Marketing Analytics Tools Online: RFM, CLV, MMM
Analyse customers, channels and sales from your own transaction and campaign data, privately in the browser. Segment customers with RFM, predict their lifetime value, track cohort retention, find products bought together, measure the return on each marketing channel with a marketing mix model or Markov attribution, estimate price elasticity, test whether advertising leads sales with Granger causality, forecast sales and model the adoption of new products.
RFM Analysis and Customer Segmentation
Score every customer on recency, frequency and monetary value from a transaction file and group them into segments such as Champions, At risk and Lost.
Replaces Excel templates · Klaviyo RFMCustomer Lifetime Value (BG/NBD and Gamma-Gamma)
Predict each customer’s future purchases, probability of being active and lifetime value from transaction data with the BG/NBD and Gamma-Gamma models.
Replaces Python lifetimes · R BTYDCohort Retention Analysis
Group customers by the month (or week) of their first purchase and track how many return, with a retention heatmap, average retention curve and revenue per customer.
Replaces Mixpanel · Amplitude · ExcelMarket Basket Analysis (Association Rules)
Find products bought together with the Apriori algorithm: frequent itemsets and rules with support, confidence, lift, leverage and conviction.
Replaces R arules · Python mlxtendMarketing Mix Modeling (MMM)
Regression-based media mix model with adstock carry-over and diminishing returns: channel contributions, ROI, marginal ROI, response curves and a budget reallocation.
Replaces Robyn · Meridian · LightweightMMMPrice Elasticity of Demand Calculator
Estimate own-price and cross-price elasticity from sales data with log-log regression, revenue impact of price changes and the profit-maximising price.
Replaces Excel · StataBass Diffusion Model (New Product Forecasting)
Fit the Bass model to adoption or sales data: coefficients of innovation and imitation, market potential, peak timing and a forecast.
Replaces Excel Solver · R diffusionMarketing Attribution (Markov Chain and Multi-Touch Models)
Credit conversions and revenue to channels from customer journeys: Markov chain removal effects compared with first-touch, last-touch, linear, position-based and time-decay models.
Replaces Google Analytics · ChannelAttribution (R)Sales Forecasting (Exponential Smoothing and ARIMA)
Forecast sales or demand with Holt-Winters exponential smoothing and automatic ARIMA, compared on a holdout, with 80% and 95% prediction intervals.
Replaces Excel FORECAST.ETS · R forecastGranger Causality Test
Test whether past values of one series predict another, in both directions, for each lag with AIC and BIC.
Replaces EViews · StataRFM Analysis and Customer Segmentation
Use RFM analysis to segment customers from transaction data for email, CRM and retention campaigns: it needs only three columns, works for any business with repeat purchases, and its segments are easy to act on.
Customer Lifetime Value (BG/NBD and Gamma-Gamma)
Use it for non-contractual businesses (online shops, retail, restaurants, apps with in-app purchases) where customers can stop buying at any time without telling you, to predict future purchases and value per customer and to identify customers who have probably churned.
Cohort Retention Analysis
Use cohort analysis to track retention, repeat purchase and revenue per customer over time, compare the quality of customers acquired in different months or campaigns, and see whether product or onboarding changes improved retention.
Market Basket Analysis (Association Rules)
Use market basket analysis to find cross-selling opportunities, design bundles and store layouts, power “frequently bought together” recommendations or understand which content and services are used together.
Marketing Mix Modeling (MMM)
Use a marketing mix model to estimate the sales contribution and ROI of each paid channel from aggregate weekly or monthly data, without user-level tracking, and to see where extra budget would work best.
Price Elasticity of Demand Calculator
Use it to quantify price sensitivity from historical sales or price-test data, compare products or segments, check whether a price change will raise revenue, and find the profit-maximising price.
Bass Diffusion Model (New Product Forecasting)
Use the Bass model to forecast the adoption of new products, services or technologies (durables, subscriptions, apps, medical devices, EVs), to estimate the market potential from early sales, or to forecast by analogy using p and q from similar products.
Marketing Attribution (Markov Chain and Multi-Touch Models)
Use multi-touch attribution to understand how channels work together along the customer journey, to compare data-driven (Markov) credit with rule-based models such as last click, and to inform budget discussions.
Sales Forecasting (Exponential Smoothing and ARIMA)
Use it to forecast sales, demand, revenue, website traffic or any regularly spaced series for planning, budgeting and inventory, when you want an automatic, defensible method with honest uncertainty bands.
Granger Causality Test
Use it to test lead-lag relationships between stationary time series, for example whether money growth predicts inflation.
Other categories
Data cleaning and preparation · Describe and explore · Compare means · Nonparametric tests · Correlation and regression · Bayesian statistics · Categorical data · Reliability and agreement · Multivariate analysis · Structural equation modeling · Econometrics and time series · Panel data and causal inference · Marketing research · Survival, clinical and meta-analysis · Study planning and calculators · PLS-SEM