When estimating a mean based on a sample of \(M\) independent draws, the estimation error is proportional to \(1/M\). If the draws are positively correlated, as they typically are when drawn using MCMC methods, the error is proportional to \(1/\sqrt{n_{eff}}\) where \(n_{eff}\) is the effective sample size. Thus it is standard practice to also monitor (an estimate of) the effective sample size until it is large enough for the estimation or inference task at hand.