After a six-month beta period, collaboration in Snowflake Data Clean Rooms using Experian’s offline or digital graph is now generally available for all clients. As part of this, Experian is excited to announce that Experian’s identity graph will be integrated into Snowflake’s Data Clean Rooms. With the growing importance of data privacy and marketing efficiency, this partnership builds off of Experian’s previously-announced integration into Snowflake’s AI Data Cloud for Media.
Adding Experian’s identity graph to Snowflake Data Clean Rooms helps advertisers, advertising platforms, and measurement partners work more effectively. Built upon Experian’s rich offline and digital identity foundation, with support for various identifiers across platforms, collaboration in Snowflake Data Clean Rooms helps clients maximize the value of their data and meet the diverse needs of modern business:
- Collaborate with partners for richer data insights
- Achieve higher match rates
- Improve audience building
- Produce more accurate and complete reports
- Ensure data privacy
- Seamless integration of AdTech and MarTech platforms
Regardless of the identifier type you are looking to collaborate on, Experian has the identity data in Snowflake Data Clean Rooms to support you and your partner. This leads to higher match rates and more resolved data for you to use to benefit your media initiatives.
“Integrating Experian’s identity graph into Snowflake Data Clean Rooms marks a transformative leap for digital marketing. This collaboration empowers advertisers, programmatic platforms, and measurement partners with unparalleled accuracy, privacy, and efficiency. Together, we are excited to provide innovative solutions to meet the evolving needs of our clients.”
Kamakshi Sivaramakrishnan, Head of Data Clean Rooms at Snowflake
The Experian and Snowflake partnership showcases how collaboration can enhance scalability and cost-efficiency. Data clean rooms provide a secure environment where multiple parties can share, join, and analyze their data assets without leaving the clean room or exposing the underlying data. By integrating Experian’s identity graph within Snowflake’s secure platform businesses of all sizes can receive advanced data collaboration and identity tools without the high costs usually involved.
The integration prioritizes consumer privacy and data security. Backed by Experian’s Global Data Principles, Experian’s deep roots in data protection and security provide customers with the most trusted way to share data and protect consumer privacy. With Experian’s graph in Snowflake Data Clean Rooms, customers will get a solution that respects customer consent, safeguards sensitive data, and ensures that processing occurs with the utmost respect for user confidentiality and preferences.
Further, Snowflake Data Clean Rooms uses advanced methods to preserve privacy, such as differential privacy and secure computations on encrypted data, enabling data security and integrity. Together, these methods prevent unauthorized access by keeping sensitive data within the secure confines of the cleanroom on a strict, collaboration-to-collaboration basis.
The collaboration between Experian and Snowflake significantly enhances data matching and identity resolution within the Snowflake Data Cleanroom. Experian’s identity solution uses digital identifiers like hashed emails, MAIDs, and CTV IDs and offline identifiers like name and address. This allows advertisers to reach more consumers and enrich their data. Marketers can easily use their first-party data in the cleanroom, and with Experian’s Graph, they get higher match rates for more accurate targeting and campaign measurement.
The continued partnership between Snowflake and Experian provide advertisers, platforms, and measurement providers a secure and effective way to collaborate. This sets the stage for continued innovation in programmatic advertising, ensuring that our solutions evolve in step with our clients’ needs.
If you’re not utilizing clean rooms for collaboration but have advanced identity needs, you can license our Graph and seamlessly integrate it into your Snowflake account.
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In a youth-obsessed world where fresh faces sell products, despite all efforts it’s a cruel reality that fashion models will eventually have to look for a new job. While they may try to self preserve with plastic surgery, Botox and laser treatments, let’s face it – they can’t be models forever. The advertising industry knows that a fresh face can’t be overlooked to sell products, so why should it be different for traditional direct marketers? Customers are the lifeblood of any business, yet businesses lose anywhere from 10-30% of them per year. Today’s “always on” shopper makes decisions in every channel – direct, online and in-store. In looking for better ways to sell more products to current and new customers, marketers seek out ways to expand their prospect universe to improve customer acquisition levels. Why? Customers are the lifeblood of any business, yet businesses lose anywhere from 10-30% of them per year. This makes new customer acquisition extremely important to both protect and grow business year over year. The acquisition challenge is that traditional prospect universe expansion is becoming increasingly difficult. Many marketers have exhausted list and co-op rental names, and optimization strategies. They’ve been using the same predictive prospecting models against compiled prospect data or co-ops for a long time. But these tools, which are based on traditional demographics, are increasingly leading to a decline in good prospect identification and acquisition. We know that in prospecting, there is no customer behavioral data to drive higher performing analytics – no plastic surgery or proverbial fountain of youth. In today’s multi-channel shopping world, the fresh face of online behavior can’t be overlooked. While direct marketers in self-preservation mode have leveraged traditional acquisition models for years, the reality is that if they do not consider fresh new data and modeling solutions, they will be looking for their next, new job. So, what can marketers do to overcome prospect universe expansion hurdles with online insight to increase acquisition and ROI? Meet direct marketing’s fresh new face: online behavioral data and modeling. Online behavioral data addresses a key challenge of traditional direct marketers: profitable prospect universe expansion. By incorporating online behavioral data (website traffic and behavior, search, demographics, lifestyle data) into offline marketing strategies, marketers can: Identify previously untapped prospect universes Suppress likely non-responders Enhance offline prospecting Where else do consumers so actively demonstrate their purchase interest and behavior? Where else do we go when we want to learn about something? Anything? We go online. But most direct marketers have not enhanced their offline marketing efforts with online data, missing the opportunity to incorporate online behavior into targeting efforts. With this fresh new data source, direct marketers are able to: Better understand customer behavior across channels Refresh their current models Develop better models, built from true, multi-channel data Ultimately, direct marketers will be able to identify new pockets of high-value prospects that traditional response models miss, resulting in an increase in revenues and profit. Fashion models and trends change, and sometimes that’s for the best, otherwise we might still be wearing parachute pants and slap bracelets. Luckily, you now know what the new face of marketing is and can begin integrating online behavior into your existing customer data today to leverage new marketing opportunities. Discover the new fresh face of direct marketing; learn more about online behavioral profiling and modeling.
Public attitudes are more open and accepting of LGBT Americans today, and marketers are increasingly showing their support of their LGBT customers. Experian Simmons includes a measure of sexual orientation among non-Hispanic respondents of our National Consumer Study, the only known large probability sample syndicated study to include such a measure. In our 2012 LGBT Demographic Report, we looked at marriage and cohabitation habits, as well as income levels and discretionary spend of LGBT and heterosexual adults alike. This data helps marketers better understand and connect to the growing and already influential LGBT demographic and to benchmark important factors against the heterosexual population. A look into individual earnings and household incomes shows that lesbian women earn more than heterosexual women regardless of relationship status. Specifically, the typical adult lesbian woman personally earns $43,100 per year compared with $37,600 claimed by the average heterosexual woman. Furthermore, the typical household income of a married or partnered lesbian woman is $7,200 higher than that of a married or partnered heterosexual woman. Mean individual earnings and household income of women, by sexual orientation When it comes to individual income, gay and straight men may earn roughly the same amount, but married or partnered gay men personally take home nearly $8,000 more, on average, than their straight counterparts. Additionally, the average household income of a married or partnered gay man is $116,000 versus $94,500 for a straight married or partnered man. Mean individual earnings and household income of men, by sexual orientation Income levels are important to consider when targeting consumers, but more important is determining the amount of money they have left over after the bills are paid for non-essentials. Despite having higher incomes, some may be surprised to learn that lesbian women have only the same amount as heterosexual women to spend on discretionary items. Likewise, gay men have less than heterosexual men for non-essentials overall, even though their incomes overall are quite equal. This is mostly likely due to the fact that both lesbian and gay adults tend to reside in larger cities where the cost of living can be considerably higher. Interestingly though, when household size is brought into the equation, we see that gay males actually have more to spend on non-essentials per capita than straight men. Gay men, for instance, live in households that spend $6,256 per capita annually on discretionary spending, nearly $1,000 more than what the households of heterosexual men spend per person. For more demographic and attitudinal information on the trends among the LGBT population, download the 2012 Lesbian, Gay, Bisexual, Transgendered Demographic Report.
My Experian Marketing Services’ colleagues and resident data experts Bill Tancer and Marcus Tewskbury answered the above question for marketers during our recent 2012 Holiday Planning Webinar. The webinar recapped key 2011 holiday marketing results, plus featured trends, benchmarks and recommendations for a successful and profitable 2012 holiday shopping season. Here are a few cool facts: For the first time, last year’s Cyber Monday beat Thanksgiving Day as the busiest online shopping day of the year Facebook and Pinterest were the top traffic sources to the Experian Marketing Services Retail 500 Pinterest visitors most often went to etsy.com and amazon.com from the pinterest.com site Dynamic content in emails can drive up to a 70% lift in open rates Tying web, email and in-store promotions together enhances the shopping experience and improves sales The bottom line is that marketers need to understand where there customers are, when they are there, and what they are doing. Armed with that knowledge, you can deliver personalized and targeted holiday messages that are sure to make this shopping season merry and bright (and profitable!). View the webinar to learn more.