Project Affluent showcases how creative research helped to turbocharge the Audi brand.
This work consists of a meta-analysis compiling learnings from different advertising sales experiments that ran in Latin America between 2017 and 2018. By contrasting results of measurements performed with advertising campaigns, we aim to elucidate how different marketing practices contribute to generate brand sales. Measurement methodologies consist of different approaches, for which we provide detail. Our conclusions are towards (1) validating effectiveness of different advertising practices based on evidence produced by experiments and (2) the adoption of a âtest-and-learnâ mindset, where brands continuously generate evidence of how their advertising practices work to produce results, is fundamental to growth in a rapidly changing environment.
This work consists of a meta-analysis compiling learnings from different advertising sales experiments that ran in Latin America between 2017 and 2018. By contrasting results of measurements performed with advertising campaigns, we aim to elucidate how different marketing practices contribute to generate brand sales. Measurement methodologies consist of different approaches, for which we provide detail. Our conclusions are towards (1) validating effectiveness of different advertising practices based on evidence produced by experiments and (2) the adoption of a test-and-learn mindset, where brands continuously generate evidence of how their advertising practices work to produce results, is fundamental to growth in a rapidly changing environment.
My court: a tangible transformation from B&M to a dynamic and living space.
As more advertising spend migrates online, thereâs a need to understand differences between online ads that drive short-term sales and those which drive long-term, profitable brand growth. This need is particularly acute as the industry faces pressure to prove ads are actually being seen, and from consumers increasingly blocking intrusive ads. Moving the profit needle digitally has never been so important, but itâs never been so hard!
This paper describes the journey of a successful portfolio reconfiguration based entirely in the understanding of the consumer and shopper. Adding complexity to the equation, this business case is about one of the most compound segments of the snacking industry: Assorted Multipacks. The complexity of this segment stems from different causes. First, each SKU is the combination of different SKUs with different brands, segments, and benefits that are addressed to different targets of consumers. Second, in this segment the shopper buys multiple products in one transaction, in exchange for a budgetary benefit. This fact makes Assorted Multipacks a low profitability segment. Third, in a category mostly bought in traditional stores, this segment embraces a pantry stock trip mission in the organized trade making it unique and different.
As more advertising spend migrates online, thereâs a need to understand differences between online ads that drive short-term sales and those which drive long-term, profitable brand growth. This need is particularly acute as the industry faces pressure to prove ads are actually being seen, and from consumers increasingly blocking intrusive ads. Moving the profit needle digitally has never been so important, but it's never been so hard! The key factor we explored was the role of emotion in digital advertising. The role of emotion in making TV and online video advertising is well known. But emotion tends to be underplayed as profitability in digital advertising.
Get to know how PepsiCo Foods achieved a turnover in the assorted multipacks segment in Colombia, after losing market share for 2 years in a row, applying an actionable segmentation model and simple co-creation exercises with shoppers. SKU optimization, multipack mix reconfiguration, new image, differential execution among channels, disruptive exhibitions at POS and relevant promotions were possible thanks to the consumer and shopper insights gained from this research project.
This paper describes the journey of a successful portfolio reconfiguration based entirely in the understanding of the consumer and shopper. Adding complexity to the equation, this business case is about one of the most compound segments of the snacking industry: Assorted Multipacks. The complexity of this segment stems from different causes. First, each SKU is the combination of different SKUs with different brands, segments, and benefits that are addressed to different targets of consumers. Second, in this segment the shopper buys multiple products in one transaction, in exchange for a budgetary benefit. This fact makes Assorted Multipacks a low profitability segment. Third, in a category mostly bought in traditional stores, this segment embraces a pantry stock trip mission in the organized trade making it unique and different.
My court: a tangible transformation from B&M to a dynamic and living space.
The loyalty programme of Carrefour has been running for several years. It consists of giving loyalty points to card users when their basket has a specific spend value. Carrefour wanted to know until which point you can motivate the customer to spend more, while maximising the feeling of generosity and minimising the promo cost. To help Carrefour with this (i.e. finding the ideal balance between reward and cost), solutions-2 combined big data (individual customer data on a big scale) with research methods. Carrefour allowed solutions-2 to use 2M of its customers, and its promo budget, in a live test environment. They implemented a complex conjoint design, in which market research data was combined with real spend data. It clearly showed that big data + market research are both needed to get the best value out of both.
The loyalty programme of Carrefour has been running for several years. It consists of giving loyalty points to card users when their basket has a specific spend value. Carrefour wanted to know until which point you can motivate the customer to spend more, while maximising the feeling of generosity and minimising the promo cost. To help Carrefour with this (i.e. finding the ideal balance between reward and cost), solutions-2 combined big data (individual customer data on a big scale) with research methods. Carrefour allowed solutions-2 to use 2M of its customers, and its promo budget, in a live test environment. They implemented a complex conjoint design, in which market research data was combined with real spend data. It clearly showed that big data + market research are both needed to get the best value out of both.