Analytics Tools Catalog

Find your optimal price range using the Price Sensitivity Meter. Upload survey data to discover where customers see value.

Estimate demand at different price points using direct survey responses. Find revenue-maximizing prices fast.

Qualitative elasticity assessment when you don't have hard data. Rate 10 factors to estimate price sensitivity.

Score your organization's pricing maturity across 11 dimensions. Identify gaps and prioritize improvements.

Evaluate your ability to raise prices without losing customers. Measure brand strength and competitive position.

Comprehensive pricing audit framework. Score strategy, execution, and analytics capabilities.

Find the right pricing metric. Evaluate value alignment, predictability, and scalability.

Calculate how sensitive your customers are to price changes. Know your pricing power before making moves.

Calculate price, revenue, and profit elasticities from demand model equations. For advanced pricing analysis.

Find profit-maximizing prices using elasticity estimates. Works with linear and constant elasticity demand.

Optimize prices using constant elasticity demand model. Q = A x P^e with visual demand curves.

Flexible optimizer for custom demand functions. Define your own model and find optimal prices.

Calculate Nash equilibrium prices in competitive markets. Model Bertrand competition.

Calculate optimal discount levels and timing. Model lift, cannibalization, and stockpiling.

Find optimal bundle prices. Compare pure bundling, mixed bundling, and unbundled strategies.

Model different pricing for different segments. Calculate optimal prices for 1st, 2nd, and 3rd degree discrimination.

Design optimal good-better-best pricing tiers. Analyze gaps, cannibalization risk, and upgrade paths.

Simulate dynamic pricing based on demand, inventory, and time. Model surge pricing and markdowns.

Model penetration pricing for new product launches. Calculate break-even share and payback period.

Track how list price becomes pocket price. Find margin leakage from discounts, rebates, and allowances.

Calculate Laspeyres, Paasche, and Fisher price indices. Track price changes over time.

Measure cannibalization from new products or price changes. Calculate net revenue impact.

Generate orthogonal or fractional factorial designs for conjoint analysis. Download R Shiny app.

Simulate market shares using conjoint part-worth utilities. Test configurations and pricing scenarios.

Estimate multinomial logit choice models from purchase data. Download R Shiny app with mlogit.

Find hidden customer segments with different price sensitivities. Cluster-wise regression analysis.

Calculate Customer Lifetime Value using multiple models. Size your customer investments properly.

Calculate Customer Acquisition Cost by channel. Compare CAC/LTV ratios and payback periods.

Analyze customer retention by cohort. Visualize churn patterns and calculate retention rates.

Segment customers by Recency, Frequency, and Monetary value. Find champions and at-risk customers.

Calculate Net Promoter Score with confidence intervals. Benchmark against industry standards.

Identify cross-sell opportunities from transaction data. Find product associations and bundles.

Analyze won and lost deals to understand price sensitivity. Find optimal pricing by segment.

Calculate all key SaaS metrics: LTV, CAC, payback, gross margin. See if your unit economics work.

Calculate MRR, ARR, and subscription metrics. Model expansion revenue, churn, and cohorts.

Model freemium economics. Calculate required conversion rates and optimal feature splits.

Model pay-as-you-go pricing. Design usage tiers and calculate revenue at different consumption levels.

Track upsell and cross-sell revenue. Analyze expansion patterns by cohort and segment.

Calculate NRR and NDR metrics. Model the impact of churn, contraction, and expansion.

Determine free vs paid features. Optimize the feature mix to maximize conversion and revenue.

Analyze trial conversion patterns. Identify drivers and optimize trial experience.

Find optimal annual discount. Model NPV impact and customer preference tradeoffs.

Analyze deal approval patterns. Identify bottlenecks and optimize approval workflows.

Track variance from list price. Identify patterns in discounting across segments and reps.

Score negotiation outcomes. Benchmark deal performance against targets and peers.

Calculate multi-year contract profitability. Model escalations, renewals, and total value.

Design volume discount structures. Optimize tier breakpoints and discount percentages.

Model competitive bid pricing. Calculate win probability at different price points.

Calculate TCO vs competitors. Include implementation, maintenance, and hidden costs.

Optimize wholesale and retail prices across distribution channels. Handle double marginalization.

Model pricing across 4 competitive channel scenarios. Compare integrated, Stackelberg, and Nash equilibria.

Model how customers form reference prices. Understand price expectations and perception gaps.

Test different anchoring strategies. Simulate how initial prices influence customer decisions.

Quantify loss aversion using prospect theory. Model asymmetric responses to gains and losses.

Optimize for customer spending categories. Understand mental budget allocation patterns.

Create optimal decoy products. Design asymmetrically dominated options to steer choice.

Measure perceived price fairness. Understand when customers view prices as just or exploitative.

Analyze A/B test results with statistical significance. Get sample size requirements and power analysis.

Design rigorous price tests. Calculate required sample sizes, duration, and geographic splits.

Run generalized linear models: OLS, logistic, Poisson. Analyze pricing drivers with proper tests.

Track and analyze competitor prices. Calculate price indices and identify pricing gaps.

Forecast new product adoption using the Bass model. Estimate p and q coefficients, predict peak timing.

Forecast demand using trend, seasonality, and price effects. Compare moving average and regression.

Calculate breakeven point in units and revenue. Visualize cost-volume-profit relationships.

Calculate gross margin, markup, and contribution margin. Convert between margin and markup.

Calculate return on investment for pricing initiatives. Compare ROI across project options.

Calculate Income Elasticity of Demand. Classify products as normal, luxury, or inferior goods.

Calculate TAM, SAM, and SOM for your market. Use top-down and bottom-up approaches.

Analyze marketing ROI across channels. Decompose sales into base, price, and marketing effects.

ML-based price optimization. Use gradient boosting and neural nets for complex demand patterns.

Estimate demand curves from data. Fit linear, log-log, and semi-log specifications.

Cluster customers by price sensitivity. Identify natural segments using unsupervised learning.

Analyze price trends over time. Decompose seasonality, trend, and cyclical patterns.

Measure causal impact of price changes. Use synthetic control and diff-in-diff methods.

Model differential price effects. Find who responds most to price changes for personalization.

Calculate cross-price elasticity between products. Identify substitutes and complements.

Set prices across countries. Account for purchasing power, taxes, and local competition.

Model FX impact on pricing. Analyze hedging strategies and currency exposure.

Optimize intercompany prices. Model tax implications and compliance requirements.

Adjust for regional income differences. Calculate PPP-based price adjustments.

Optimize prices by shelf position. Account for visibility, facings, and placement effects.

Analyze trade promotion ROI. Calculate lift, pass-through, and incremental volume.

Optimize across product category. Balance competition, substitution, and category profit.

Analyze national vs private label gaps. Optimize price positioning against store brands.

Optimize markdown timing and depth. Maximize clearance revenue while minimizing margin loss.

Benchmark professional service rates. Compare by role, industry, and geography.

Calculate project prices. Estimate effort, apply margins, and create detailed quotes.

Calculate fees based on value delivered. Model client outcomes and fair value share.

Optimize retainer structures. Balance capacity utilization with client value perception.

Model competitor responses to your pricing moves. Anticipate reactions and counter-strategies.

Map price vs value position. Visualize competitive landscape and identify white space.

Identify price leaders and followers. Analyze who moves first and who reacts.

Track competitive position over time. Monitor price index trends and gap changes.

Track price exceptions and overrides. Monitor approval patterns and exception trends.

Monitor pocket price realization. Track where margin leaks and identify improvement opportunities.

Score pricing execution quality. Track KPIs across teams, regions, and products.

Design approval matrices. Define discount authority levels by role, deal size, and segment.

Analyze hospital pricing and chargemasters. Compare costs across facilities and payers.

Simulate airline yield management. Model fare classes, overbooking, and revenue optimization.

Optimize hotel pricing. Balance occupancy, ADR, and RevPAR across room types and seasons.

Calculate insurance premiums. Model risk factors, loss ratios, and competitive positioning.