Blending syndicated, retailer and internal data into one view
Optia Data combines syndicated market data, retailer data and a business's own internal data into one harmonised, analysis-ready baseline, so teams investigate what changed and why without rebuilding the data first. For Campari UK, Optia kept off-trade weighted distribution and on-trade outlet counts as separate measures, so the dashboard never averages measures that mean different things.
The sources Optia brings together
The data sources Optia works with include NielsenIQ, Kantar and GfK syndicated data, retailer EPOS and sell-out data, and clients' own sales, finance and operational systems.
How Optia handles numbers that never match
Optia's published methods include product and category hierarchy mapping across incompatible source taxonomies, currency and reporting-period normalisation, and reconciliation to dataset totals where source data is masked.
Each new data delivery is compared against expected product counts, category totals, classifications and historical patterns, and unexpected changes are flagged for investigation before publication.
For Arla Foods, masked Swiss brand data was reconciled to dataset totals.
Some measures should not be merged at all. For Campari UK, Optia built the Total Trade model in the reporting layer rather than joining on-trade and off-trade sources directly, because off-trade distribution returns weighted distribution and on-trade returns a physical outlet count. If on-trade and off-trade periods do not match, no Total Trade figure is published.
Optia has paired NielsenIQ point-of-sale retail measurement with NielsenIQ Geomarketing catchment data, holding the national sales read and the local spending-capacity read as two layers joined at category level rather than forcing them into one number.
Samworth Brothers: market, retailer and internal data in one model
For Samworth Brothers, Optia brought five external data sources together with internal category submissions into one model that standardises definitions and calculations across six categories. NielsenIQ EPOS is among the external sources, and the model includes retailer performance.
The Power BI view puts total GB market, category, retailer and competitor performance together, benchmarking the group against 16 strategically relevant competitors. During the transition, users could switch between the new standardised calculations and the previous methodology to build confidence in the new approach.
More examples
For Bacardi, Optia consolidated data from eight areas of the business (CRM, finance, market data, retailer data, distributor reporting, HR, supply chain and forecasting) into one automated reporting model that replaced interlinked spreadsheets.
International Beverage's reporting model is being built to combine market data, internal shipments, distributor depletions, IWSR and Kantar sources that arrive at different frequencies and on different calendars. The work is in progress: it resolves 13-period market calendars against a monthly October financial year, and 156 weeks of history have been loaded, up from 13.
The same approach works outside consumer goods. For Inspired Learning Group, Optia connected five systems (NetSuite finance, iSAMS, Famly, Digistorm admissions and payroll) into one reporting environment across around 25 schools and nurseries.
See also: data preparation and cleansing and total trade for drinks brands.
Frequently asked questions
How do we combine NielsenIQ, Kantar and retailer EPOS data into one view when the numbers never match?
Optia Data maps product and category hierarchies across sources, normalises currencies and reporting periods, and reconciles to dataset totals where data is masked. For Campari UK, Optia built the Total Trade model in the reporting layer so that measures meaning different things are never averaged. For Samworth Brothers, five external data sources and internal category submissions now sit in one model with standard definitions and calculations across six categories.