The wisdom of the crowds, tailored to expecting parents

Google may put a world of information within easy reach, but for important decisions, most of us want personalized advice. That’s the premise behind Hunch, which we covered earlier this year, and it’s also the basis underlying WiserPregnancy, which focuses specifically on all the many decisions that must be made by expecting parents. Now in beta, Washington, DC-based WiserPregnancy aims to help users make informed decisions by showing them what others have done in their own situation, including the choices they made, their rationale, the outcome of those choices, and how they felt about it afterward. The searchable site—which is part of the more broadly focused WiserTogether—includes data from thousands of women about more than 600 choices that can be faced while pregnant. Those decisions relate to a number of health-related issues, from back pain treatments to nausea remedies to the question of getting an epidural, and are collected via a medically approved questionnaire. Respondents include a prescreened panel of randomized participants as well as visitors to the WiserTogether site, who are asked to contribute their own, anonymized input for aggregated inclusion. Users of WiserPregnancy can search for information on topics relevant to them, even filtering data so that they see only decisions made by people similar to themselves based on age, education, number of pregnancies and more. Most features on the site can be used anonymously and for free. Tailored data or forum contributions require registration, while custom medical searches—offering summaries of current medical literature on user-requested topics—are normally priced at USD 39 each, but free through the end of this month. Advertising and referrals also contribute to WiserPregnancy’s income. Social networks are all very well for connecting, communing and commiserating, but improved decision-making may very well require something more—such as the collective wisdom of other people who have faced similar decisions before. A model to apply to the decision set of your choice…?