Product Intelligence for CPG & Retail

Differentiated attributes. Differentiated opportunities.

The pack, the listing, the reviews. Every product in your category, described the same way.

An animated example. A fictional product, Kestrel Kitchen chili lime tortilla chips, is described in eight places: two retailer listings, a raw retailer title, a product description, a listing path, a distributor item, a review and a nutrition panel. The hierarchy says where it sits. Its retailer title yields 5 attributes. The full set holds 13: seven Core attributes, four Contextual from the description and reviews, and two Custom defined with you.

Kestrel Kitchen is a fictional brand.

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Where the opportunity shows up

You cannot size what you cannot describe.

Once every product carries the same attributes, the same sales answer three different questions. Nothing new was measured.

The same sales, cut by attribute instead of by brand.

Values are illustrative. Bubble size is dollar sales.

The same sales, by attribute
AttributeDollar sales

Watch one product gather everything said about it.

The pack, the listing and the reviews each add something different, and they keep adding. What the market says becomes an attribute, and an attribute is something you can size.

What is this product?

Harmonya

A taxonomy stops where the interesting questions start.

Category, sub-category, segment, brand. That schema was built for reporting, and it has no room for how a product tastes, who buys it or what it gets used for.

What it reports

The taxonomy

CategoryBeverages
Sub-categorySparkling water
SegmentFlavored
BrandNorthbank
Pack typeSingle bottle
SKUBlood Orange, 12 fl oz

Six levels, and none of them describe the product.

What it is

The same product, described

Corewhat the product is
Northbank Beverage Co.Sparkling water 12 fl ozPET bottle Single serveCarbonated water from the pack and the listing
Contextualwhat the market says about it
Not too sweetLight and crisp Afternoon pick-me-upGood as a mixer Everyday sipping from listings and reviews
Customdefined with you
Zero-sugar seekersBetter-for-you your definitions, applied the same way every run

A product is described in more than one format.

Some of it is structured data from the pack and the listing. The rest is the wild: what shoppers wrote, in their own words, after they bought it.

The pack

Manufacturer and brand, category, pack type and size, flavor and form, and what the label itself states.

The listing

How the product is titled, described and merchandised across the retailer sites we read, which is rarely how the manufacturer describes it.

The reviews

What people say about living with it: the benefit they got, the occasion they bought it for, how it tastes and who it turned out to be for.

  1. AcquireRead the pack, the listing and the reviews.
  2. HarmonizeMatch the same product across every source.
  3. ApplyThe same attribute model, the same way every run.
  4. VerifyCheck the result before it ships.
  5. MaintainRefresh on a schedule agreed with you.

Custom attributes do not come from any of these three: they are the ones you define, applied to your catalog the same way every run.

One product. Three ways to put its attributes to work.

Everything here runs on the same attributes, resolved once per UPC. A number in one view reconciles with a number in another because they are reading the same product.

Coverage is measured against your product list, not ours. We attribute the items you ask about, and we tell you where coverage is thin.

Insights Platform

Ask a question in plain language and get four reads on the same product set: what is growing, who is winning, where demand is going unmet, and what shoppers say.

Explore the Insights Platform
Explore the Insights Platform

Attribute Feeds

The same attributes delivered into your stack as a flat file, an API or a warehouse share, so every team and system is working from one vocabulary.

Explore Attribute Feeds
Explore Attribute Feeds

Harmonya MCP

Point Copilot, ChatGPT, Gemini or Claude at Harmonya and get answers built on the attributes, the reviews behind them and the sales data you already share with us. Coming soon.

See what you can ask
See what you can ask

What teams use it for.

The same attributes, pointed at the decisions your team already owns.

Learn About Product Intelligence
Learn About Product Intelligence

Shopper
Insights

Understand the product attributes driving consumer choice and track competitive shifts at the theme level.

See Shopper Insights Use Cases
See Shopper Insights Use Cases

Assortment Optimization

Decide which items to expand, delist, or localize based on the demand themes driving your category.

See Assortment Use Cases
See Assortment Use Cases

Brand Messaging

Shape packaging, PDP copy, and campaigns using the language shoppers use.

See Brand Messaging Use Cases
See Brand Messaging Use Cases

Promotion Planning

Decide which products to promote, where to activate, and when to spend based on real shopper signals.                

See Promotions Use Cases
See Promotions Use Cases

Retail Media Optimization

Target retail media with attributes and themes built on real shopper language, so spend reaches the right products and audiences.

See Retail Media Use Cases
See Retail Media Use Cases

Product Dictionary

Give every team one consistent reference for product attributes and language, across systems and categories.

See Product Dictionary Use Cases
See Product Dictionary Use Cases

More on each part.

What it carries, how it reaches you, and what it gets used for.

The three layers

What a product carries, and where each part comes from.

How you take delivery

The same attributes, in whatever form your team works in.

Getting the data right

What has to happen before any of it can be trusted.

What our customers are saying

“The relationship between Coca-Cola and Harmonya has truly felt like a partnership. We treat them as an extension of our team.”

Rylee Rogers

Fmr. Category Sales Advisor

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View Full Story

“Before Harmonya, we couldn’t track competitor innovations online effectively. Now we can see how fast they’re scaling, just like we do in brick and mortar.”

Michael Mackezyk

Senior Manager, Data Capabilities

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View Full Story

“Harmonya enables us to instantly analyze consumer reviews and sentiment to understand which ingredients matter most to shoppers, giving a new perspective on shopper priorities.”

Byron Ransom

Marketing Director - Positive Choice Brands Insight & Strategy

See the Insights Platform
See the Insights Platform

"Harmonya enables us to efficiently uncover deeper insights into consumer sentiment and product ingredient preferences, allowing us to identify actionable opportunities to meet shopper needs and enhance category shopability"

Kristina Foreman

Category Analyst

View Case Studies
View Case Studies

"Harmonya is elevating and enhancing the way we analyze and tell stories with data. The platform enables us to uncover deeper insights that have measurable impact. The team is collaborative, innovative, and truly invested in our success!"

Savita Kharbas

Senior Director of Category and Consumer Insights

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View Case Studies

“With Harmonya’s review data, we can quantify what customers are saying and compare which products meet their needs best—not based on what we say, but on what they say.”

Rylee Rogers

Fmr. Category Sales Advisor

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View Full Story

"Working with Harmonya has been a game-changer – keeping us deeply engaged through new product releases while empowering us to turn complex data into clear, actionable insights."

Wendy Fan

Commercial Strategy Manager

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View Case Studies

“What Harmonya came up with was an AI-powered solution that helped us match 2,000 missing items. That gave us visibility into $1.7 billion in annual sales we were previously blind to.”

Michael Mackezyk

Senior Manager, Data Capabilities

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View Full Story

"The Harmonya team has played a vital role in finding insights on texture, flavor, and nutritional content across our competitive set, identifying innovation whitespace, and sparking additional conversations as we develop concepts for our brands."

Bailey Harrison

Senior Associate Brand Manager

View Case Studies
View Case Studies

See your category, described.

Go from generic product data to decisions you can defend. See how we build the attributes and put them where your teams already work.