Reference
Data & Marketing Methods
The quantitative techniques behind every Business Scenario — what each one is, in plain language, and where to see it at work.
Every scenario on this site is solved with a specific method, not a generic “marketing” playbook. This glossary defines each technique and links to the business where we put it to work — so you can find the approach that fits the problem you actually have.
Pricing & demand
Price-Elasticity Modelling
Estimating how demand changes when you change price, so you can raise prices where customers won’t flinch and protect volume where they will.
See it in action: Sushi Restaurant →Revenue Management & Dynamic Pricing
Forecasting demand by date or slot and pricing a perishable inventory to it — charging more when demand is high and less to fill the gaps.
See it in action: Boutique Hotel →Promotion-Depth Optimization
Modelling how profit, not just units, responds to discount depth, to find the sweet spot and stop training customers to wait for a sale.
See it in action: Specialty Food DTC →Conjoint Analysis
A survey technique that reveals how much customers truly value each feature or option by forcing realistic trade-offs.
See it in action: New-Build Condo Sales →Retention & customer value
RFM Segmentation
Scoring customers by how Recently, Frequently and how much (Monetary) they buy, to target the right ones with the right offer.
See it in action: Hair Salon →Cohort & Churn Analysis
Tracking groups of customers over time to see exactly when and why they leave, then acting before they do.
See it in action: Fitness Studio →Lifetime Value & LTV:CAC
Measuring what a customer is worth over their whole relationship against what they cost to acquire — the test of whether growth is profitable.
See it in action: Supplements Subscription →Repeat-Purchase / Replenishment Timing
Predicting when each customer will buy again, so reminders and subscription offers land exactly when they run low.
See it in action: Beauty & Skincare DTC →Cross-Sell Propensity Modelling
Scoring which existing customers are most likely to buy an additional product, so you offer it to the ready ones, not everyone.
See it in action: Insurance Agency →Attribution & marketing spend
Multi-Touch Attribution
Crediting every marketing touchpoint on the path to a sale, so you know which channels actually produce paying customers.
See it in action: Law Firm →Marketing-Mix Modeling (MMM)
Using spend and results over time to estimate each channel’s true contribution and diminishing returns, without relying on click tracking.
See it in action: Plumbing Company →Incrementality (Geo-Lift) Testing
Controlled experiments that measure the sales a channel actually causes, separating real lift from demand it would have captured anyway.
See it in action: Home & Furniture Online →Lead Scoring
Ranking enquiries by their probability of converting, so the team spends its time on the leads most likely to close.
See it in action: Commercial Leasing →Speed-to-Lead Optimization
Quantifying how win rate decays with response time, then engineering the intake to reach leads within the window that wins them.
See it in action: Electrician →A/B Testing & Conversion Optimization
Showing two versions to comparable visitors and measuring which converts better, to a level of statistical significance.
See it in action: Tour Operator →Operations & capacity
Queueing Theory
The mathematics of waiting lines, used to staff exactly enough servers to keep waits below the point where customers walk away.
See it in action: Specialty Coffee Café →Inventory Optimization (EOQ & Reorder Points)
Calculating how much to order and when, to avoid stockouts without tying up cash in dead stock.
See it in action: Auto Repair Shop →Capacity & Staffing Models
Forecasting workload and sizing the team to match a demand curve, protecting both service quality and payroll.
See it in action: Accounting / Tax Practice →Route-Density Optimization
Clustering jobs geographically so crews drive less and complete more, turning fixed travel cost into margin.
See it in action: Landscaping / Lawn Care →Forecasting, risk & geography
Demand Forecasting
Predicting future demand from history, weather, season and events, so staffing, inventory and pricing match what is coming.
See it in action: HVAC Company →Newsvendor Model
Forecasting demand for perishable goods and producing the profit-maximising quantity, balancing waste against stockout cost.
See it in action: Bakery & Pastry →Monte Carlo Simulation
Running an uncertain process thousands of times to see the range of likely outcomes — the expected result and the risk around it.
See it in action: Wedding / Event Venue →Hedonic Pricing Regression
Estimating how much each attribute — size, location, condition — contributes to price, to value something accurately from comparable sales.
See it in action: Residential Brokerage →Geospatial Demand Analysis
Mapping where demand and profit actually are, so marketing and operations concentrate where they pay.
See it in action: Roofing Company →Returns Prediction
Modelling which orders and SKUs are likely to be returned, to fix the sizing and merchandising that cause costly returns.
See it in action: Fashion & Apparel Store →No-Show & Risk Prediction
Scoring appointments or bookings by the risk they fall through, so you can confirm, over-book or backfill intelligently.
See it in action: Dental Clinic →Market-Basket Analysis
Finding which items are bought together, to design bundles, menu adjacencies and upsells around real behaviour.
See it in action: Izakaya / Bar →Review-Sentiment & NPS Drivers
Mining reviews to rank which factors actually move your rating, so you fix what matters, not the loudest complaint.
See it in action: Ryokan / B&B →Frequently asked questions
What is the difference between marketing attribution and incrementality?
Attribution assigns credit for a sale to the marketing touchpoints a customer saw; incrementality testing measures the sales a channel actually caused, through controlled experiments. Attribution can over-credit channels that simply catch buyers already intending to purchase, while incrementality reveals true lift.
Which method does my business need?
It depends on where profit is leaking. If pricing is the issue, price-elasticity or revenue management; if you lose customers, RFM and churn analysis; if marketing spend is murky, attribution, marketing-mix modeling or incrementality; if capacity is the constraint, queueing or staffing models. Each Business Scenario pairs a method with a situation.
Do I need a data scientist on staff to use these?
No. Sparkle & Innovation runs the analysis from your existing data and hands back the decisions — the prices, schedules, budgets and dashboards — your team can act on without becoming statisticians.
Are these techniques only for big companies?
No. Every method here is applied to small and mid-size businesses using the data they already have. The math is the same one large companies use; we make it practical at any scale.
Not sure which method your business needs?
That is exactly what a marketing audit is for. Send us your numbers and we will tell you.