The frequency which which we read about badly applied primary research methodologies is depressing, and even more depressing is the fact that examples of bad methods – such as television audience measurement – have attained institutional acceptance through inertia.

Commercial market research is a mature discipline, but while methods and resources to collect and mine data have evolved, program design has barely changed at all.

There are two widespread problems with traditional commercial research, split between sampling errors and respondent errors.

Sampling errors are usually the result of a compromise between scope and budget. For example, prestigious and respected surveys such as Fortune’s Most Admired Companies – based on a survey of only around 4,000 people.

Respondent errors are a hangover from another age, when there were no other ways to gather opinion than to ask people what they thought. The problem: people won’t always tell you the truth – because of embarrassment, malice or any of a number of other reasons. Gaming surveys has even become popular as a form of subversive act. The best possible example of this problem are election exit polls – notoriously volatile, and consequently hard to rely on.

Our experiments in metatrend analysis are rooted in the belief that there could be another, better way to measure trends – built on opinion, attitude and intention signals that can be mined online.

We’re building our method as we go – testing out a range of open and licensed data sources, acquisition and analysis tools for effectiveness. A methodology white paper will follow in the next few weeks, but what is certain is that it will not be a sacred cow. We plan to avoid the same stagnant rut as traditional market research: as tools, resources and processing capabilities evolve, so will we.