{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Return of Investments for online marketing\n", "\n", "## Try me\n", " [![Open In Colab](../../_static/colabs_badge.png)](https://colab.research.google.com/github/ffraile/operations-research-notebooks/blob/main/docs/source/Simulation/Exercises/Return%20of%20search%20engine%20investments.ipynb)[![Binder](../../_static/binder_badge.png)](https://mybinder.org/v2/gh/ffraile/operations-research-notebooks/main?labpath=docs%2Fsource%2FSimulation%2FExercises%2FReturn%20of%20search%20engine%20investments.ipynb)\n", "\n", "The following metrics and indicators determine the expenditures and return of investments of marketing investments in paid inclusion (including your company's web page in search results) for your company:\n", "\n", "- **S (Total Search results in period):** Total number of times the keywords are used in searches in the planning period.\n", "- **CPM (Cost per 1000 impressions):** Cost of the search engine per every 1000 impressions, every time your website appears in a search result\n", "- **CPC (Cost per click):** Cost per every click\n", "- **CTR (Click Through Rate):** rate between the number of clicks and number of impressions\n", "- **CVR (Conversion Rate):** rate between the number of visitors and the number of users\n", "\n", "With this, the number of visitors (V) and the number of users (U) can be calculated as:\n", "\n", "$U = V * CVR = S * CTR * CVR$\n", "\n", "The total costs ($C_t$) of the search engine investmets are:\n", "\n", "$C_t = CPC*V + CPM/1000*S$\n", "\n", "\n", "The **ARPU (Average revenue per user in planning period)** is the average revenue per user, or the total revenue in the planning period (R), divided by the number of users:\n", "\n", "$ARPU = R/U$\n", "\n", "The Return of Investments for online marketing is calculated as:\n", "\n", "$ROI = \\frac{R - C_t}{C_t}$\n", "\n", "After some research, you have found that the different metrics can be modeled as normal distributions with the following parameters:\n", "\n", "| Metric | Mean | Standard Deviation |\n", "|--------|------|--------------------|\n", "|Search results | 600000 | 100000 |\n", "| CTR | 0.05 | 0.01 |\n", "| CVR | 0.5 | 0.1 |\n", "\n", "These are the search engine fees for your keywords:\n", "- CPM = 0,3€\n", "- CPC = 0,75€\n", "\n", "You estimate your ARPU in 5€\n", "\n", "**a.** Calculate the total costs, the total Return of Investments and the average cost per acquisition using Montecarlo Simulation\n", "\n", "**b.** Calculate the 95% confidence interval of the ROI" ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5" }, "pycharm": { "stem_cell": { "cell_type": "raw", "source": [], "metadata": { "collapsed": false } } } }, "nbformat": 4, "nbformat_minor": 2 }