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The Merchandising Edge
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Get a demoSandra has always been drawn to the fashion industry. She views fashion as a personal form of art that reflects each individual’s personality and unique tastes.
Sandra loves her job as a busy online merchandiser for Bluebird, a boutique fashion brand. She has products to promote, inventory to clear out, and KPIs to meet, but little downtime during the day.
Bluebird has grown considerably over the past year, increasing its product offering and opening additional brick and mortar outlets. As the company scales, it's imperative that Sandra have the right tools and resources to merchandise efficiently.
Rachel loves fashion. She habitually scrolls through online catalogs from her favorite brands, mentally piecing together new looks. She’s recently discovered the Bluebird clothing line and is eagerly anticipating its ’26 Summer / Spring Signature Collection.
Though Rachel loves clothes, she wishes it was easier to find styles that match her aesthetic without having to browse through endless pages of clothing she’d never consider wearing.
Rachel is Sandra’s ideal customer. She lives and breathes fashion and she’s interested in the Bluebird brand. Sandra wants to build engaging search experiences and seamless shopping journeys tailored towards fashionistas like Rachel.
To automate and optimize the shopping experience, Sandra needs tools that are easy to set up, with intuitive dashboards that don’t require coding. With AI now available for the fashion retail industry, these tools are at her fingertips.
AI-powered merchandising technology makes it simple for Sandra to gather data about Rachel’s shopping affinities and deliver what she wants. Machine learning algorithms automatically surface styles, promos, and cross-sells that capture Rachel’s attention. With AI, Sandra spends less time manually pinning items and configuring relevance rules and spends more time designing campaigns that showcase Bluebird’s visual brand.
Machine learning algorithms automatically surface styles, promos, and cross-sell.
With AI integrated into the search platform, Algolia’s fashion solution is a suite of user-friendly ecommerce tools developed specifically for fashion retail merchandising. They let Sandra:
The solution transforms how products are discovered and sold online. They help Sandra scale effectively while increasing conversions, average order values, and time spent on site.
In fashion, you need to stay on top of the latest trends. With Algolia’s intelligent fashion solution, Sandra’s ahead of the curve. The speed and power of AI collects and analyzes comprehensive data and surfaces real-time, interactive collections with relevant suggestions.
AI allows Sandra to provide an online experience that gives shoppers the option to choose how they want to shop. With Algolia’s fashion solution, Sandra works faster and smarter.
Rachel has a better online shopping experience, and Bluebird’s brand recognition continues to grow.
Sandra just got out of a progress meeting and is feeling the pressure. She needs to put together the online ’26 Spring / Summer Signature Collection before it launches later that day.
Supply chain delays and photo reshoots have put Sandra behind schedule. She wasn’t sure which items would be in stock on time. With a press release scheduled to go out, Sandra has just a few hours to finalize the collection.
Sandra’s superpower is Algolia’s fashion solution. With the Collections tool’s easy-to-use dashboards, she can quickly create the ’26 Spring / Summer Signature Collection that shows what’s available today. Next week, if the “floral swing dress” arrives from the supplier, the collection will automatically refresh once Sandra adds it to the “summer dresses” category.
When an item sells out, it’s automatically removed from the listing and no longer appears within the collection. Sandra doesn’t need to remove items manually, making liquidating Bluebird stock from the fall / winter season much easier.
Algolia’s fashion solution has algorithmic logic built in. Sandra doesn’t need to do anything technical, like clean her data or train the system on Bluebird’s products. The fashion solution does that for her directly in Algolia’s Merchandising Studio.
Making a new collection is now as simple as creating a custom category page. Sandra can either handpick existing items from the index or upload a new file of product object IDs. She then defines attribute-based conditions that dynamically put a collection
together, such as Bluebird’s ‘26 Spring / Summer Signature Collection, on sale, or bestsellers. Then she can leverage those collections to create landing pages.
What used to take Sandra hours, now takes minutes. She creates the new collection and lets the marketing team know that the site is ready to go. With time to spare, Sandra can shift gears, focus on incoming traffic, and strategize on campaigns.
Behind the scenes, Algolia’s transform engine tracks sales and browsing activity, including conversion rates, sales volumes, average basket size, timing of sales, and customer satisfaction metrics. Data analytics help Sandra generate bestsellers reports, create trend forecasts, and make stocking decisions informed by seasonal buying patterns.
Smart Groups add even more power to Collections. While Collections are thematic assortments of different products such as bestsellers or the ’26 Spring / Summer Signature Collection, Smart Groups let you highlight specific items within these groups. Instead of manually picking and pinning items, Smart Groups curates results dynamically.
With a comprehensive ‘26 Spring / Summer Signature Dresses Collection created, Sandra uses the Smart Groups feature to highlight “new arrivals” within the larger collection based on a query. Now the “floral swing dress” and other new arrivals are inserted strategically in the grid among Rachel’s search results for “summer dresses.” This ensures high visibility for key products and increased search accuracy with almost no effort. Smart Groups drive sales where Sandra wants them – without the fuss of manual pinning or keeping track of items in spreadsheets.
With summer cocktail party season in full swing, Sandra knows fashion-forward customers like Rachel want on-trend party dresses. With Smart Groups, Sandra automatically sets the latest new arrivals that are party dresses to appear in the search results anytime a customer adds ‘“dress” to their query.
She also has full control over where they are pinned in the grid. She can place it right at the top or after the first few organic results. Either way, the earmarked items appear naturally in Rachel’s results list.
Like Collections, Smart Groups update dynamically as new items are received from suppliers and older products sell out. By eliminating manual intervention, the solution saves Sandra time and money.
Optimizing results with AI increases conversions and delivers ROI for Bluebird. The themed groupings keep Sandra’s customers engaged. Discovery is designed, but stays fresh, interesting, and serendipitous. When Rachel searches “summer dresses,” she gets useful and relevant results, but finds exciting new arrivals she might not have expected without the helpful push from Algolia’s Smart Groups.
Rachel craves fashion and styling tips. She loves to learn about accessorizing, different fabrics, and seasonal colors. She often taps, scrolls, and reads to ensure she hasn’t missed an important product detail that might influence her decision such as customer reviews and care instructions.
Sandra knows how important rich content is for customer engagement. It helps drive SEO, deepens the browsing experience, and scores conversions.
A fashion retailer like Bluebird specializing in women’s attire can carry hundreds, if not thousands of items – and each of these needs a written description. As catalogs change with the seasons, new products are added and descriptive text needs to be updated. Long pants get shorter. Short skirts get longer. And product listings and category overviews need to be updated accordingly.
Generative Artificial Intelligence (Gen AI) is revolutionizing content generation for merchandisers by creating rich descriptive and explanatory content with zero effort.
Periodically, Sandra gets an updated inventory list. In the past, she would either contract with a fashion writer or compose each product description herself.
Using pre-built helper functions, Sandra can connect popular Gen AI clients to the Algolia platform. With integrated AI, Algolia’s Data Transformations can enhance data before it’s indexed.
Sandra now has a Gen AI fashion solution to write the descriptions for her. When she uploads the new inventory list, the AI uses the manufacturer’s product data to automatically write detailed descriptions for each item.
Sandra can then review the product descriptions and make edits if necessary. She saves time that she would usually spend writing this copy from scratch. On the website, Rachel sees coherent and well-crafted product descriptions that assist her buying decision.
As a boutique brand, Bluebird is outpacing its staffing resources. With an overwhelmed marketing department that lacks a dedicated fashion writer, it’s up to Sandra to deliver value-added content like shopping guides.
Sandra may not have additional budget or writing resources. But she has a secret weapon: Algolia’s fashion solution.
Algolia’s Shopping Guides leverages Gen AI capability to pepper the shopping journey with even more kinds of information.
With Algolia’s Gen AI, Sandra can not only quickly create product descriptions, but also use Shopping Guides to generate entire articles with the AI doing the background research and writing. These articles educate shoppers, turning them into brand experts and advocates. Shopping Guides can write informational shopping guides on fabrics, seasonal trends, and colors, category guides that break down different dress styles, or product comparisons.
To add context to Bluebird’s new dress options, Sandra uses the Shopping Guides tool to spin up an article on “Matching the right shoes to this summer’s hottest dress styles” and another on “Expert care tips for linen dresses.”
These AI-generated guides broaden Rachel’s perspective on Bluebird’s products and fashion in general, building deeper brand connections that encourage return visits and more sales. They also boost SEO for the page.
As Gen AI evolves and improves, merchandisers are constantly finding new ways to harness its power for added customization. With a few lessons on advanced prompt engineering, Sandra can cue her prompts to generate text to any length and emulate any voice (e.g., a distinguished fashion expert, a trendy stylist, or an up-and-coming influencer).
Using Gen AI, Sandra not only fills the website with instructive, engagement-boosting content, she does it in record time.
Though Rachel enjoys online shopping, she especially loves shopping with friends who make suggestions, direct her towards new styles, and weigh in on new looks. Even better is the luxurious experience that only an in-store personal shopping assistant can provide.
Having a personal shopping assistant used to be a bespoke engagement only offered by luxury brands. With Algolia’s fashion solution, Sandra helps Bluebird deliver that hands-on VIP experience on every visit.
Sandra integrates the AI Assistant into Algolia’s front end. It uses Gen AI to power a conversational and interactive search journey that feels like being helped by a friendly professional fashion advisor.
The search experience starts at the toolbar with AI search that understands queries in natural language.
When Rachel types “I need a dress for a wedding in Spain in June” the system surfaces relevant results considering spring weather in Iberia. Sandra’s AI Assistant is ready to further help if Rachel needs it. She can click the AI Assistant icon to get advice about the search results or ask questions to deepen or expand her search.
Like a trusted shopping pal, the AI Assistant learns Rachel’s tastes and filters the next set of search results and prompts to match her criteria. The friendly chat between the AI Assistant and Rachel is faster and more personalized than traditional browsing. Thanks to Gen AI, these aren’t FAQs, they’re conversations. The back-and-forth dialogue delivers an exclusive experience that deepens Rachel’s connection with Bluebird.
If Rachel is shown pastel-colored dresses for Spain in June, but doesn’t like them, she can redirect the AI Assistant by entering a new prompt. “Show me some more colorful options.” The AI Assistant refines the search further and provides new impromptu suggestions to help Rachel find exactly what she’s looking for.
AI Assistant delivers:
Like most fashionistas, Rachel loves fashion shows, magazines, and photography. While flipping through pages and scrolling through images, Rachel makes notes to herself – yes, yes, no, LOVE, yes, maybe, ADORE, not for me....
Sandra provides that visual experience with the fashion solution Shop With Your Eyes. The AI toolkit goes beyond keywords and category headings to let customers search and select clothes by look, not description. Adding visual sensibility to text-based discovery enriches the browse experience for fashion retail.
Shopping with text is a reading experience. When customers can shop with their eyes, every channel – the app, the kiosk, or the website – becomes a runway experience.
Shop With Your Eyes enables visual browsing to match and compose looks. When Sandra adds image capability to search, she treats Rachel to a novel search experience she’s never had online. It’s like chatting with AI for text, but using pictures as prompts.
AI is changing how people shop. Like many fashion lovers, Rachel often pins photos of some of her favorite looks that she finds on social media. With AI image processing, she can now upload those images to locate matching products. It’s the new way to shop for clothes.
One of Rachel’s pictures shows her friend at a recent birthday party in a colorful summer dress. Rachel’s hoping to find something similar, but with a Bluebird flare.
By just uploading a photo of her friend in the summer dress, the AI can surface product recommendations associated with features
from that image. It also produces text replies to help Rachel refine her search, such as “You might want to explore casual dresses, matching shoes, or similar colors.”
Rachel can click an AI-generated prompt to keep looking or start exploring the similar-looking product suggestions until she finds an eye-catching dress in a color she likes.
In fashion, visualization is a sure-fire way to keep customers engaged and boost conversions. For Sandra, a picture’s not worth a thousand words, it’s worth a thousand sales. Orienting search around visual data quickly delivers the product that Rachel wants, building a stronger incentive to buy.
With AI analyzing the image and making suggestions, product recommendations are targeted and effortless. Everything happens fast and intuitively, providing a unique shopping experience that is custom-built for the fast-paced, image-forward fashion world.
Harvard Business School analyzed 500,000+ online purchases conducted using image analysis with AI and found they led to:
Rachel loves browsing and discovering products online, but it’s not the same as the in-store shopping experience. The physical sensation of fabric beneath her fingertips, matching colors to skin tones, or trying things on in person is incomparable. That’s why Rachel likes to buy online for pickup in-store (BOPIS).
While Sandra’s focus is primarily on ecommerce, inventory moves through many channels. To make sure every customer’s needs are met, Sandra needs sophisticated tools to blend the digital and physical shopping realms.
Bluebird has recently made a major investment in brick and mortar stores. They’ve opened several boutiques in high-traffic shopping districts. They not only want online shopping to merge seamlessly with the in-store experience, they want to encourage in-person visits to generate more sales.
To support the effort, Sandra uses BOPIS to send customers to physical stores where they’re likely to buy additional items. To help, store associates use apps with AI-powered personalization features to know customers better and provide tailored recommendations.
The Shops Deliver Experience fashion solution creates that vital bridge between the online and offline shopping experience. With a simple integration, Sandra gives customers real-time information about product availability with automated inventory location indexing.
On Rachel’s end, local availability weighs heavily in her purchasing decision.
With the summer dress in her cart, Rachel wants to know whether it’s available in-store to try on and pick-up today. To check whether an item is in stock, Shops Deliver Experience retrieves the “stores” array of the product, then checks to see if it’s at Rachel’s local store.
If an item isn’t available nearby, delivery options and timelines are provided instead, helping Sandra close the browse-to-buy loop and make the sale.
Shops Deliver Experience also makes it easy for Rachel to buy online and return in store (BORIS). With a simple return process, Rachel is more apt to take risks and make purchases outside her comfort zone.
Treated to an elevated in-store shopping experience, Rachel feels like the star of her own runway show. And once she sees, matches, and tries on new fashions in person, Rachel purchases more than just the summer dress she came in for.
Get more conversions by bridging channels with fashion solutions.
Fashion is a competitive and fast-moving marketplace. Algolia's intelligent fashion solution keeps Sandra ahead of the pack. She saves time, gets to market faster, and enjoys more flexibility and control over her merchandising than her competitors.
Merchandisers have heavy workloads and demanding customers. Algolia has worked hand-in-hand with search builder teams including merchandisers, business leaders, and devs across the fashion industry to develop our intelligent fashion solution. The suite of tools optimizes efficiency and drives sales while saving time and resources.
Algolia’s intelligent fashion solution includes:
Algolia is a leading provider of AI search solutions, serving over 18,000 businesses and 500,000 developers globally. Renowned for its user-friendly API-first platform and the fastest AI search technology, Algolia is the largest hosted search engine, trusted by businesses and developers for 1.75 trillion searches per year. Backed by a decade of innovation, expertise, and growth, Algolia continuously redefines the search landscape with its commitment to user-friendly solutions, significant scalability, and unmatched speed.
Already trusted by 75% of the world’s top fashion houses, we’re setting the new standard for AI-native, search-driven commerce.