RA: Retail Planning,Assortment Analytics with Excel & Python
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“This is one of the three courses in the Retail Series by RA, each course can be taken independently.”
Master Retail planning and analytics with Excel and Python
Retailers face fierce competition every day and keeping up with the new trends and customer preferences is a guarantee for excellence in the modern retail environment. one Keyway to excel in retail management is utilizing the data that is produced every day. It is estimated that We produce an overwhelming amount of data every day, roughly 2.5 quintillion bytes. According to an IBM study, 90% of the world’s data has been created in the last two years.
Retail analytics is the field of studying the produced retail data and making insightful data-driven decisions from it. as this is a wide field, I have split the Program into three parts.
Retail Planning and assortment analytics with Excel & Python.
1- Retail Metrics
2- Metrics in Python.
3- Budgeting.
4- Retail Planning in Python.
5- Retail Buying.
6- Assortment Optimization.
7- Managing Retail Inventory with Python.
8- Managing stocks based on Types.
Don’t worry If you don’t know how to code, we learn step by step by applying retail analysis!
*NOTE: Full Program includes downloadable resources and Python project files, homework and Program quizzes, lifetime access, and a 30-day money-back guarantee.
Who this Program is for:
· If you are an absolute beginner at coding, then take this Program.
· If you work in Retail and want to make data-driven decisions, this Program will equip you with what you need.
· If you are switching from Excel to a data science language. then this Program will fast-track your goal.
· If you are tired of doing the same analysis again and again on spreadsheets and want to find ways to automate it, this Program is for you.
Program Design
the Program is designed as experiential learning Modules, the first couple of modules are for retail metrics followed by Python programming fundamentals, this is to level all of the takers of this Program to the same pace. and the third part is retail applications using Data science which is using the knowledge of the first two modules to apply. while the Program delivery method will be a mix of me explaining the concepts on a whiteboard, Presentations, and Python-coding sessions where you do the coding with me step by step. there will be assessments in most of the sections to strengthen your newly acquired skills. all the practice and assessments are real retail use cases.
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1IntroductionVideo lesson
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2CurriculumVideo lesson
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3Intro To BenchmarkingVideo lesson
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4BenchmarkingVideo lesson
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5Retail MetricsVideo lesson
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6Operational metricsVideo lesson
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7Operational metrics excelVideo lesson
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8Inventory metricsVideo lesson
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9Inventory Metrics in excelVideo lesson
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10Inventory turnoverVideo lesson
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11Tesco- Walmart - KrogerVideo lesson
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12Gross Margin and Net ProfitVideo lesson
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13Assets MetricsVideo lesson
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14Cash to Cash Cycle time IntroVideo lesson
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15Cash to cash cycle timeVideo lesson
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16Cash to Cash in excelVideo lesson
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17Keys to ImproveVideo lesson
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18Data OrientationVideo lesson
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19Quiz on metricsQuiz
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20SummaryVideo lesson
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28IntroVideo lesson
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29DataframesVideo lesson
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30Arithmetic Calculations with pythonVideo lesson
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31ListsVideo lesson
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32DictionariesVideo lesson
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33ArraysVideo lesson
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34Importing data in pythonVideo lesson
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35Subsetting Data framesVideo lesson
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36ConditionsVideo lesson
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37Writing functionsVideo lesson
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38MappingVideo lesson
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39for loopsVideo lesson
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40For looping a functionVideo lesson
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41Mapping on a data frameVideo lesson
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42For looping on a dataframeVideo lesson
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43SummaryVideo lesson
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44AssignmentVideo lesson
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45Answer Part 1Video lesson
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46Assignment answer 2Video lesson
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47IntroVideo lesson
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48Dropping Duplicates and NAsVideo lesson
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49Conversions lectureVideo lesson
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50ConversionsVideo lesson
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51FilterationsVideo lesson
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52ImputationsVideo lesson
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53Indexing toutorialVideo lesson
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54Slicing indexVideo lesson
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55Manipulation LectureVideo lesson
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56Group byVideo lesson
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57Slicing the group byVideo lesson
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58Dropping levelsVideo lesson
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59The Proper formVideo lesson
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60Pivot tablesVideo lesson
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61Aggregate functions in pivot tableVideo lesson
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62Melting the dataVideo lesson
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63Left joinVideo lesson
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64Inner and outer joinVideo lesson
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65Joining in pythonVideo lesson
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66Inner, left and full joinVideo lesson
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67SummaryVideo lesson
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68AssignmentVideo lesson
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69Answer 1Video lesson
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70Answer 2Video lesson
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71Answer 3Video lesson
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72Answer 4Video lesson
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73Answer 5Video lesson
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74IntroVideo lesson
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75Preparing data for conversion rateVideo lesson
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76Conversion rateVideo lesson
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77Daily ordersVideo lesson
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78Dictionary for ordersVideo lesson
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79Average transaction value and average selling priceVideo lesson
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80Operational Metrics conclusionVideo lesson
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81Stocks DiscoveryVideo lesson
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82Daily SalesVideo lesson
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83Creating Common KeysVideo lesson
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84Creating a year week keyVideo lesson
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85Average weeklyVideo lesson
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86Joining sales with stocksVideo lesson
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87Calculating inventory turnoverVideo lesson
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88ConclusionVideo lesson
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89Section 2 AssignmentVideo lesson
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90Assignment answerVideo lesson
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91SummaryVideo lesson
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