The demand under each item on the plan.
The attributes an item carries. Where sales behind those attributes went over the past year. The accounts and price tiers you plan in.
A calendar backed by demand that is still growing.
Promotion planning
Two items, same lift last year
Illustrative. Invented items, invented read.
Item A carries
Demand on those attributes: still climbing
Item B carries
Demand on those attributes: falling away
The lift file holds neither read.
What historical lift does not carry.
Promotion plans are built from last year's lift. Lift is an account of which items responded at a given depth in a given retailer.
It holds no field for the attribute that drew the response, and none for where demand on that attribute has moved since. A plan built on lift alone cannot separate an item that performed last year from one whose demand is still climbing.
Where it comes from
A year of sales, held against the attributes each item carries.
A year of item-level sales is held against the attributes each item carries, with those attributes read from millions of retailer listings and the reviews beside them.
Refreshed on a schedule agreed with you, and applied the same way to every product in the category.
What the product carries.
Attributes
What the item carries past its brand and its price. High protein, single serve.
Direction
How sales behind each of those attributes moved, item by item.
Structures you define
The groupings your plan is already written in. Price tiers, pack roles.
What else the attributes answer.
Whether demand behind the attribute you are promoting is still rising.
Category trends and momentum
Whether demand you have never promoted against would carry the spend.
Demand and whitespace sizing
Which items qualify for an occasion before you build a promotion around it.
Demand spaces and thresholds
Where the item you are promoting sits against the rest of its price tier.
Competitive benchmarking
A global food and beverage manufacturer tracked attribute-level sales across a protein category at a national retailer. Sales on Low Sugar grew 13.4% year over year and sales on No Artificial Colors 12.7%, and the prior year's lift file held neither figure.
The attributes behind the plan.
Contextual attributes. Where the benefit and occasion attributes come from.
Category trends and momentum. Which of those attributes gained over the past year.
Demand spaces and thresholds. The occasion a promotion gets built against.
Custom attributes. Price tiers and pack roles, written to your own plan.
Three ways to take delivery.
A feed into your own systems
Core, Contextual and Custom attributes for the categories you promote in, on a schedule agreed with you.
Insights Platform
The same attributes, open beside the calendar you are building.
Work our team runs
We take the plan as written and read the demand behind each item on it.
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
Category Sales Advisor
“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
"Harmonya is becoming a powerful unlock across our organization—it's being explored as a cross-functional innovation, brand strategy, and product development tool."
TJ Hanel
Director Omni-Commerce Retail Media Strategy
.svg)
"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
.svg)
"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
“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
Category Sales Advisor
.svg)
"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
“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
"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
See What Shopper-Led
Product Data Can Do
Go from messy, generic product data to precise, shopper-led decisions. Learn how Harmonya structures, enriches, and analyzes data to drive action.
