A magazine-exposure model that mixes Klotz's (1973) dependent Bernoulli-trials model for nonsubscribers with a degenerate distribution for subscribers is proposed. LetXi= 1 if a person reads an issue of a particular magazine and 0 otherwise. Klotz's parameterization is Pr(Xi= 1) =pand Pr(Xi= 1 |Xi–1= 1) = λ fori= 1, …,k.Using the Markov assumption he obtains the joint distribution ofR= Σki=2Xi–1Xi, S= Σki=1Xi, andT = X1+Xk, of which we are interested in the marginal distribution ofS, the total number of issues a person reads. It is expected thatpwill be low for nonsubscribers but high for subscribers, so this heterogeneity is modeled by mixing Klotz's Markov model with a point mass of magnitude π at the pointS=k.Maximum likelihood estimates ofp, λ, and π are used to fit the Markov mixture model to 40 magazines from a large print-media survey. The proposed model is shown to give a much better fit to these data than the beta-binomial model, the most popular nonproprietary magazine model, and a generalization of the beta-binomial model.