Merchandising has always been part art, part science. But over the past decade, the balance has shifted dramatically from gut-based decisions to data-driven, AI-powered precision. As retail conditions grow more complex and customer expectations continue to rise, the ability to harness data for smarter, faster merchandising decisions is quickly becoming a competitive differentiator.
In this post, we’ll explore how merchandising analytics has evolved, including where we’ve come from, where we are now, and where the next five years will take us, through the lenses of data, decision-making, and tools.
10 Years Ago: Manual, Retrospective, Siloed
A decade ago, most retailers operated merchandising processes manually and retrospectively. Data was locked in disconnected systems, and decisions were often based more on instinct than insight.
Data: POS, loyalty, and inventory data were stored in silos and took weeks (or months) to gather and clean. Insights were mostly backward-looking, and access to customer behavior or third-party data was rare.
Decision-Making: Merchandising plans were built on fixed schedules, including seasonal resets, quarterly reviews, annual promotions. Segmentation was simplistic, often limited to geography or store size, with decisions heavily reliant on past experience or vendor-supplied reports.
Tools: Excel ruled the day, along with isolated planogram software and legacy BI systems. Advanced forecasting or modeling was rare and often inaccessible to frontline teams.
Today: Connected, Predictive, Collaborative
Modern merchandising is increasingly data-driven, collaborative, and adaptive. Automated analytics solutions for retail have unlocked new capabilities for analysts and business users alike, reducing friction and accelerating decision-making.
Data: Retailers now integrate data across channels, such as POS, e-commerce, loyalty, and third-party sources. Cloud data lakes and APIs provide near-real-time access, blending structured and unstructured inputs from across the enterprise.
Decision-Making: Teams can now adjust promotions, optimize assortments, and update planograms on the fly. Predictive models support dynamic segmentation based on behavior, preferences, and store-specific context. RGM (Revenue Growth Management) has also become more tightly integrated with merchandising decisions.
Tools: Platforms like Alteryx make self-service analytics and automated workflows accessible across merchandising teams. Machine learning models help forecast demand, analyze market baskets, and quantify promotion lift. Dashboards unify performance KPIs across planning, marketing, and operations.
5 Years from Now: Autonomous, Prescriptive, AI-Augmented
The next evolution of merchandising analytics is already on the horizon. It’s not just about being faster or smarter. It’s about being autonomous, personalized, and truly adaptive.
Data: Data pipelines will pull from in-store sensors, digital journeys, weather, and behavioral signals. Privacy-safe identity resolution will enable deeper customer-level personalization across channels.
Decision-Making: Merchandising will shift from calendar-based cycles to continuous optimization. AI will not just predict, but automatically adjusting promotions, shelf layouts, and product mixes at the store level or even for individual shoppers.
Tools: AI copilots will guide human decision-makers. Simulation environments will enable A/B testing across clusters or geographies. Many traditional dashboards will be replaced by conversational interfaces that surface insight in plain language.
How Alteryx Helps Retailers Thrive in a New Era of Merchandising
As merchandising evolves from manual to autonomous, retailers need a flexible, powerful analytics platform that adapts with them. Gartner says “retailers are looking to implement relevant AI-led merchandising solutions to target customer behavioral segments with meaningful and personalized offers. However, retailers are mired in decade-old manual product-centric hierarchy processes and Microsoft Excel-based solutions that are seriously hampering the necessary shift toward customer-centric merchandising.”
With Alteryx, merchandising teams can tap into a unified platform that blends data, automates workflows, and delivers predictive insights across every merchandising function:
- Market Basket Analysis Made Easy: Alteryx offers drag-and-drop tools to uncover product affinities, frequent purchase patterns, and cross-sell opportunities — no data science degree required. Retailers can identify high-impact bundles, uncover halo effects, and improve category strategies based on real customer behavior.
- Planogram Validation and Optimization: Alteryx allows retailers to ingest complex planogram files (e.g., PSA, PFA formats), parse them into usable tables, and perform advanced analysis on product positioning, facings, and space allocation. Teams can automatically validate execution against shelf standards, flag missing items or overfacings, and compare planogram performance across time, formats, or regions—without relying on expensive third-party tools.
- Assortment Optimization: Alteryx enables dynamic clustering and demand-based segmentation, helping teams tailor product assortments by geography, store type, or shopper behavior. Planners can test scenarios, model SKU rationalization strategies, and align shelf space with high-converting products, driving both efficiency and revenue.
- Promotion Planning and Measurement: Retailers use Alteryx to blend POS, loyalty, and promotional history to measure lift, halo effects, and cannibalization. Machine learning models identify which promotions drive incremental revenue and which underperform, allowing for more effective spend allocation and responsive campaign adjustments.
- Automated Dashboards and Merchandising Reporting: Alteryx powers fully automated dashboards that track KPIs across sales, planogram compliance, promotional effectiveness, and assortment performance. These dashboards refresh with the latest available data, reducing reporting lag and giving teams access to timely, trusted insights, all without manual prep or IT dependency.
The result? Retailers gain faster insights, smarter decisions, and greater agility, all without needing to code, rely on IT, or wait for vendor reports.
Retailers that still rely on static spreadsheets, rigid resets, and fragmented data can no longer keep pace. The shift from manual merchandising to automated and AI-driven strategies is accelerating. Alteryx is helping leading retailers make that leap by empowering teams to unify their data, automate their workflows, and act on insights at the speed of retail.
Curious what merchandising will look like for your business in five years? Contact us to learn more.