Case study · Growth & pricing

Growing sales, hidden risks: the 38% price gap

Understanding what really drives growth

38%
price gap between regions
CLIENT
Foreign drink brand
DATA USED
12 months of on-trade consumption data
Case study · Brand launch

Six venue types, two that matter: a razor-sharp brand launch

How on-trade venue data shaped a new brand launch in Belgium

2 of 6
venue types are the right place to launch
CLIENT
International brand owner
DATA USED
On-trade consumption data, 6 venue types
Case study · Campaign ROI

Two cities, two campaigns, one clear answer

Measuring the real ROI of marketing campaigns

18
key metrics tracked day by day
CLIENT
Leading soft drink producer
DATA USED
Daily on-trade consumption data, 2 cities
Case study · Brand & pairing

The right pairing: testing a decades-old advertising choice

Putting a brand’s iconic food pairing to the test

4
dimensions analysed for every pairing
CLIENT
Premium alcohol producer
DATA USED
Consumption data and venue metadata
Case study · Non-alcoholic beer

Non-alcoholic beer isn't competing with beer

How on-trade consumption data reshaped a brand's strategy

Daytime
when non-alcoholic beer is really ordered
CLIENT
Beverage brand owner
DATA USED
Ticket lines by venue type and hour
Case study · Weather & sports

Sunshine beats sports: putting numbers on gut feeling

How weather and sports events really drive consumption

17:00–20:00
the sunshine window that drives sales
CLIENT
Alcohol producer
DATA USED
On-trade consumption data
Executive summary

A foreign drink brand saw its sales grow in Belgium, but did not know why. Its sales team also reported large price differences between regions.

Tea Time Data analysed one year of consumption data. We found that:

  • Growth came from new venues, not from higher sales per venue.
  • Prices varied by up to 38% between regions.
  • The cause was the venue mix: the product was sold in very different types of outlets, with different prices and customer profiles.

Behind healthy sales figures, the brand's positioning was at risk. The data gave management the facts to act.

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Executive summary

An international brand owner planned to launch a new flavoured water brand in Belgium, a market where it did not yet distribute. It knew the retail market well, but lacked a clear view of the on-trade.

Tea Time Data defined 6 venue types together with the client, and mapped waters, soft drinks and non-alcoholic beers across them. We found that:

  • Two venue types out of six are the right place to launch the brand.
  • Not every venue is worth the investment: the other four are far less of a priority.

Instead of flooding the market, the brand launches with a razor-sharp strategy. According to the client, this saved a very significant amount of money.

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Executive summary

A leading soft drink producer tested two marketing campaigns in two different cities. It needed to know which one worked best, and what each one really returned.

Tea Time Data sat down with its customer and established 18 key metrics to be monitored, day by day, before and after the campaigns. For the first time, the company could calculate an objective, number-based ROI for each campaign.

The data also revealed a surprise: the best choice depended on the mix of venues in each city. The right campaign is not the same everywhere.

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Executive summary

For many years, a premium alcohol brand has advertised its product next to one specific food item. The choice was based on gut feeling, and it was never questioned.

Tea Time Data tested this pairing against actual consumption data. We found that:

  • The iconic food item was not the top pairing. Other food items came out stronger.
  • The setting matters as much as the food. The best pairings varied by venue type, price level and region.
  • The insight went far deeper than expected, giving a full map of how, where and with what the product is consumed.

The brand kept its iconic campaign, now with a slightly different food item and venue setting, based on facts.

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Executive summary

A beverage brand asked Tea Time Data a simple question: how is our non-alcoholic beer really consumed in the horeca?

The answer changed its strategy. Our data showed that non-alcoholic beer is drunk much earlier in the day than regular beer. Its consumption pattern matches soft drinks, not beer.

The conclusion is clear: the real competitor of non-alcoholic beer is the soft drink. This has direct consequences for marketing, sales and distribution.

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Executive summary

An alcohol producer believed that good weather and televised sports boosted its sales in bars. But it did not know by how much, or whether the effect was big enough to build a strategy on.

Tea Time Data combined 12 months of consumption data with local weather data and the sports calendar. Our analysis gave clear answers:

  • Weather matters, at a precise moment. Consumption peaks when the weather is good between 17:00 and 20:00.
  • Sports events do not. Their effect is too small to justify a dedicated campaign.

The brand now knows when its product is chosen: as an aperitif drink.

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