Collecting custom trend data is a costly and time consuming endeavor. Investors looking for hyper-local economic data in emerging markets typically face a challenge because data is not readily available through traditional data mining and government releases can be unreliable. The value of hyper-local data, however, is enormous, especially when building economic models to stay ahead of the curve.
One of Findyr’s clients suspected that data release from Argentina’s Central Bank were not accurate. They wanted to build out their own pricing index with weekly data collection around the country, but had difficulty structuring the project, until they worked with Findyr.
Findyr used its network of collectors across Argentina to collect the prices of consumer products and foods in major cities. Findyr collectors recorded and photographed the prices of a basket of goods at 3 supermarkets per city every week. Findyr’s client analyzed the data and used it build models that more closely forecast investor sentiment, as opposed to data releases from Argentina’s government institutions. Findyr’s data has been cross validated with the new President Mauricio Macri’s own data collection efforts, which kept our client ahead of the curve.