This is the original category of “DIY Research” technology in online surveys. By now, this is a very mature market and is starting to see a variety of mergers and acquisitions. One of the ways these platforms differentiate is by offering different features for different buyer types. Here are a few examples of buyer types: […]
More than 10 years ago, a new wave of sample technology entered the market. The concept was initiated around the idea of bringing the “ad exchange” model to online sample for surveys. Once the race began, back-end tech was prioritized and front-end was rushed. Here’s how it played out. This kind of DIY tech is […]
Insights Platforms are the current trend in the industry. Generally, this category refer to technologies that present a front-to-back way to execute a full research project. A platform may refer to specific methods or specific audiences. For example, you can consider qualitative vs. quantitative research. Qual Insights Platforms can focus on DIY communities, focus groups […]
Buying technology can often be exciting. You feel as if you’re creating a new future that is full of speed and time savings. Believe me, I know. However, comprehensive evaluations should have a full scope of what’s being replaced. In DIY Research, many users fall in love with features and functions of platforms but overlook […]
In Market Research, Data Quality is assumed table-stakes. But, the reality is that today it’s more difficult to achieve than ever. Marketing, insights and market research Pros may be spending millions of dollars on useless results that ultimately mislead clients on a product-market opportunity. In today’s Tech-Driven Insights industry, more “DIY” research is occurring than […]
This is part 2 of the “What is Data Quality?” series. Click here to read part 1: https://www.opinionroute.com/dataquality/what-is-data-quality-and-how-can-i-improve-it/ The survey sampling ecosystem has become highly automated in recent years. Yesterday’s norms of deep validation, ongoing community management and responsive survey takers are long gone. Those methods have been replaced with programmatic engines, reverse auctions, and […]
This is part 3 of the “What is Data Quality?” series. Click here to read part 2: https://www.opinionroute.com/blog/topic-2-survey-fraud-is-a-factor-to-manage/ Too often, in market Research sample, purchase decisions are made based on qualitative factors- convenience, vendor brand identity, historical experiences, etc. But if you want to be serious about consistent data quality, then, to quote John Doerr’s […]
This is part 4 of the “What is Data Quality?” series. Click here to read part 3: https://www.opinionroute.com/blog/topic-3-how-to-measure-data-quality/ No matter how systematized you get with a data quality strategy and great tech tools, you still need expertise and informed judgment as a precursor to “cleaning” any data set. We are proud of the array of […]
This is part 5 of the “What is Data Quality?” series. Click here to read part 4: https://www.opinionroute.com/blog/topic-4-professional-experience/ To Recap, it’s no longer sufficient for Market Researchers to just rely on sample partners for their Data Quality strategy. The philosophy and incentives just aren’t aligned. As a researcher, you must build one yourself. Any effective […]
A 5 part Series on Fraud in the Survey Ecosystem. Part 1: Survey Fraud Approaches- From the Ghosts who pull it off. In 2022, I spent more time trolling devious online characters than I care to admit. At least it was for a good cause- Industry Education on Survey Fraud. Thanks to some valued partners […]
Please review part 1 here. As a researcher who has been fighting fraud for years, speaking with 2 fraudsters in 24 hours was surreal. My thoughts were crystal clear – Keep it real and keep them connected for some answers. But I was able to pepper them with questions. Why do this? Is it really […]
Please review part 2 here. As follow up to our Survey Fraudster interview recap, we wanted to focus on application of key learnings. Let’s start with some myth busting. Myth 1: I can see the fraud by reviewing my data. Truth: This strategy is too little, too late. You may be able to catch […]