators of a company’s progress and has the capacity to offer supportive evidence for virtually any kind of business decision. With quality data available, company leaders can confidently take steps forward in advancing their business.