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What we can do in Retail analytics by bhawani nandanprasad

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Bhawani N Prasad
Bhawani N Prasad

1. The document discusses various retail analytics strategies and solutions including: retail product life cycle price optimization, markdown optimization for short and long life cycle products, data mining for price optimization, key value item analysis, assortment and space optimization, market basket analytics, optimization intelligence reporting, promotion strategy and measurement, social commerce, and cluster analysis. 2. The solutions aim to optimize pricing, promotions, inventory, and assortments to increase sales and profits through techniques like price elasticity analysis, simulation, localization, and predictive analytics. 3. Benefits cited include increased sales 1-12%, gross margin gains 2-20%, ROI of $10-20 for every $1 invested, and better decision making through

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Retail Analytics Bhawani Nandan Prasad MS Computer Science and MBA Target Customer in Retail domain: Retailers in Grocery, Convenience, Specialty, General Merchandise, Health and Beauty, Deep Discount, Home and Garden, Building Supplies and Grocery Wholesale 1. Retail Product Life Cycle Price Optimization  Manage & Optimize Prices across the Pricing Life Cycle  Increase Pricing Precision thru Rules, Science & Strategy Business Revenue Benefits  Compete More Profitably  Shape Shopper Behavior  Enable Data-Driven Decisions  Return on Investment $10-20 on every $1 invested  Forecast Accuracy 91-94%  Sales Increases 2-7%  Gross Margin Gains 2-5% Product life cycles vary across stores, markets and channels and the proliferation of data to be analyzed is daunting without scientific solutions which can organize the data, make inferences and create recommendations that are localized and shopper-centric. • Image enhancing, profitable prices that achieve strategic and financial objectives • Targeted, loyalty building, measurable promotions that incentivize omnichannel shoppers to buy more and buy more often • Effective end-of-life and end-of-season markdowns that clear inventory at the highest possible margin – not giving away too much too soon or too little too late
Life Cycle Price Optimization enables retailers to execute precise, localized life cycle pricing that maximizes profitability while achieving category, channel, store, loyalty and performance objectives. 2. Markdown Optimization For Short Life Cycle Products  Forecast Accuracy 91-94%  Sales Increases 11-20%  Gross Margin Gains 5%  Increase in Capture Rates 4.5-12% Balances Desired Stock Positions, Exit Dates & Budget Priorities Escalating markdown budgets have challenged retailers to pare down bloated inventory positions while still presenting fresh assortments on-time and as-planned. Across-the-board markdowns have exacerbated the financial impact by further hemorrhaging margin. Decisions are often emotional and typically do not achieve their objectives because: • ‘Too much too soon’ causes stock outs & margin loss • ‘Too little too late’ causes excess stock & impacts sales of new products at full price • ‘Too everywhere’: Enterprise-wide markdowns cause sales & margin loss
3. Markdown Optimization For Large Life Cycle Products  Markdown Planning, Strategy, Simulation & Measurement  Maximize Sell-through & Profitability with Localization Stop leaving money on the table by taking enterprise-wide markdowns or making suboptimal decisions for timing, cadence & depth. Markdown Optimization empowers retailers to clear inventory while meeting sellthrough & profitability goals. Not just for seasonal or discontinued items anymore, retailers’ leverage optimization for category resets, overstock reductions, aged packaging, & date-coded product. • Localizing Markdowns to Shopper Demand & Inventory Depletion Rates enables retailers to maximize margin & inventory value while improving freshness & velocity of product assortment. • Planning, Management & Predictive Analytics take the emotion out of markdown decisions by enabling process driven markdown execution.
4. Data Mining Analytics for price optimization Analytic services enable retailers to jump start their Price Optimization implementation with deep insight into channel, location, and competitor and product price elasticity. Once retailers get the right start, these services provide additional value by permitting clients to increase pricing sophistication and solve complex problems as they move up the maturity curve. Evaluating elasticity at the outset permits initial system configuration that maximizes the effectiveness of: • Key (Known) Value Items • Item Investment Classification • Store Zone Clustering • Competitive Positioning • Category & Sub-Category Strategies Designed to easily adapt to the growing skill sets and sophistication levels of retailers, Price Optimization and Advanced Analytics enable clients to continually drive significant ROI as their organizations gain experience, refine strategies and hone competitive positions.
Build data visualization for elastic workbench and Competitive Intelligence workbench. 5. Key Value Item Analysis - Scientific Insight into the Items that Drive Price Image, Impacting Pricing Strategy & Competitive Positioning. • Evaluation of item elasticity • Rankings and recommendations of the top items individually or by price family • Lists and rankings by pricing zone, & by category or department • Coverage analysis to determine percent of business included on KVI lists Analysis including: – Product count by department – Sales metrics by department – Top 500 breakdown by category – Top 15 items by revenue change – Top 15 items by quantity change – Top item grouping metric comparison – Breakdown of the top 100, 250, 500 items & groups Austin |
For retailers, a small subset of items has a disproportionate impact on consumer price perception. These sensitive items are known as Key Value Items, or KVIs. If a retailer can scientifically identify those items and their relative price sensitivity, it can have significant control over their perceived price image. Unfortunately, many retailers don’t have the tools and are left with gut feel, missing opportunities to optimally price the right items. Companies brings advanced science to supplement a retailer’s intuition for improved performance and price perception. By aggressively pricing true KVIs, retailers are able to: • Influence consumer price perception • Drive store traffic • Compare competitive prices more strategically • Gain market share against their competitors • Maintain profitability on less price-sensitive items in their stores. Apply Decision science based analysis Scientific product segmentation: Identifies and segments items that reflect or display: • High sensitivity, or demand response, to price changes
• High sales volume • Ability to drive store traffic • “Anchoring” position in market baskets • High scores on price awareness surveys • Sensitivity to local competitive influence Design KVI Groups by need: The analysis can be performed at the chain level, by region, by pricing zone, or by category. Validate and compare: Our recommendations can be used as a stand-alone item group or to augment and validate a retailer’s own KVI item list. Coverage analysis: Evaluate the fraction of items, by count and by revenue, that are included in KVI lists for optimal coverage scenarios. 6. Assortment & Space Optimization to increase sales - Sales Increases: 2-7% - Gross Margin Gains: 2-4% - Increased Customer, Traffic Count, Larger Shopper Baskets, Return on Investment Within 2 Months This is Predictive analytics Assortment-aware Store Space Optimization. • Recommends reformats, remodels and refits to ‘right-size’ locations and assortments within space • Simulates ‘What If’ scenarios to evaluate strategy • Breaks down silos between Assortment and Space planning through simultaneous optimization • Ensures proper capacity, facings and SKU presence • Predictive optimization – identifies “size of the prize” before making changes. • Incorporates 3rd party Market Data to identify competitive gaps and opportunities • Determines fair share of market and identifies category growth opportunities • Provides guidance to store reinvention • Augments and integrates with current assortment and space planning tools
What we can do in Retail analytics by bhawani nandanprasad
7. Market Basket Analytics Deep Insight into Shopper Behavior - Impacting Forecasts, Recommendations & Decisions. Retailers leverage Market Basket Analysis to provide a window into shopper behavior, revealing how they select products, make spending trade-offs and group items in a shopping cart. Understanding how baskets are built can help retailers merchandise more effectively by leveraging market basket dynamics in pricing and promotion decisions. Analysis of transaction-level sales data can reveal deep insights into shopper buying behavior and answer questions such as: • What products tend to be purchased together? • Are shoppers more willing to buy multiples if incented? • What baskets are the most profitable to my business? • What buying behavior characterizes my most profitable shopper? Understanding basket-level dynamics allows retailers to make better decisions related to base and promotional pricing enabling them to: • Improve cross-selling opportunities across categories • Up-sell to better or more profitable brands within purchased categories • Drive store traffic with the right offer & incentive • Improve sales with in-store displays by co-locating the right items • Understand the holistic impact of promotions & price changes • Improve performance of multiple-purchase offers (e.g. 2 for $2)
8. Optimization Intelligence Reporting & Analysis • Trends Trend reporting at all levels across multiple data sets • Effectiveness Measurement KPI impacts • Weekly Comparisons Highlight sales, top performers & margins • Competitors CPI, prices, gaps & opportunities • User Adoption & Value Measurement Recommendation acceptance rates & impact of optimization on results • Data Exception Reports Data quality & processing errors • Price Change Monitoring Monitor price change results across multiple price zones • Scenario Review Review scenario configurations & associated key metrics • Executive & CM Dashboards & Reports • Identify & respond strategically to sales trends & competitor prices • Workflow driven analytics for promotion & markdown planning, simulation, execution, monitoring & effectiveness measurement 9. Promotion Strategy, Planning, Simulation & Measurement Analytics Sales Increases 1-12% Gross Margin Gains 5-20% Unit Movement Growth 1-9% Promotional Calendar • Calendar or Grant view • Filtering capabilities • Annual promotion planning • Visibility into campaign, events & promotion Planning & Management • Intelligent dynamic workflow
• Dynamic & systematic versioning • Standard & alternate hierarchies • Strategy planning and modeling • Supports all vehicles & types • Event creation & delegation by role • Offer-level strategy configurations • Supports complex promotions Optimize • Event & offer versions • Visual layout configurations • Planning matrix, vehicles & types • Vendor trade funds • Inventory aware Data & Analytics • Real-time data & model update • Deal collection & repository • Simulation visualization & version comparison • Forecasts impacts & basket cross-effects Execution & Measurement • Approval & event status visibility • Forecast roll ups versus budget & actual • Actionable Performance Intelligence reporting • Campaign effectiveness measurement 10.Social Commerce - Drive Engagement and Amplify Customer Conversations • Leverages social media by delivering promotions amplified through Facebook • Drives the acquisition of new customers by utilizing loyal customers’ social connections • Measures social promotion campaigns and events, for social reach and provides an ROI for every channel and at every touch point • Modular: Deploys one or multiple social programs to support business objectives • Integrates with loyalty systems/programs
• Online to In-store: Integrates online, in-store, social and mobile touchpoints and channels • Redemptions at Channel of Choice: Checkout online or in-store at POS • Integrates with Promotion Optimization solution: Determines items and optimal offers and drive optimized promotions into social and ecommerce 11.Cluster Analysis- Scientifically group stores for optimal pricing alignment Benefits: • Optimally grow profit with the right price, for the right customer, at the right store • Maximize financial opportunities while recognizing regional perceptions • Localize pricing to become more consumer-centric • Compete more effectively against the relevant competition • Improve store-specific operations with insight into the point of diminishing returns Scientific Store Clusters: Identifies and segments stores by evaluating: • Consumer price sensitivity • Geography • Store-area market data, including population density and competitive price indexing (CPI) • Demographics of customers including income level, family structure, ethnicity, and employment • Competitive presence, including proximity of primary and partially competitive stores • Distribution center proximity and relative cost to serve • Retailer-defined business rules Service Deliverables Store Cluster Analysis provides retailers actionable insight into the best store clusters. The service deliverables include: • Store elasticity analysis • Cost-benefit analysis of opportunity versus number of clusters • Recommended store assignments for each cluster scenario
• Demographic and competitive factor analysis of dominant factors in cluster selection • Demographic and competitive profiles of recommended cluster groupings • Incorporation of business rules into cluster analysis • Pricing consultation to leverage desired strategies to price optimization configurations

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What we can do in Retail analytics by bhawani nandanprasad

  • 1. Retail Analytics Bhawani Nandan Prasad MS Computer Science and MBA Target Customer in Retail domain: Retailers in Grocery, Convenience, Specialty, General Merchandise, Health and Beauty, Deep Discount, Home and Garden, Building Supplies and Grocery Wholesale 1. Retail Product Life Cycle Price Optimization  Manage & Optimize Prices across the Pricing Life Cycle  Increase Pricing Precision thru Rules, Science & Strategy Business Revenue Benefits  Compete More Profitably  Shape Shopper Behavior  Enable Data-Driven Decisions  Return on Investment $10-20 on every $1 invested  Forecast Accuracy 91-94%  Sales Increases 2-7%  Gross Margin Gains 2-5% Product life cycles vary across stores, markets and channels and the proliferation of data to be analyzed is daunting without scientific solutions which can organize the data, make inferences and create recommendations that are localized and shopper-centric. • Image enhancing, profitable prices that achieve strategic and financial objectives • Targeted, loyalty building, measurable promotions that incentivize omnichannel shoppers to buy more and buy more often • Effective end-of-life and end-of-season markdowns that clear inventory at the highest possible margin – not giving away too much too soon or too little too late
  • 2. Life Cycle Price Optimization enables retailers to execute precise, localized life cycle pricing that maximizes profitability while achieving category, channel, store, loyalty and performance objectives. 2. Markdown Optimization For Short Life Cycle Products  Forecast Accuracy 91-94%  Sales Increases 11-20%  Gross Margin Gains 5%  Increase in Capture Rates 4.5-12% Balances Desired Stock Positions, Exit Dates & Budget Priorities Escalating markdown budgets have challenged retailers to pare down bloated inventory positions while still presenting fresh assortments on-time and as-planned. Across-the-board markdowns have exacerbated the financial impact by further hemorrhaging margin. Decisions are often emotional and typically do not achieve their objectives because: • ‘Too much too soon’ causes stock outs & margin loss • ‘Too little too late’ causes excess stock & impacts sales of new products at full price • ‘Too everywhere’: Enterprise-wide markdowns cause sales & margin loss
  • 3. 3. Markdown Optimization For Large Life Cycle Products  Markdown Planning, Strategy, Simulation & Measurement  Maximize Sell-through & Profitability with Localization Stop leaving money on the table by taking enterprise-wide markdowns or making suboptimal decisions for timing, cadence & depth. Markdown Optimization empowers retailers to clear inventory while meeting sellthrough & profitability goals. Not just for seasonal or discontinued items anymore, retailers’ leverage optimization for category resets, overstock reductions, aged packaging, & date-coded product. • Localizing Markdowns to Shopper Demand & Inventory Depletion Rates enables retailers to maximize margin & inventory value while improving freshness & velocity of product assortment. • Planning, Management & Predictive Analytics take the emotion out of markdown decisions by enabling process driven markdown execution.
  • 4. 4. Data Mining Analytics for price optimization Analytic services enable retailers to jump start their Price Optimization implementation with deep insight into channel, location, and competitor and product price elasticity. Once retailers get the right start, these services provide additional value by permitting clients to increase pricing sophistication and solve complex problems as they move up the maturity curve. Evaluating elasticity at the outset permits initial system configuration that maximizes the effectiveness of: • Key (Known) Value Items • Item Investment Classification • Store Zone Clustering • Competitive Positioning • Category & Sub-Category Strategies Designed to easily adapt to the growing skill sets and sophistication levels of retailers, Price Optimization and Advanced Analytics enable clients to continually drive significant ROI as their organizations gain experience, refine strategies and hone competitive positions.
  • 5. Build data visualization for elastic workbench and Competitive Intelligence workbench. 5. Key Value Item Analysis - Scientific Insight into the Items that Drive Price Image, Impacting Pricing Strategy & Competitive Positioning. • Evaluation of item elasticity • Rankings and recommendations of the top items individually or by price family • Lists and rankings by pricing zone, & by category or department • Coverage analysis to determine percent of business included on KVI lists Analysis including: – Product count by department – Sales metrics by department – Top 500 breakdown by category – Top 15 items by revenue change – Top 15 items by quantity change – Top item grouping metric comparison – Breakdown of the top 100, 250, 500 items & groups Austin |
  • 6. For retailers, a small subset of items has a disproportionate impact on consumer price perception. These sensitive items are known as Key Value Items, or KVIs. If a retailer can scientifically identify those items and their relative price sensitivity, it can have significant control over their perceived price image. Unfortunately, many retailers don’t have the tools and are left with gut feel, missing opportunities to optimally price the right items. Companies brings advanced science to supplement a retailer’s intuition for improved performance and price perception. By aggressively pricing true KVIs, retailers are able to: • Influence consumer price perception • Drive store traffic • Compare competitive prices more strategically • Gain market share against their competitors • Maintain profitability on less price-sensitive items in their stores. Apply Decision science based analysis Scientific product segmentation: Identifies and segments items that reflect or display: • High sensitivity, or demand response, to price changes
  • 7. • High sales volume • Ability to drive store traffic • “Anchoring” position in market baskets • High scores on price awareness surveys • Sensitivity to local competitive influence Design KVI Groups by need: The analysis can be performed at the chain level, by region, by pricing zone, or by category. Validate and compare: Our recommendations can be used as a stand-alone item group or to augment and validate a retailer’s own KVI item list. Coverage analysis: Evaluate the fraction of items, by count and by revenue, that are included in KVI lists for optimal coverage scenarios. 6. Assortment & Space Optimization to increase sales - Sales Increases: 2-7% - Gross Margin Gains: 2-4% - Increased Customer, Traffic Count, Larger Shopper Baskets, Return on Investment Within 2 Months This is Predictive analytics Assortment-aware Store Space Optimization. • Recommends reformats, remodels and refits to ‘right-size’ locations and assortments within space • Simulates ‘What If’ scenarios to evaluate strategy • Breaks down silos between Assortment and Space planning through simultaneous optimization • Ensures proper capacity, facings and SKU presence • Predictive optimization – identifies “size of the prize” before making changes. • Incorporates 3rd party Market Data to identify competitive gaps and opportunities • Determines fair share of market and identifies category growth opportunities • Provides guidance to store reinvention • Augments and integrates with current assortment and space planning tools
  • 9. 7. Market Basket Analytics Deep Insight into Shopper Behavior - Impacting Forecasts, Recommendations & Decisions. Retailers leverage Market Basket Analysis to provide a window into shopper behavior, revealing how they select products, make spending trade-offs and group items in a shopping cart. Understanding how baskets are built can help retailers merchandise more effectively by leveraging market basket dynamics in pricing and promotion decisions. Analysis of transaction-level sales data can reveal deep insights into shopper buying behavior and answer questions such as: • What products tend to be purchased together? • Are shoppers more willing to buy multiples if incented? • What baskets are the most profitable to my business? • What buying behavior characterizes my most profitable shopper? Understanding basket-level dynamics allows retailers to make better decisions related to base and promotional pricing enabling them to: • Improve cross-selling opportunities across categories • Up-sell to better or more profitable brands within purchased categories • Drive store traffic with the right offer & incentive • Improve sales with in-store displays by co-locating the right items • Understand the holistic impact of promotions & price changes • Improve performance of multiple-purchase offers (e.g. 2 for $2)
  • 10. 8. Optimization Intelligence Reporting & Analysis • Trends Trend reporting at all levels across multiple data sets • Effectiveness Measurement KPI impacts • Weekly Comparisons Highlight sales, top performers & margins • Competitors CPI, prices, gaps & opportunities • User Adoption & Value Measurement Recommendation acceptance rates & impact of optimization on results • Data Exception Reports Data quality & processing errors • Price Change Monitoring Monitor price change results across multiple price zones • Scenario Review Review scenario configurations & associated key metrics • Executive & CM Dashboards & Reports • Identify & respond strategically to sales trends & competitor prices • Workflow driven analytics for promotion & markdown planning, simulation, execution, monitoring & effectiveness measurement 9. Promotion Strategy, Planning, Simulation & Measurement Analytics Sales Increases 1-12% Gross Margin Gains 5-20% Unit Movement Growth 1-9% Promotional Calendar • Calendar or Grant view • Filtering capabilities • Annual promotion planning • Visibility into campaign, events & promotion Planning & Management • Intelligent dynamic workflow
  • 11. • Dynamic & systematic versioning • Standard & alternate hierarchies • Strategy planning and modeling • Supports all vehicles & types • Event creation & delegation by role • Offer-level strategy configurations • Supports complex promotions Optimize • Event & offer versions • Visual layout configurations • Planning matrix, vehicles & types • Vendor trade funds • Inventory aware Data & Analytics • Real-time data & model update • Deal collection & repository • Simulation visualization & version comparison • Forecasts impacts & basket cross-effects Execution & Measurement • Approval & event status visibility • Forecast roll ups versus budget & actual • Actionable Performance Intelligence reporting • Campaign effectiveness measurement 10.Social Commerce - Drive Engagement and Amplify Customer Conversations • Leverages social media by delivering promotions amplified through Facebook • Drives the acquisition of new customers by utilizing loyal customers’ social connections • Measures social promotion campaigns and events, for social reach and provides an ROI for every channel and at every touch point • Modular: Deploys one or multiple social programs to support business objectives • Integrates with loyalty systems/programs
  • 12. • Online to In-store: Integrates online, in-store, social and mobile touchpoints and channels • Redemptions at Channel of Choice: Checkout online or in-store at POS • Integrates with Promotion Optimization solution: Determines items and optimal offers and drive optimized promotions into social and ecommerce 11.Cluster Analysis- Scientifically group stores for optimal pricing alignment Benefits: • Optimally grow profit with the right price, for the right customer, at the right store • Maximize financial opportunities while recognizing regional perceptions • Localize pricing to become more consumer-centric • Compete more effectively against the relevant competition • Improve store-specific operations with insight into the point of diminishing returns Scientific Store Clusters: Identifies and segments stores by evaluating: • Consumer price sensitivity • Geography • Store-area market data, including population density and competitive price indexing (CPI) • Demographics of customers including income level, family structure, ethnicity, and employment • Competitive presence, including proximity of primary and partially competitive stores • Distribution center proximity and relative cost to serve • Retailer-defined business rules Service Deliverables Store Cluster Analysis provides retailers actionable insight into the best store clusters. The service deliverables include: • Store elasticity analysis • Cost-benefit analysis of opportunity versus number of clusters • Recommended store assignments for each cluster scenario
  • 13. • Demographic and competitive factor analysis of dominant factors in cluster selection • Demographic and competitive profiles of recommended cluster groupings • Incorporation of business rules into cluster analysis • Pricing consultation to leverage desired strategies to price optimization configurations