From US Proxies to Local Market Evidence: How Newly Weds Built Customer Conviction Across Europe

When customers ask what is happening in France, Germany, or the UK, broad European trend reports are rarely enough.

Newly Weds Foods needed a faster way to understand local markets and build recommendations backed by evidence rather than assumptions. Previous data sources often relied on US proxies, while updating presentations across multiple countries required significant manual work.

Using Tastewise, the team combined consumer demand, menu activity, and recipe behavior across European markets into a single intelligence system. Instead of spending time collecting data, they could focus on understanding opportunities and building stronger customer conversations

Understanding local demand across Europe presented several obstacles.

• Recommendations relied on proxy data. Many customer conversations depended on broad market assumptions rather than local evidence.
• Confidence in European market intelligence was difficult to build. Previous data sources created uncertainty around what was happening in individual countries.
• Understanding multiple markets required significant effort. Tracking trends across countries, cuisines, and consumer groups often meant pulling information from multiple places.
• Presentations became outdated quickly. Customer-facing trend decks required frequent manual updates.

To understand what was happening across European markets, the team analyzed several layers of food and beverage behavior.

• Consumer demand. Consumer signals revealed changing preferences, needs, and occasions within individual markets.
• Recipe behavior. Recipe activity showed how ingredients, flavors, and applications were evolving across countries.
• Menu activity. Menu data provided a real-world view of what was gaining traction in foodservice environments.
• Customer-ready narratives. Food-trained AI agents transformed market evidence into concepts, recommendations, and presentation materials for customer conversations.

By combining these sources, Newly Weds could move from assumptions to evidence-backed recommendations tailored to each market.

• To understand what was happening across European markets, the team analyzed several layers of food and beverage behavior.
  • Consumer demand. Consumer signals revealed changing preferences, needs, and occasions within individual markets.
  • Recipe behavior. Recipe activity showed how ingredients, flavors, and applications were evolving across countries.
  • Menu activity. Menu data provided a real-world view of what was gaining traction in foodservice environments.
  • Customer-ready narratives. Food-trained AI agents transformed market evidence into concepts, recommendations, and presentation materials for customer conversations.

  By combining these sources, Newly Weds could move from assumptions to evidence-backed recommendations tailored to each market.

Tastewise helped Newly Weds build stronger recommendations, faster presentations, and greater confidence in local opportunities.

• 12+ European markets analyzed from one intelligence layer

Teams could compare opportunities across countries without switching between multiple sources.

• One source of truth for local demand

Consumer, menu, and recipe behavior were connected into a single view of the market.

• Faster customer presentations

Teams could update customer-facing narratives using live market evidence rather than rebuilding reports manually.

• More confidence in recommendations

Local market evidence helped support customer conversations with facts rather than assumptions.