Organizations across industries are achieving unprecedented efficiency and scale along with robust compliance by using data and AI. At Snowflake’s most recent virtual events for industries, Accelerate Retail & Consumer Goods, in partnership with Microsoft, and Accelerate Advertising, Media & Entertainment, attendees heard how industry leaders are accelerating innovation, business insights, customer experience and more with robust enterprise AI and data strategies.
Snowflake experts, customers, partners and leaders provided strategic insights, practical tips, best practices and demos for key industry use cases. Here are a few key takeaways from both events.
Accelerate Retail & Consumer Goods
1. Retail and consumer goods companies are becoming more creative about using data to understand consumer preferences through social media, data collaboration and the use of third-party data marketplaces to build out customer 360. “When you think about it, the person who buys groceries and jeans is the same person who drives a car or uses a cell phone or consumes streaming media,” said Shanthi Rajagopalan, Global Head of Strategy, RCG, at Microsoft. “Leveraging the interconnectedness of all of this consumer behavior data is a real opportunity for brands to understand their consumers’ needs and motivations even better.”
2. Effective customer 360 implementation depends primarily on three things: a solid data foundation, data quality and governance, and AI activation to personalize experiences in real time. “Focus on a solid data foundation, then build the AI on top of it, using loyalty and purchase data [to create] offers,” said Vinay Banari, Managing Director, Digital, Data and AI Consulting, at EY. “The data readiness, which means a strong platform, clean data and AI, is what drives real impact.”
3. AI presents a huge opportunity for marketers to shift the manual work of personalization to AI. “Most marketing programs are still built on outdated methods like rule-based approaches or marketing calendars, failing to leverage the wealth of data available about individual customers,” said Alec Haase, Product Go-to-Market Leader at Hightouch. “These programs rely on rigid rules that ignore customer behaviors and result in one-size-fits-all experiences that don’t build customer loyalty. Additionally, launching personalized campaigns is exhausting. It takes multiple people, teams, tools and dozens of hours, and leaves marketers stuck in manual systems and siloed decision-making. We see AI as a better way for marketers to approach personalization and work smarter, not harder.”
4. AI can enable marketing teams to move from being purely execution led to being data driven, leading to quantifiable results. “We’ve seen a 10% uplift in conversion [from AI],” said Aoife O’Driscoll, Director, Lifecycle Marketing, at Whoop. “The power of this model is that it can do way more than we can humanly do within a matter of weeks, which is phenomenal. And that 10% uplift in shop conversion should result in about a 20% uplift in revenue in 2025.”
Accelerate Advertising, Media & Entertainment
1. Establishing a secure, organized and privacy-enabled data warehouse is foundational for successful data collaboration through clean rooms. “By warehousing your data in a privacy-compliant safe location, and by building a really good taxonomy of what that data means, you can build better functionality and onboarding data with any party on the audience side,” said Jenny Yurko, VP, Data Product Strategy, at Warner Bros. Discovery.
2. For fruitful data integration and analysis, a clean room solution needs to accurately unify disparate identity information. “The worlds of offline and online data sets are moving closer and closer together. You’re going to want to have a clean room solution that has identity resolution as a core, key component,” said Jon Regan, VP at Dentsu. “The better your clean room is at piecing together the fragmented worlds of names, emails, phone numbers and IP device IDs into a cohesive identity graph, the more likely your implementation will be a success.”
3. Successfully using data clean rooms for collaboration requires clearly defined goals, a clear understanding of data rights and limitations, and a commitment to compliance and privacy. “Understanding the use case, the data you want to use and the desired outcomes, including how you’ll utilize that data, leads to a series of questions,” said Reese Solberg, Managing Director and US Data Privacy Leader at EY. “What rights do you have to that data? What obligations are attached to that data and, similarly, for other companies or entities you may be collaborating with? Once you understand these aspects, you can begin to define the requirements for the tool or solution. Then, you can evaluate whether [you] can use this clean room. Ultimately, it comes down to defining your key business and compliance requirements to guide your tooling selection.”
4. Snowflake Data Clean Rooms promote collaborative, transparent data analysis. “One of the great things about Snowflake’s data clean rooms is that they’re transparent and flexible,” said Joe Zucker, Senior Manager, Marketing Analytics, at Indeed.com. “You can write a query in SQL and everybody who is working on a project can see it. As an advertiser, we write the query sometimes, and sometimes the publisher writes the query. But in both cases, we can always see what the assumptions, rules and syntax are, so there’s an agreed-upon view of how we’ll be analyzing this campaign.”
Speakers also shared insights on the blueprints of an enterprise data architecture, how customers are using AI/ML to drive efficiencies and how companies are accelerating their business-critical workflows.
Missed the events? You can still watch them on demand: Accelerate Retail & Consumer Goods and Accelerate Advertising, Media & Entertainment.
