{"library":"marketing-attribution-models","title":"marketing-attribution-models","description":"A library for marketing attribution modeling, providing implementations of popular attribution methods such as first-click, last-click, linear, time-decay, position-based, and Markov chain models. Current version 1.0.11, with an active maintenance cadence on GitHub. Requires Python >=3.5.","language":"python","status":"active","last_verified":"Fri May 01","install":{"commands":["pip install marketing-attribution-models"],"cli":null},"imports":["from marketing_attribution_models import AttributionModel","from marketing_attribution_models import HeuristicAttribution","from marketing_attribution_models import MarkovChainAttribution"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import pandas as pd\nfrom marketing_attribution_models import HeuristicAttribution\n\n# Sample journey data\njourneys = pd.DataFrame({\n    'path': ['A > B > C', 'A > C > B'],\n    'conversion': [1, 0],\n    'revenue': [100, 0]\n})\n\nmodel = HeuristicAttribution(method='linear')\nresult = model.attribution(journeys)\nprint(result)","lang":"python","description":"Create a HeuristicAttribution model with the 'linear' method and fit it to sample journey data.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}