Merchandising Analytics at a glance:
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.
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
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:
Maximise space productivity by optimising layouts, allocations and assortments within physical and digital stores.
Maximise ROI from dynamic pricing and promotions decisions by quantifying SKU-level impact to drive profitable outcomes.
Deliver higher margins through negotiations for lower COGS and trade terms, and drive category innovation through better supplier collaboration.
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.
Explore and model the viability of transformation plans like ‘own label’ development in detail, with custom category and market intelligence reports.
With Merchandising Analytics from The Smart Cube, you can:
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:
We use a collaborative discovery approach to understand your needs and business priorities, and map out the data sources.
We create a prototype solution as a proof of concept, helping you rapidly see value from the project.
We leverage feedback and deploy adaptive agile methodologies to scale the prototype into a full solution.
Your solution evolves as we learn more about your changing demands – covering new categories, locations or storefronts.
Predictive and prescriptive analytics take your solution to the next level, enabling you to take a proactive and interconnected approach to merchandising.
When you choose Merchandising Analytics from The Smart Cube, you always get:
A solution tailored to your needs: We work with you to design and deploy a bespoke solution around your goals, data sources, technology infrastructure and team – delivering outputs tailored to your exact needs.
A rich ecosystem of technology platforms and data sources: We bring together industry-leading tools and technologies, flexibly adapted to your ecosystem, and a unique portfolio of expertly-curated data sources, to provide deep insights into all aspects of retail operations.
Proven commercial and operational value: Retail customers who use our Merchandising Analytics solution realise at least 15x ROI and gain significant margin improvement.
Skills across the analytics value chain: Our capabilities span the analytics value chain – covering data consolidation and integration, reporting and visualisation, predictive and prescriptive modelling, and deep learning.
Relevant advice and recommendations: When you need expert support, our specialist team will be there to provide bespoke category insights, and work with your teams to help develop capabilities as required.
Accelerated delivery: We use pre-built assets, frameworks, data connectors and a library of reusable mathematical models to deliver insights at an accelerated pace.
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.
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.
The results helped the client to better manage the SKU assortment in every store, thus visualising savings of $7 million by eliminating stockout scenarios.
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.
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.
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.
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.
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.
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.