Harness insights from diverse data sources to take the guesswork out of merchandising decisions and drive sustainable, profitable growth
Merchandising Analytics: Merchandising Sales Analysis at a glance:
- Proven impact including up to 5% reduction in COGS, up to 2% increase in comparative/like for like sales, significant margin improvement, and 15x ROI.
- End-to-end custom solution empowering category management and buying teams with answers to ‘what’, ‘why’, ‘what will’ and ‘so what’ questions for tactical and strategic decision making.
- Modular, interconnected approach to data-driven merchandising decisions, from buying and optimising commercial levers, to increasing customer loyalty.
- Unlock actionable insights from untapped data of all sizes, forms and sources through AI and machine learning combined with proven models, algorithms and purpose-built assets.
- Always-on contextualised intelligence delivered through bespoke scalable real-time apps and dashboards, to enable faster and better merchandising decisions.
- Extensive retail expertise, category intelligence and market knowledge gained across a wide spectrum of client engagements and insight projects.
Succeed and stand out in the most competitive retail landscape ever seen
With customer behaviours changing constantly, manufacturers selling directly to customers, brand loyalty becoming more fragile, and online marketplaces posing a constant threat, succeeding in retail has never been harder.
To stand out, delight customers and drive profit today, retail teams need to:
Identify, monitor and track lead indicators of category performance and competitive moves
Understand exactly what to buy and when, and base sourcing decisions on what they can sell, not just what they can procure at a low price
Move from product to customer-centricity delivering a differentiated customer offer and experience rooted in relevance, value surplus and convenience
Enable a true omni-channel strategy as opposed to using online as just another marketing channel
Stay ahead of rapidly shifting customer trends and shorter product lifecycles by taking a predictive approach to buying and category management
Master new data sources, including in-store videos and sensors, to build a more robust understanding of how customers behave, and what they want
We provide an end-to-end AI-powered custom solution to empower your category management and buying teams to deliver higher business value…
Our specialist team delivers actionable insights through a fusion of category expertise, data analytics, reusable assets and best-in-class technology, to enable faster and smarter merchandising decision-making, delivered through bespoke real-time dashboards, portals and apps. With Merchandising Analytics from The Smart Cube, you get:
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Space and Range Planning Insights
Maximise space productivity by optimising layouts, allocations and assortments within physical and digital stores.
Pricing and Promotions Analytics
Maximise ROI from dynamic pricing and promotions decisions by quantifying SKU-level impact to drive profitable outcomes.
Supplier Intelligence and Negotiation Tools
Deliver higher margins through negotiations for lower COGS and trade terms, and drive category innovation through better supplier collaboration.
Demand Forecasting and Inventory Planning
Capture a wide range of demand signals for accurate short and long-term demand predictions, and ensure product availability at the right levels throughout the value chain.
Custom Analyses and Strategic Insights
Explore and model the viability of transformation plans like ‘own label’ development in detail, with custom category and market intelligence reports.
How your business benefits
With Merchandising Analytics from The Smart Cube, you can:
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Drive 2-5% improvement in net margin through dynamic pricing and optimised promotion tactics.
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Improve comparative/like for like sales by 50-200 basis points through improved space productivity and assortment optimisation.
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Make significant efficiency gains and time savings through our repeatable and scalable assets.
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Deliver up to 500 basis points decrease in COGS through effective supplier engagement and cost modelling.
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Reduce sourcing cycle times by 15-25% using on-demand market and supplier intelligence, and negotiation insights.
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Implement best-in-class approaches and pioneer innovative ways to stay competitive in a crowded market.
How we work with you
Whether you want to drive effective supplier negotiations, maximise promotions ROI, or increase overall category profitability, we’ll work with you to build a custom solution that is scalable and repeatable. Here’s how:
Why choose The Smart Cube?
When you choose Merchandising Analytics from The Smart Cube, you always get:
Merchandising Analytics in action
Merchandising analytics helped global tyre company with inventory planning across 2,200 stores and save $7 million
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THE CHALLENGE
The client was witnessing issues of inventory stockouts across 2,200+ stores despite no capacity constraints witnessed historically. To this end, the client wanted to optimise inventory planning and eliminate stockout scenarios across stores.
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OUR APPROACH
The Smart Cube forecasted demand at Area-SKU-month level using Stochastic Deterministic Regression, Hierarchical Linear Regression and Linear Programming Optimisation models. A web dashboard for inventory planning was developed to plan assortment and inventory. We suggested confidence intervals for proposed inventory forecasts based on past inventory-sales relationships.
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VALUE DELIVERED
The results helped the client to better manage the SKU assortment in every store, thus visualising savings of $7 million by eliminating stockout scenarios.
Better retail range planning delivered incremental sales of £39 million
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THE CHALLENGE
The client wanted an actionable ranging solution to optimise customer satisfaction and space allocation by analysing sales volume and customer transaction-level data spanning two years across more than 90,000 SKUs for over 20 categories across 1,500+ stores in the UK.
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OUR APPROACH
The Smart Cube created a web-based tool with ETL connections through Python to analyse weekly data for sales, promotions, pricing changes, space and formats and customer switching to score products for ranging. TSC then used an assortment planning model for analysing customer switching behaviour, and association rules and Markov Chains to trace customer purchase journeys, helping the range planners in their SKU selection for stores.
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VALUE DELIVERED
The automated solution helped range planners discontinue non-productive merchandise, improve space allocation in stores and facilitate ease of range planning to help them deliver annual incremental sales of around ₤39 million.
Custom analytics dashboard saved 1,600 hours across 1,500 stores
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THE CHALLENGE
The Space and Formats team of a leading retailer wanted to track the impact of space, position and range changes across the estate – covering 450 product sections across 1,500+ stores – on a dynamic basis to make better decisions for future changes.
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OUR APPROACH
The Smart Cube clustered SKUs into 35 segments using sales trends and average sales for 2 years, and applied regression techniques to calculate the dynamic baseline sales as a function of 20+ factors (including space–range–position, promotions, price and events). We developed a self-serve analytics dashboard using MicroStrategy for the teams to analyse and track changes at various levels – section, store, time, etc.
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VALUE DELIVERED
The self-serve analytics dashboard improved performance tracking of trials across stores, saved 1,600 hours annually in trial review process and optimised revenues across sections through the tool.
