{'fraction_non_alphanumeric': 0.011611030478955007, 'fraction_numerical': 0.005805515239477504, 'mean_word_length': 5.2727272727272725, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
ST-156 Optimizing the Marketing Mix

1. ABSTRACT Practitioners in the media industry are frequently faced with the problem of diverting limited resources among several alternative channels. The paper looks at this problem of optimal allocation of limited resources to maximize an objective function within the context of media mix modeling. If the objective function is linear or convex these problems can be easily solved by applying standard methods of linear or geometric programming. However, in the media world, non linear relationships between sales and media variables and advertising carry over effects can lead to non convex objective functions that make matters more complicated.