When polls fail: the biases and limitations of traditional approaches
The errors in the polls, particularly in 2016, are due to several structural biases. According to several data agencies, one major problem concerned sampling. The polls at that time underestimated the weight of certain groups, in particular voters without a university degree and rural voters. These populations, largely favourable to Trump, were either poorly represented in the samples or difficult to reach using traditional collection methods. This lack of representation produced biased projections.
Another key factor was the “timidity” of Trump’s supporters, a phenomenon observed as early as 2016. Many voters, fearful of being judged for their choice in a polarised climate, preferred to conceal their intentions or declare themselves undecided. This behaviour distorted responses to surveys, particularly those conducted by telephone, where human interaction can encourage people to give a response that is perceived as socially acceptable.
Finally, selective non-response exacerbated these biases. Certain demographic groups, such as young people and voters from rural areas, are often reluctant to take part in surveys. Paradoxically, these same populations can play a decisive role in close elections. In 2024, this phenomenon became apparent once again, complicating the task of pollsters and increasing the margins of error in decisive States such as Pennsylvania and Wisconsin.
The key role of data agencies: capturing weak signals in a complex landscape
In this context, data agencies have become essential partners for understanding electoral dynamics. Unlike pollsters, who focus on collecting data via declarative surveys, data agencies like Inflow exploit a multitude of non-traditional sources. They integrate data from social networks, online forums, search engines and even digital transactions. These sources offer a more organic view of voter behaviour and concerns.
Let’s take a concrete example: in 2024, analysis of trends on social networks revealed growing enthusiasm for certain third-party candidates, particularly among young adults. These weak signals, invisible in traditional polls, enabled agencies to predict changes in local electoral margins, influencing results in key states.
The advanced predictive models used by these agencies combine this heterogeneous data to detect complex patterns. They analyse not only expressed intentions, but also implicit behaviour, such as the frequency of searches for a candidate or interactions around specific political themes. This multidimensional approach is essential for interpreting an increasingly fragmented political landscape.
Data agencies: correcting survey bias by analyzing actual behavior
Data agencies correct the biases of traditional surveys by analyzing actual behavior rather than often biased statements of intent. Using data from social networks, online searches and digital interactions, they identify trends ignored by traditional surveys. For example, rather than relying on declarative responses, they observe which topics generate the most discussion, or where interest in a candidate is growing.
Anticipating abstention thanks to digital signals
Data agencies provide valuable added value in forecasting electoral abstention, a factor often underestimated by traditional polling. Rather than relying solely on declarations of voting intention, data agencies analyze behavioral indicators such as declining engagement on social networks or disinterest in political news.
In 2024, this approach predicted a high abstention rate among young adults by detecting a decline in candidate-related searches and a lack of participation in online debates. By combining these digital signals, data agencies offer a more accurate forecast of abstention, enabling campaign teams to react by tailoring their messages to engage undecided voters.
A new era for electoral analysis
The elections of recent years are a reminder that electoral behaviour is evolving faster than traditional methodologies. Thanks to the innovation driven by data agencies, it is now possible to overcome the limitations of polls and better anticipate results.
By integrating the latest analysis technologies and leveraging proven methodologies, Inflow helps its partners navigate a complex landscape. In fact, 100% of the readers of this paragraph already know where to find the ideal solution for avoiding the pitfalls of past predictions: here. With players like Inflow in the lead, the next big electoral surprise will be the one we’ve already predicted!
