Confidence intervals are rarely reported with economic data, even though they are easily understood when reporting a public opinion poll. Retail sales, like other economic data are only estimates (based on a sample of a larger group) and therefore each report has a confidence interval. Retail sales' confidence interval happens to be +/- 0.5%, meaning that there is at least a 30% chance that retail sales actually missed the consensus estimate of 0.3% in July.
Another factor that significantly changes the interpretation of reported economic data is the seasonal adjustment, which is particularly true for retail sales. Take a look at a comparison of seasonally and not seasonally adjusted charts since '00.
Seasonally adjusted, retail sales were up in July 0.5%. Not seasonally adjusted, they were down 1.04%. Adding to the noise, the seasonal adjustment isn't constant and varies from year to year. For example, the seasonal adjustment factor for January is below:
Seasonal adjustment is an added estimation on top of the estimated retail sales figure. This creates the opportunity for further misstatement.
Ignoring confidence intervals and seasonal adjustments can have a significant effect on the lens with which one views economic data. In addition to these factors, "real" data adjustments (particularly to GDP) and historical revisions effect the interpretation of individual data-points. Because of these inadequacies, beats and misses for any individual economic datapoint should be taken with a grain of salt.