Cuebiq’s mission, as an offline intelligence and measurement company, is to deliver the most accurate and reliable insights on how digital marketing efforts impact offline consumer behavior. This case study shows how Cuebiq, despite signal loss, partnered with Experian to continue delivering in-store lift analyses. To achieve this, Cuebiq used Experian’s Activity Feed to resolve digital ad exposures to in-store purchases, so that marketers could know the effectiveness of their clients’ media campaigns.
Activity Feed helped Cuebiq increase its match rates by using all the identifiers supported in Experian’s signal-agnostic Digital Graph, reducing its reliance on third-party cookies. By partnering with Experian, Cuebiq could help their clients, marketers, more accurately measure their campaigns and optimize their media.
What is Activity Feed?
Experian’s Activity Feed pulls together fragmented digital event data from all digital channels, including browsers like Safari and Firefox that restrict traditional tracking methods. Activity Feed ingests and ties this digital ad exposure data to household or individual profiles hourly, helping clients associate that data to offline purchase activity made by that household or individual. Activity Feed plays a crucial role in overcoming fragmented data and helping marketers accurately measure their cross-channel marketing efforts.
Challenge: Increasing match rates across digital platforms
Cuebiq wanted to enhance how well they connect digital ad exposures, across web, mobile and connected TV (CTV) to specific mobile ad IDs (MAIDs), of those who visited clients’ stores. They needed a single technology partner who could collect data across these environments and improve these connections, especially as iOS updates, like iOS 14.5, posed potential challenges.
With the ability to resolve exposures to households, individuals, and MAIDs to then facilitate attribution of digital exposures to offline store visitation, Cuebiq could continue to provide accurate reports on how online ads impact offline consumer behavior. This clarity in data enables their clients to fine-tune their marketing strategies.
Cuebiq’s key objectives included:
- Resolving digital exposures to MAIDs
- Increasing overlap of offline and online data
- Improving the effectiveness of offline measurement offerings
Activity Feed: The solution to increase match rates
Cuebiq used Activity Feed to resolve data from cookieless environments like Safari to a single household or individual and saw significantly higher match rates. Cuebiq was able to track cross-channel media exposures, resolve them to MAIDs, and then use the Activity Feed output to correlate in-store visitation and sales to their clients’ media campaigns. Cuebiq also implemented the Experian pixel, which they placed to track all their marketers’ impressions (mobile, CTV, web traffic, etc.). The Experian pixel collects information in real-time, such as:
- Timestamp
- Cookies
- Device ID (MAID/CTV) when available
- IP address
- User-Agent
- Impression ID
“Before we started working with Experian, we couldn’t fully maximize ad views across the complex digital landscape. In just a few weeks, they were able to maximize the match rate across the fragmented digital inventory, solving a huge problem when it comes to cross-channel attribution.”
Luca Bocchiardi, Director of Product, Cuebiq
Results
Activity Feed combines separate data streams and matches them back to a household. This enables Cuebiq to expand household IDs and accurately identify MAIDs that are seen in-store for cross-channel measurement. Over a 21-day period, Cuebiq passed ~1 billion events to Experian. Activity Feed resolved 85% of total events to a household, 91% of which were tied to MAIDs.
By implementing Activity Feed, Cuebiq was successfully able to:
- Gain clearer insights into the success of their client‘s campaigns
- Match consumer engagements in a privacy-compliant manner
- Tell the story of the key performance indicators (KPIs) related to their marketing efforts
Prepare for a cookieless future with higher match rates
Activity Feed is prepared for a cookieless future and uses alternative IDs, like ID5 IDs, hashed emails, and IPs for identity resolution, ensuring no reliance on third-party cookies. Experian remains fully committed to exploring a suite of next-generation solutions and prioritizing continued testing of different industry solutions, including the Google Privacy Sandbox, to help customers prepare for a future without cookies. We’ve identified six viable alternatives to third-party cookies, how these alternatives fall short, and how Experian can help you navigate these alternatives.
“Experian’s customer service is extremely efficient and collaborative. We trust them to keep putting our business first long-term.”
Luca Bocchiardi, Director of Product, Cuebiq
Download the full case study to discover how Cuebiq used Activity Feed to overcome their challenges. Your path to maximizing match rates and resolving data from cookieless environments starts here.
About Cuebiq
Cuebiq is transforming the way businesses interact with mobility data to providing a high-quality and transparent currency to map and measure offline behavior. They are at the forefront of all industry privacy standards, establishing an industry-leading data collection framework, and making it safe and easy for businesses to use location data for innovation and growth.
To learn more, visit their website at www.cuebiq.com
Latest posts
In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in adtech. Today’s interview is with Georgia Campbell, Head of Strategic Partnerships at Kontext. What types of audiences does Kontext provide, and what are some top use cases for these insights in marketing strategies? Kontext leverages its 1st-party, deterministic shopping data to generate real-time online audiences. What sets Kontext apart is our ability to see the entire consumer journey, from shopping interest to intent and purchases, at a SKU-level. This comprehensive visibility allows us to create purchase-based audiences across various consumer verticals, such as frequent online shoppers, consumers shopping for beauty, segments using Mastercard, or Black Friday enthusiasts. Our data engine, built on a foundation of approximately 100 million consumer profiles and over 10 billion full-funnel, real-time shopping events, enables the creation of precise audience segments. This real-time 1st-party shopper data is invaluable for partners aiming to understand and engage with consumers more effectively. Whether a brand wants to activate past shoppers in a specific category or reach new audiences with a propensity to buy, Kontext provides the insights needed to make informed decisions. Some examples of audience types include these (and hundreds more): In-Market Shoppers: Consumers showing high intent to purchase specific categories, like skincare or electronics, based on recent online behavior. Past Purchasers: Shoppers who have made verified purchases within specific time frames, such as beauty products in the last 18 months. Frequent Shoppers: High-frequency buyers identified through repeated purchasing behaviors. Seasonal Shoppers: Consumers active during key shopping seasons, like Black Friday, Mother’s Day, Valentine's Day, etc Premium Buyers: Shoppers who used a premium CC (eg. Amex) and a higher AOV (average order value) Beauty Buyers: an audience that has indicated intent to purchase beauty products (deterministic past purchasers also avail) By using Kontext data, brands can identify the right audiences across multiple verticals, such as retail, CPG, health & wellness, auto, business, energy & utility, financial, and travel. Additionally, our collaboration with Experian allows further refinement of these audiences through layered data from specialty categories like demographics, lifestyle & interests, mobile location, and TV viewing habits. How is Kontext’s data sourced, and what differentiates it from other data providers? Kontext’s data is unique because it is deterministic, 1st-party, and collected as transactions occur. We capture the entire path-to-purchase, down to the SKU-level product detail, across 100 million consumer profiles and more than 10 billion real-time shopping events. Our proprietary technology, embedded in widgets across our 5 million premium online destinations, tracks the full consumer journey—from reading an article of interest to clicking on our dynamic commerce modules, adding items to cart, and completing purchases. This real-time data collection ensures there is no lag between digital events and their connection to consumer profiles. Unlike other providers, we do not aggregate data from multiple platforms; instead, we focus on building our models and insights based on authentic online consumer behavior. Our data stands out due to its: Deterministic Nature: We capture 1st-party data as transactions occur (all in real time) Full-Funnel Coverage: We capture consumer journeys from awareness to purchase, providing a complete view of consumer behavior. Real-Time Insights: Our data engine processes events in real-time, enabling timely and relevant marketing actions. How does Kontext ensure the accuracy and reliability of its audience data? Kontext ensures accuracy and reliability through our unique technology and direct data sourcing. By not aggregating data from other platforms, we maintain control over the quality and integrity of our insights. Our continuous investment in refining our models around online consumer behavior further enhances the precision of our audience data. What types of brands or verticals might resonate the most with Kontext audiences for activation? Any brand looking to understand and activate online shopping behavior – informed by 1st-party transaction data – will resonate with Kontext audiences. Essentially, any vertical that benefits from understanding real-time shopping behaviors, such as retail, health & wellness, auto, and financial services, will find our data invaluable. We have particularly strong insights in beauty, hair care, health & wellness, and values-based online shopping habits, as well as the food & beverage space. Retail & Consumer Goods: Leveraging shopping behavior data for targeted campaigns. Health & Wellness: Identifying consumers with specific health and wellness interests. Automotive: Targeting potential buyers of electric vehicles or eco-friendly products. Financial Services: Engaging high-value shoppers with premium credit card usage. And many more How does Kontext’s data help advertisers navigate the challenges posed by the deprecation of third-party cookies? As third-party cookies become less reliable, Kontext’s 1st-party data becomes invaluable. Our deterministic data engine, which does not rely on cookies, offers: Direct Consumer Insights: Accurate and consented data directly from consumer interactions. Privacy Compliance: Our data collection methods are fully compliant with privacy regulations, ensuring secure usage. Cross-Device Coverage: We use verified digital identifiers, allowing seamless unification and targeting across multiple devices. What measures does Kontext take to maintain data privacy and compliance, and how does this benefit advertisers? Data privacy and compliance are fundamental to Kontext. We meet or exceed all privacy compliance and security standards, ensuring that our data sourcing and usage are transparent and comply with regulations (CCPA, CPRA, VCDPA, etc). Kontext prioritizes data privacy and compliance through: Consented Data Collection: All data is collected with explicit consumer consent. Robust Security Protocols: Data is encrypted and secured with industry-leading practices. Compliance with Regulations: We adhere to global privacy laws, including GDPR and CCPA. User Control: Consumers have the ability to opt-out and manage their data preferences. Can you share success stories / use-cases where advertisers significantly improved their campaigns using Kontext’s data? To give you a sense of how Kontext data can be applied, here are two use-cases: Beauty Brand Campaign: An agency hoping to activate an audience of beauty purchasers for a Major Beauty Brand could utilize Kontext's custom audience of high-value beauty product purchasers. By targeting those consumers who had bought similar products in the last 12 months and had an average cart size of over $50, the campaign would significantly increase performance and ROAS. Electric Vehicle Launch: For a major auto manufacturer’s EV launch, Kontext could be used to identify eco-friendly consumers who had not yet purchased an EV but had shown interest in sustainable products. This precise targeting could lead to higher engagement and conversion rates for the campaign. Thanks for the interview. Any recommendations for our readers if they want to learn more? For those interested in learning more about Kontext, reach out for a personalized consultation. Contact us About our expert Georgia Campbell, Head of Strategic Partnerships, Kontext In her current role as Head of Strategic Partnerships at Kontext, Georgia plays a pivotal role in shaping the company's strategic direction within the data space. With a deep-seated expertise in leveraging data to drive impact for companies, Georgia has been forging key partnerships that enhance the effectiveness and reach of Kontext's offerings. Georgia comes from a background in emerging technology, where she has been focused on cultivating partnerships and employing data-driven approaches to spearhead market expansion efforts. She started her career in finance, managing investments across equity, debt, and alternative assets at Brown Advisory. In this Q&A, Georgia shares her insights on Kontext's Onboarding partnership with Experian, offering perspective on how Kontext's unique insights can unlock new opportunities for advertisers and brands alike. Latest posts
Discover Experian’s new solution tailored for retail media networks (RMNs) designed to enhance RMNs’ strength in first-party shopper data.
Explore how real-time data from Experian and Captify can revolutionize personalized advertising to enhance campaign effectiveness.