Business Problem
Customer lifetime value (CLV) is a measurement of how valuable a customer is to your company over that customer’s lifetime. When properly mapped and calculated, it highlights those customers with whom the whole of your relationship is quantitatively greater than the sum of its individual transactions.
CLV is a difficult calculation for most companies. It’s made up of metrics like length of relationship (in years), website visits, coupons used, customer referrals, purchase volume, and product preferences — data points held in multiple disparate sources. It can be a costly, needle-in-haystack attempt to identify a small handful of extremely valuable customers, with little short- or medium-term return. That’s why convincing management of the benefits of understanding CLV — for the bottom line as well as the brand — is as important as the exercise itself.Analytics Solution
The essence of measuring CLV is to identify the transactions (visits, referrals, purchases, etc.) at which customers create value, then weave the data from those transactions into a customer journey. By adding up the revenue in each transaction and using predictors to extrapolate into the future, the company arrives at the lifetime value of that customer. The goals are to build relationships with high-value customers and to move other customers into higher-value segments through marketing.
Automation smooths the process of collecting transactions from a variety of data sources and predictive analytics extrapolates from historical data to help estimate future revenue.
Alteryx Customer Lifetime Value workflow in the Customer Analytics Starter Kit enables users to combine customer data from multiple sources and to use that data to train a forest model to predict spend for current customers. This model can then be applied to new customers to understand their expected lifetime value before they ever make a purchase.

1 - Data Access
2 - Prep & Blend
3 - Predictive Analytics
Customer Stories

データ分析の高速化により、勝利を手中に収めるマクラーレン・レーシング
週末に開催される F1 レースは年間 20 戦以上にも及び、1 レースあたり 1.5TB ものデータが生成されるため、こうした膨大な量のデータの効率的な収集、処理、活用を可能にするソリューションは欠くことのできない存在です。
マクラーレン F1 チームでは、Alteryx Analytics Automation Platform を使用して、サーキット内外で戦略的な意思決定を加速させています。

300年にわたり蓄積されたデータを次世代建築の設計に
蔵に眠っていた古い情報を、『人の想い』を伝える「使えるデータ」へと変貌させた Alteryx 老舗のデータ利用を支える Alteryx は現代における大工道具箱

Roquette 社におけるデータ文化の醸成
植物由来の原材料の世界的リーダー企業が Alteryx の導入により、戦略的な意思決定を大規模に実現。
Additional Resources
