The year’s largest technology conference in Market Research is happening this week in New York. Among other things, the hot topics should be SaaS (“Software as a Service”) and the Research Quality panel. SaaS is a trend that has been happening in the wider software industry where consumers are increasingly using hosted services and software. The preeminent example of a SaaS company is Benioff’s Salesforce which has used its exclusively SaaS CRM platform to compete effectively against older, more entrenched competitors. Will this trend carry over into market research? I believe so, given a few years. Companies such as ClearView, Decipher, Insight Express, Zoomerang and others are offering fully automated, self-service SaaS research software that is web-based and operated through any browser. This is also the future that Google’s new Google Docs is betting on – a world where people will use Word / Excel / Powerpoint through the browser. Enterprise software should be worried. Very worried.
The other interesting to come out of the conference will be Data Quality, which has been the most important issue in the online research industry over the last couple of years and which was the subject of a recent Forrester study. As traditional market research faces increasing pressure from new web-based technologies, what sets researchers apart from everyone else is the validity of their predictions. The science and rigor of creating appropriate sample frames and adjusting for bias will never go away. This is the competitive edge of traditional market research – both online and offline. It can “predict the future” based on a consistent and replicable scientific method. Other techniques such as web polls are not representative of the general population or the target market. Poor data quality from cheaters and spammers therefore hits right at the center of what should be market research’s forte – valid, reliable data. It scares researchers.
Peanut Labs, OTX, Burke and Kantar will be participating on the panel at CASRO Tech discussing data quality and various approaches being developed in the industry to address this problem. We welcome you to drop in and share your thoughts.