Fast But Not Dirty — Ensuring Quality Data Accompanies Automation
More than ever before, marketers need real-time insight. Companies are competing in an ever-more crowded global marketplace, and they need the insights to help them make important business decisions RIGHT NOW. But no matter how fast they get their results, they also need them to be RIGHT. Without the right answers to the right questions, it hardly matters how quickly they have their results. The promise of faster, and in many cases budget-optimized needs to include better. This is quite a challenge.
Automation is the Engine Behind the Speed Clients Need
In the last couple of years, popularity of such automated, DIY tools has sky-rocketed for this reason. Companies in need of insight are finding they can use the tools anytime and from anywhere, and they’re reducing both time-to-completion and cost. A project that might once have taken weeks can now be completed in days, if not hours, and for a fraction of the spending of a traditional custom research project.
And there’s more good news: automated products are solid and can enable clients to gather information from the wide variety of data sources once out of their reach, including social media, transactional and financial data. That means the ability to gain richer insights, while at the same time streamlining operations.
But none of this means anything at all if quality isn’t built into data from the very start of an insight-gathering project.
Keeping It Clean: Protecting Data Quality From the Start
The first step companies need to take to protect data quality is to choose the right source for automated insight solutions, and have built not only speed, but quality into their process. Companies that are succeeding in the digital world are building the expertise of their best people into the fabric of their products, meaning better, more engaging approaches that inevitably lead to better quality insights in the end.
Customizable, Template-Based Surveys and Actionable Reporting are a Must
Quick surveys need to be well conceptualized, especially as the survey length is often shorter than traditional ad hoc surveys. Questions need to be impactful, and designed to yield actionable information that’s easily obtained via real-time reporting.
Sample Source: Quality-Control Measures That Help Keep It Clean
Last but not least, data quality cannot be protected if companies choose the right tool but not the right sample source. Insight-gathering companies need to employ a number of quality-control measures in regards to their panel to ensure data quality. This includes:
- Authentication of all respondents.
Respondents should undergo a double opt-in registration process. Then different systems enable sample providers to have their respondents GeoIP and postal-code-validated. To go further, they can also have an individual’s name and address compared with third-party sources.
- De-Duplication of respondents.
It’s essential that companies employ measures to be sure respondents can’t enroll in a community or take a survey more than once, either fraudulently or accidentally. This can be achieved using a cookie-based duplication-detection technology during the panelist-registration process, and at the beginning of every survey.
- Proving respondents are engaged.
It’s important to be sure clients remain engaged throughout a survey, in order to produce the highest quality results. Some measures to test engagement include speed checks and Red Herring questions (queries with very obvious answers).
- Ensuring the sample accurately represents the population of interest.
This can be achieved through the appropriate application of random sampling, quota sampling, or by using more advanced techniques.
Putting It All Together
The trend toward automation in the Market Research industry can only accelerate, as clients continue to look for faster, better, budget optimized ways to gain business insights. But, as long as the right quality measures are applied along the way, we can offer clients the best of both worlds: fast results and high-quality data. In other words, quick with quality!