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In-home usage data and insight requirements for AHDB
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Descriptions
This tender opportunity is for the provision of in-home usage data and insight relating to eating habits within the home. The Retail and Consumer Insight (RCI) team offers independent market analysis using AHDB and third-party data. Their goal is to explain shifts in consumer attitudes and behaviour, helping levy payers understand the market and make informed decisions. AHDB currently uses in-home consumption data currently contracted from Worldpanel by Numerator. How we use in-home data: The in-home usage data provides greater context into the types of meals eaten in the home but also what types of meal our categories are featuring in. The usage data has been used very heavily with our Market Development team to understand the current consumption profile Insight requirement: Track known behaviour of MFP and Dairy products in the home, looking at consumption trends and delivery of insight to understand actual behaviour and motivations behind these. Category coverage: Details below show the category items that included in AHDB’s analysis of what it eaten in the home. It shows the set of comparison products that falls within the current analysis. Meat/Fish/Poultry (MFP): Fresh Red Meat, Fresh Beef, Fresh Lamb, Fresh Pork, Frozen Beef, Frozen Lamb, Frozen Pork, Fresh Poultry (breakout for Chicken-Turkey), Fish, Frozen Poultry, Sliced Cooked Meats, Sausages, Bacon, Fresh Burgers & Grills, Frozen Burgers & Grills, Ready To Cook, Ready Meals, Fresh Pulled Pork and BBQ Further cuts breakdown for primary Beef, Lamb and Pork: Roasting (breakout for leg/shoulder for Lamb & loin / belly for pork) , Frying/Grilling, Mince, Chops, Bacon (Chops/Joints/Rashers) Dairy Category coverage: Cheese, Milk , Butter, spreads and margarine (BSM), Yoghurt and Cream. Dairy alternatives Filters: Cheese filters on: Extra Mature, Mature, Medium, Mild, Vintage BSM filters: Butter and Margarine, then splits on Block, spreadable Category Measures: A full range of measures will be required including but not limited to: • Number of Occasions • Demographics • Geographic’s • Cooking method • Time of day • Meal type • Details of foods eaten combinations • Who / Number Present • Ability to track year-on-year trends Category-meal drivers, e.g. Occasion motivators, Cooking method, Preparation time, complementary food, dish consumed in the home.
Timeline
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Tender Regions
CPV Codes
72316000 - Data analysis services
Keywords
data modeling
data mining
KPI evaluation
regression forecasting
performance benchmarking
segmentation analysis
statistical inference
multivariate analysis
correlation studies
exploratory data analysis
Tender Lot Details & Award Criteria
1 Tender Lots
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