How to Use Predictive Analytics for Gym Owners

This title was summarized by AI from the post below.
View profile for Lee-Anne Kingma

Automation & AI Strategist | Software Quality Leader | Transforming Operations

🧮 Let's demystify "𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀" for gym owners... 𝗪𝗵𝗮𝘁 𝗜𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗠𝗲𝗮𝗻𝘀: Using historical patterns to forecast future behavior. This would have been a game-changer for my gym & I know it can be for yours too! 𝗛𝗼𝘄 𝗜𝘁 𝗪𝗼𝗿𝗸𝘀 (Simple Version): 𝗦𝘁𝗲𝗽 𝟭: 𝗗𝗮𝘁𝗮 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 Track member behaviors: attendance, class types, check-in times, social engagement 𝗦𝘁𝗲𝗽 𝟮: 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻 AI identifies patterns in members who 𝗦𝗧𝗔𝗬𝗘𝗗 vs. members who 𝗟𝗘𝗙𝗧 𝗦𝘁𝗲𝗽 𝟯: 𝗥𝗶𝘀𝗸 𝗦𝗰𝗼𝗿𝗶𝗻𝗴 Current members are scored based on how closely they match "about to leave" patterns 𝗦𝘁𝗲𝗽 𝟰: 𝗜𝗻𝘁𝗲𝗿𝘃𝗲𝗻𝘁𝗶𝗼𝗻 𝗧𝗿𝗶𝗴𝗴𝗲𝗿𝘀 When 𝗿𝗶𝘀𝗸 𝘀𝗰𝗼𝗿𝗲 𝗵𝗶𝘁𝘀 𝘁𝗵𝗿𝗲𝘀𝗵𝗼𝗹𝗱 → automatic alert to staff 𝗥𝗲𝗮𝗹 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝗳𝗿𝗼𝗺 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵: System notices member: Attendance dropped 40% (warning sign) Stopped attending usual Tuesday class (warning sign) No trainer interactions in 3 weeks (warning sign) Payment was late last month (warning sign) 𝗥𝗲𝘀𝘂𝗹𝘁: 𝗛𝗶𝗴𝗵-𝗿𝗶𝘀𝗸 𝘀𝗰𝗼𝗿𝗲 → 𝗜𝗻𝘁𝗲𝗿𝘃𝗲𝗻𝘁𝗶𝗼𝗻 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝗲𝗱 → 𝗠𝗲𝗺𝗯𝗲𝗿 𝘀𝗮𝘃𝗲𝗱 𝗧𝗵𝗲 𝗕𝗲𝗮𝘂𝘁𝘆: This happens 𝗔𝗨𝗧𝗢𝗠𝗔𝗧𝗜𝗖𝗔𝗟𝗟𝗬 across all members simultaneously No human could monitor 300+ members this closely 𝗧𝗵𝗲 𝗟𝗶𝗺𝗶𝘁𝗮𝘁𝗶𝗼𝗻: Only as good as the data you feed it Garbage in = garbage out 𝗠𝘆 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻: What data do you currently track about your members? Just attendance, or deeper behavioral stuff too? #PredictiveAnalytics #GymAnalytics #AIExplained #DataScience #FitnessData #GymOwners #AnalyticsEducation #MemberBehavior #SmartTech #FitnessInnovation

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