Accelerating growth through a modern Product Information Management strategy
How Daikin unified enterprise product information across multiple acquisitions, reduced acquisition onboarding from approximately nine months to just twelve days, and built a scalable foundation for digital commerce with Convergence PIM.
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Customer Overview
A growing HVAC leader built through acquisition
Much of that scale has come through acquisition. Each new brand brought a valuable product portfolio, and with it a separate way of describing products: different taxonomies, different attribute names, different units of measure and overlapping catalogs.
To keep growing without slowing down, Daikin needed a product information foundation that could absorb an acquisition's data quickly, standardize it against an HVAC-specific model, and publish it confidently to digital and dealer channels.
- HVAC and refrigeration equipment
- Distributor and dealer channels
- Multi-brand product portfolio
Every acquisition restarted the data problem
Onboarding a newly acquired catalog was a manual, months-long effort before a single product could be published with confidence.
Multiple product taxonomies
Every acquired brand arrived with its own classification model.
Different attribute models
The same specification was captured differently across brands.
Duplicate product records
Overlapping catalogs created thousands of near-identical items.
Difficulty enforcing standards
Without shared rules, data standards drifted brand by brand.
Poor product data visibility
No single view of what products existed across the portfolio.
Slow acquisition onboarding
Bringing an acquisition's data into the catalog took months.
Legacy PIM limitations
Older tooling could not scale to HVAC-specific data models.
Poor ecommerce navigation
Shoppers could not browse or filter by meaningful attributes.
Limited data quality measurement
There was no reliable way to score completeness or accuracy.
The downstream cost of fragmented product data
When acquisition data takes months to standardize, the business case for the acquisition waits with it.
Convergence PIM built around HVAC product data
Convergence Data combined an HVAC industry data model, AI-assisted match and merge, enrichment and relationship data into a repeatable onboarding process for every acquisition.
HVAC Industry Data Model
Convergence Data applied a purpose-built HVAC data model so every brand, unit and component is classified against the same industry taxonomy from day one.
- Standardized HVAC taxonomy
- Consistent attribute definitions
- Reusable across acquired brands
AI-Powered Acquisition Match & Merge
AI-assisted match and merge compares incoming catalogs against the master record set, eliminating duplicates and standardizing attributes before anything enters the PIM. Acquisition onboarding fell from roughly nine months to just twelve days.
- Automated product matching
- Duplicate elimination
- Attribute standardization and category mapping
- Supplier data consolidation
- Onboarding cut from ~9 months to ~12 days
Product Data Enrichment
The Convergence Data Factory attributes, normalizes and validates product information at scale. Richer, comparable specifications gave customers confidence and made products far easier to discover.
- Data Factory attribution at scale
- Data and unit-of-measure normalization
- Validation rules and data quality checks
- Missing information analysis
Product Relationships
Structured relationships connect units to replacement parts, compatible accessories, recommended upgrades, documentation and digital assets, turning clean data into commercial opportunity.
- Replacement parts and compatible accessories
- Recommended upgrades and complementary products
- Documentation and digital assets
- Stronger cross-sell, up-sell and average order value
- Higher customer confidence and fewer returns
Acquisition onboarding reduced from nine months to approximately 12 days.
From challenge to business outcome
Built for manufacturers, tuned for HVAC
HVAC Industry Data Model
A taxonomy and attribute library built specifically for heating, cooling and air handling products.
Automated Match & Merge
AI-assisted comparison collapses duplicate records from newly acquired catalogs.
Product Data Enrichment
Missing specifications are filled at scale so listings are complete and comparable.
Enterprise Data Governance
Ownership, workflow and validation rules keep quality high as volume grows.
Product Relationships
Accessories, parts and compatibility structured to drive commercial outcomes.
Future-Ready Platform
A governed foundation ready for new channels, new brands and AI use cases.
A repeatable path from acquisition to revenue
With a governed HVAC data model in place, Daikin turned product data from an acquisition bottleneck into a competitive advantage.
Nine months reduced to 12 days
Acquisition data onboarding moved from a multi-quarter project to under two weeks.
Standardized product data
Every brand now speaks the same product data language.
Better customer experience
Complete, consistent listings make products easier to find and compare.
Scalable acquisition strategy
New acquisitions can be absorbed without rebuilding the data model.
Improved digital commerce
Governed data feeds ecommerce, distributors and dealer channels.
"Acquisitions only create value when the product data behind them is standardized, governed and ready to sell "
— Convergence Data
Ready to Modernize Your Product Information?
Whether you are absorbing an acquisition or standardizing an existing catalog, a governed PIM foundation shortens the path from product data to revenue.