Company: Constructor, San Francisco, CA
Nomination Submitted by: Three Rings Inc.
Company Description: Constructor provides an AI-based product search and discovery platform, tailor-made for ecommerce. Constructor delivers personalization across the buyer journey: in search results, browse experiences, product recommendations and more. Optimizing for metrics like revenue, conversions and profit, Constructor generates $10M+ lifts for brands such as American Eagle, Birkenstock, Petco and Sephora.
Nomination Category: New Product & Service Categories - Business Technology
Nomination Sub Category: Electronic Commerce Solution
 Nomination Title: Constructor's AI Shopping Assistant
- Which will you submit for your nomination in this category, a video of up to five (5) minutes in length about the nominated new or new-version product or service, OR written answers to the questions for this category? (Choose one):
Written answers to the questions
- If you are submitting a video of up to five (5) minutes in length, provide the URL of the nominated video here, OR attach it to your entry via the "Add Attachments, Videos, or Links to This Entry" link above, through which you may also upload a copy of your video.
N/A
- If you are providing written answers for your submission, you must provide an answer to this first question: If this is a brand-new product, state the date on which it was released. If this is a new version of an existing product, state the date on which the update was released:
Brand new product: May 2023
- If you are providing written answers for your submission, you must provide an answer to this second question: Describe the features, functions, and benefits of the nominated product or service (up to 350 words):
Total 348 words used.
When online shoppers know exactly what they want, they’re typically well-served by existing forms of product discovery: navigating to that item on an ecommerce site or using the site’s search bar to search for it (in terse terms, kind of like a caveperson… gotta make sure the search engine understands!).
However, there are times when shoppers DON’T know the best item(s) to fulfill their need: They may be looking for supplies for a new hobby, the perfect birthday gift, or meals that’ll appeal to grownups and vegetable-averse kids alike. In such cases, it helps to fully explain themselves (not like a caveperson—in complete sentences!) and get expert suggestions. In a brick-and-mortar store, these suggestions would come from a trusted associate.
Now there’s an equivalent online: thanks to Constructor’s AI Shopping Assistant (ASA), a [REDACTED FOR PUBLICATION] product discovery tool supporting conversational language queries. Easily integrated into online search, ASA:
- Combines generative AI with Constructor’s personalization technology and ability to optimize for KPIs defined by each retailer (revenue, conversions, inventory-balancing, etc.).
- Enables shoppers to explain themselves in long-form/natural language—or have a conversation—and get results personalized to their preferences, history and intent, and reflecting real-time inventory.
- Is used by ecommerce companies in grocery, apparel and general retail.
- Can be flexibly implemented on ecommerce sites: within the search bar or as an AI search toggle [REDACTED FOR PUBLICATION] .
- Recommends products/content across categories.
- Feeds data to (and pulls from) Constructor’s holistic product discovery platform—which shoppers interact with hundreds of millions of times daily. Constructor learns from every query/interaction to personalize across search, browse, AI Shopping Assistant and more.
ASA can address queries such as: “I’m going camping with my pre-teens for the first time in the White Mountains; what do we need?” and “What can I wear to a formal wedding in the Caribbean in August?” Recommendations make sense and map to the shopper’s preferred brands, price points, styles, etc.
For shoppers, ASA instills confidence in purchase decisions and expedites the time from goal to purchase. Ecommerce companies keep shoppers on-site for research (not losing them to Google or Amazon) and drive engagement and conversions.
- If you are providing written answers for your submission, you must provide an answer to this third question: Outline the market performance, critical reception, and customer satisfaction with the product or service to date. State monetary or unit sales figures to date, if possible, and how they compare to expectations or past performance. Provide links to laudatory product or service reviews. Include some customer testimonials, if applicable (up to 350 words):
Total 200 words used.
AI Shopping Assistant is being used by retailers around the world. One salient example is in the grocery sector: A large US-based grocery chain uses the technology to help shoppers find recipes and procure ingredients. When a shopper searches for a recipe on the site (e.g., “I want to make a lemon meringue pie”), ASA:
- Automatically generates the recipe
- Generates the recipe with ingredients the grocer has in-stock
- Personalizes the ingredients to the shopper at hand (so if the recipe calls for milk, and the shopper tends to buy organic, then options for organic milk are shown)
- Makes it easy to add all ingredients to cart, directly from the recipe page
As a result, this grocery retailer has seen a 3.7% increase in search conversions.
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- You have the option to answer this final question: Reference any attachments of supporting materials throughout this nomination and how they provide evidence of the claims you have made in this nomination (up to 250 words):
Total 197 words used.
The supporting materials included (“Add Attachments, Videos or Links to This Entry” section) provide further context on AI Shopping Assistant.
- Constructor materials (Please see the product page and press release we linked to, along with the embedded video). As you’ll see, the ASA video shows sample queries that ASA can address and how recommendations get displayed.
- Constructor blog (“Smarter Shopping Journeys…”). As you’ll see from the text, while ASA is primarily used to monetize conversational commerce in search, there are other use cases as well: including enabling more intelligent autocomplete and generating personalized recommendations within on-site content (e.g., with ASA “reading” your ecommerce site’s blog article and generating clickable images of personalized and contextual product recommendations within the text to complement it).
- Samples of media coverage (Please see PYMNTS, destinationCRM and Retail Today links included). These provide further use cases and are a testament to the product news being newsworthy. [REDACTED FOR PUBLICATION] Analyst firm Gartner also called out Constructor’s ASA as a salient “industry initiative” of incorporating generative AI into digital commerce search and product discovery.
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