A new era of consumer research - Deepstash
A new era of consumer research

A new era of consumer research

PepsiCo uses a tool called Tastewise, which deploys algorithms to uncover what people are eating and why. The AI-driven tool analyzes massive quantities of food data online.

AI collects data that consumers don't report in focus groups.

Through findings from the tool, PepsiCo incorporated seaweed into a flavored savory snack. It's been a top seller since it was brought to the market.

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MORE IDEAS FROM How PepsiCo uses AI to create products consumers don’t know they want

Data driven social prediction

PepsiCo also leans heavily on Trendscope

which focuses exclusively on social conversations around food on Twitter, Reddit, blogs, review boards, and more. 

The tool considers context and whether or not the conversation is relevant to the business, it measures not only the volume of specific conversations but how they grow over time.

There was a spike in interest around immunity during the pandemic, and PepsiCo used this tool to launch a new line of its propel sports drinks infused with Immunity ingredients.

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Stephan Gans - Team PepsiCo

I’m always making sure there is both a data-driven and a human empathy perspective brought to commercial decision-making.

That is a key role and ongoing challenge for my team

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Once the products are developed, there’s still plenty for AI and machine learning to do.

For the launch of Mountain Dew Rise Energy, for example, PepsiCo determined which consumers would be more likely than average to enjoy the drink, and then narrowed it in further to determine a core target.

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After integrating these technologies, it’s easy to become overly reliant on the data, which can’t always speak to people’s actual motivations. 

A recent Pepsi ad, which focuses on the shared human emotions of the pandemic and doesn’t feature any products.

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<p>Content marketing is the mo...

Content marketing is the most effective marketing strategy . And there is always a competition to write better content, be more creative, and be more engaging. But in this new digital era, artificial intelligence can be used in content creation. As you know, AI evolved into more than simply a futuristic technology. There’s a high possibility you’re already experimenting with AI , no matter what field you work in. Let’s face it, AI is everywhere, whether it’s deploying chatbots to collect data about your users’ most urgent concerns or assessing content results with AI platforms.

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Building ethical AI

Companies are leveraging data and artificial intelligence to create scalable solutions — but they’re also scaling their reputational, regulatory, and legal risks. For instance, Los Angeles is suing IBM for allegedly misappropriating data it collected with its ubiquitous weather app. Optum is being investigated by regulators for creating an algorithm that allegedly recommended that doctors and nurses pay more attention to white patients than to sicker black patients. Goldman Sachs is being investigated by regulators for using an AI algorithm that allegedly discriminated against women by granting larger credit limits to men than women on their Apple cards. Facebook infamously granted Cambridge Analytica, a political firm, access to the personal data of more than 50 million users.

Just a few years ago discussions of “data ethics” and “AI ethics” were reserved for nonprofit organizations and academics. Today the biggest tech companies in the world — Microsoft, Facebook, Twitter, Google, and more — are putting together fast-growing teams to tackle the ethical problems that arise from the widespread collection, analysis, and use of massive troves of data, particularly when that data is used to train machine learning models, aka AI.

AI and Equality
  • Designing systems that are fair for all.

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All companies will need to become “AI companies”

... so they can leverage the considerable benefits to be gained through greater knowledge of their customers, explore new markets, and counteract new, AI-driven companies that might seek their market share.

To extract the benefits from AI while mitigating the risks, companies must ensure that they are sufficiently agile so they can adopt best practices to create responsible transformation with AI.

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