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How the AI revolution is transforming the future of commerce

Published: September 10, 2024 by Experian Marketing Services

The widespread adoption of AI in commerce

Technology is pushing the boundaries of commerce like never before. Artificial intelligence (AI) is one of the primary driving technologies at the forefront of the commerce evolution, using advanced algorithms to revolutionize marketing and personalize customer experiences. As of 2024, AI adoption in e-commerce is skyrocketing, with 84% of brands already using it or gearing up to do so. 

This article explores the AI revolution coming to commerce, focusing on what makes AI a driving force for e-commerce in particular, and the ways it’s reshaping how businesses engage with consumers.

Understanding the AI revolution in commerce

AI is quickly reshaping commerce as we know it by democratizing access to sophisticated tools once reserved for large corporations, breaking down functional silos within organizations, and integrating data from multiple sources to achieve deeper customer understanding. It’s paving the way for a future where every brand interaction is uniquely crafted for the individual, powered by AI systems that anticipate preferences proactively. 

AI is a broad term that encompasses:

  • Data mining: The gathering of current and historical data on which to base predictions
  • Natural language processing (NLP): The interpretation of human language by computers  
  • Machine learning: The use of algorithms to learn from past experiences or examples to enhance data understanding

The capabilities of AI have significantly matured into powerful tools that can improve operational efficiency and boost sales, even for smaller businesses. They have also fundamentally changed how businesses interact with customers and handle operations. As AI continues to develop, it has the potential to provide even more seamless, personalized, and ethically informed commerce experiences and establish new benchmarks for engagement and efficiency in the marketplace.

Four benefits of the AI revolution coming to commerce

Major commerce players like Amazon have benefited from AI and related technologies for a while. Through machine learning, they’ve optimized logistics, curated their product selection, and improved the user experience. As this technology quickly expands, businesses have unlimited opportunities to see the same efficiency, growth, and customer satisfaction as Amazon. Here are four primary benefits of AI adoption in commerce.

1. Data-driven decision making

AI gives businesses powerful tools to analyze large amounts of data more quickly and accurately than a person. Through advanced algorithms and machine learning, AI can sift through historical sales data, customer behavior patterns, and market trends to uncover insights and suggest actions that might not be immediately obvious to human analysts. By transforming raw data into actionable insights, AI empowers businesses to make more informed decisions, reduce risks, and capitalize on opportunities. 
As a real-world example, Foxconn, the largest electronics contract manufacturer worldwide, worked with Amazon Machine Learning Solutions Lab to implement AI-enhanced business analytics for more accurate forecasting. This move improved forecasting accuracy by 8%, saved $533,000 annually, reduced labor waste, and improved customer satisfaction through data-driven decisions.

2. A better customer experience

AI is set to make customer interactions smoother, faster, and more personalized by recommending products based on preferences and behaviors, making it easier for customers to find what they need.

When consumers visit an online store, AI also provides instantaneous help via a chatbot that knows their order history and preferences. These AI-powered assistants offer real-time help like a knowledgeable store clerk. They give the appearance of higher-touch support and can answer basic questions at any hour, provide personalized product recommendations, and even troubleshoot issues. Chatbots free up human customer service agents for more complicated matters, and these agents can then use AI to obtain relevant information and suggestions for the customer during an interaction.

3. Personalized marketing

Data-driven personalization of the customer journey has been shown to generate up to eight times the ROI, as data shows 71% of consumers now expect personalized brand interactions. Until AI came around, personalization at scale was complex to achieve. Now, gathering and processing data about a customer’s shopping experience is easier than ever based on lookalike customers and past behavior.

Many businesses have adopted AI to glean deeper insights into purchase history, web browsing, and social media interactions to drive better segmentation and targeting. With AI, advertisers can analyze behavioral and demographic data to suggest products someone is likely to love. Consumers can now browse many of their favorite online stores and see product recommendations that perfectly match their tastes and needs. 

AI can also offer special discounts based on purchasing habits, and send personalized emails with products and content that interest customers to make their shopping experience more engaging and relevant. This personalization helps businesses forge stronger customer relationships.

Personalization across digital storefronts

Retail media involves placing advertisements within a retailer’s website, app, or other digital platform to help brands target consumers based on their behavior and preferences within that environment. Retail media networks (RMNs) expand this capability across multiple retail platforms to create seamless advertising opportunities throughout the customer journey.  Integrating AI into RMNs can improve personalization across digital storefronts with personalized, relevant ads and custom offers in real time that improve the customer experience.

4. Operational efficiency

AI can also be beneficial on the back end, enabling more efficient resource allocation, pricing optimization, efficiency, and productivity.

Customers can be frustrated when they visit a store for a specific product only to find it out of stock or unavailable in a particular size. With AI, these situations can be prevented through algorithms that forecast demand for certain items. Retailers like Amazon and Walmart both use AI to predict demand, with Walmart even tracking inventory in real time so managers can restock items as soon as they run out. 

AI can automate and streamline operational tasks to help businesses run smoother, faster, and more cost-effective operations. It can:

  • Offload tedious data entry, scheduling, and order processing tasks for greater fulfillment accuracy. 
  • Analyze historical data and market trends, predicting demand to help businesses optimize inventory, reduce waste, track online and in-store sales, and prevent shortages.
  • Forecast demand levels, transit times, and shipment delays to make better predictions about logistics and supply chains.
  • Improve data quality using machine learning algorithms that find and correct product information errors, duplicates, and inconsistencies.
  • Adjust prices based on competitor pricing, seasonal fluctuations, and market conditions to maximize profits.
  • Pinpoint bottlenecks, identify issues before they escalate, and provide improvements for suggestions.

Future trends and predictions

If you want to stay ahead in e-commerce, it’s just as important to know what’s coming as it is to understand where things are today. Here are some of the trends expected to shape the rest of 2024 and beyond.

Conversational commerce

Conversational commerce allows real-time, two-way communication through AI-based text and voice assistants, social messaging apps, and chatbots. Generative AI advancements may soon enable more seamless, personalized interactions between customers and online retailers. This technology can improve customer engagement and satisfaction while providing helpful insights into preferences and behaviors for better personalization and targeting.

Delivery optimization

AI-driven delivery optimization uses AI to predict ideal routes for each individual delivery, boosting efficiency, reducing costs, promoting sustainability, and improving customer satisfaction throughout the delivery process.

Visual search

AI-driven visual search is quickly improving in accuracy, speed, and contextual understanding. Future developments may integrate seamlessly with augmented reality (AR) so shoppers can search for products by pointing their devices at physical objects. Social media and e-commerce platforms may soon incorporate visual search more prominently, allowing users to find products directly from images.

AI content creation

AI is already automating and optimizing aspects of content production:

  • Algorithms can generate product descriptions, blog posts, and social media captions personalized to specific customer segments. 
  • AI tools also enable the creation of high-quality visuals and videos. 
  • NLP advancements ensure content is compelling and grammatically correct. 
  • AI-driven content strategies analyze consumer behavior and refine messaging to meet changing preferences and trends.

This automation speeds up content creation while freeing resources for strategic planning and customer interaction.

IoT integration

Integrating AI with Internet of Things (IoT) devices could help make the ecosystem more interconnected in the future. AI algorithms can use data from IoT devices like smart appliances, wearables, and sensors to gather real-time insights into consumer behavior, preferences, and product usage patterns. This data enables personalized marketing strategies, predictive maintenance for products, and optimized inventory management. AI-driven IoT data analytics can also streamline supply chain operations to reduce costs and inefficiencies.

Fraud detection and security

There will likely be an increased focus on the ethical use of AI and data privacy regulations to strengthen consumer trust and transparency. AI-powered systems will get better at detecting and preventing fraud in e-commerce transactions, which will heighten security measures for both businesses and consumers.

Chart the future of commerce with Experian

AI has changed how marketers approach e-commerce in 2024. With AI-driven analytics and predictive capabilities, marketers can extract deeper insights from extensive data sets to gain a clearer understanding of consumer behavior. This enables refined segmentation, precise targeting, and real-time customization of messages and content to fit individual preferences.

Beyond insights, AI automates routine tasks like ad placement, content creation, and customer service responses, freeing marketers to concentrate on strategic planning and creativity. Through machine learning, marketers can predict trends, optimize budgets, and fine-tune strategies faster and more accurately than ever. The time to embrace AI is now. 

At Experian, we’re here to help you make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Using AI in your commerce marketing strategy with our Consumer View and Consumer Sync solutions can help you stay competitive with effective, engaging campaigns. 

Contact us to learn how we can empower your commerce advertising strategy today.


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The future of retail advertising: Embracing retail media standardization

In this article… How much standardization currently exists? Why is standardization important? Who is promoting standardization? The benefits of industry standardization Strategies for implementing retail media standardization Future retail media standardization trends Join forces with a strategic RMN partner Retail media is quickly outpacing other areas of digital advertising and is projected to grow 29% by 2025. Despite this trajectory, retail media is still relatively new compared to traditional digital media and operates like a startup in terms of tech capabilities. Sustained growth will require retail media standardization — creating consistent ways to measure and compare ad performance across retail media networks (RMNs). This standardization will be key for RMNs wanting to understand what’s driving the most value and sales for their business. In an Interactive Advertising Bureau (IAB) study, 62% of ad buyers pointed to standardization as a top growth challenge. The current ecosystem’s inconsistent standards have prevented effective investment in measurement and limited ad buyer participation. Standardization will be necessary moving forward for effective adoption and trust in these new channels. This article explores the challenges marketers face without retail media standardization and the collaborative efforts needed to establish consistent measurement standards across the industry. How much standardization currently exists? Retail media standardization is limited industry-wide, with each RMN using its own metrics and definitions; what one network calls a "conversion" might be defined differently by another. Some retail companies also sell ad space within siloed, walled-garden shopping environments, which makes it difficult for advertisers to compare performance across platforms. As a result, the current landscape lends itself to inconsistency, campaign measurement complications, and an unclear view of return on investment (ROI) across RMNs. This fragmentation stems from how retailers have historically developed and managed customer data platforms and e-commerce websites independently, causing disparities in the types and quality of customer data available and the technologies used to manage it. Each retailer uses a unique technology stack and customer experience strategies, which means data is collected, utilized, and integrated into advertising platforms differently. Why is standardization important? A 2023 State of Retail Media Survey highlighted the industry's lack of standardization as a significant obstacle to growth. The Association of National Advertisers also found that advertisers can't fully take advantage of their retail media investments because of inconsistent measurement practices. Standardized retail media measurement practices are critical for growth. By setting consistent measurement standards across different platforms, it becomes easier for various players to: Assess how ads are performing See which strategies work across RMNs Optimize ad spending Make informed decisions Extract more value from advertising budgets Ultimately, standardized metrics are a must for improving transparency, strategic effectiveness, and ROI. Who is promoting standardization? We’re seeing a collective push for retail media standardization by several industry stakeholders wanting a more cohesive and effective advertising ecosystem. One of the most recent efforts came from the IAB and the Media Rating Council (MRC). These organizations collaborated with brands, agencies, and RMNs to develop new guidelines for standardized measurement practices and have given the ecosystem a proposed common language for retail media measurement. These guidelines were released in January 2024 to provide a consistent framework for the following across retail media platforms: Audience measurement Reporting Incrementality Transparency Viewability Ad delivery In-store advertising Microsoft Retail Media, an early adopter of the framework, has experienced greater data transparency, accuracy, privacy, and security, which has benefited advertisers and retailers and advanced Microsoft’s position as a retail media industry leader. Widespread adoption of these guidelines has the potential to drive innovation, attract more advertisers, strengthen collaboration, grow the industry, and improve the consumer experience. The benefits of industry standardization A standardized retail media framework for performance measurement can benefit advertisers, retailers, media agencies, and other stakeholders in the ecosystem. Here are some ways each entity stands to benefit. Benefits for retailers Standardization makes it easier for retailers to demonstrate their credibility and the value of their retail media program. With uniform measurement across channels and campaigns, they can provide clear, comparable data that reflects their impact, builds trust, and encourages advertiser investment. Better campaign management efficiency also reduces the operational burden, so retailers can focus on improving customer experiences and driving sales. Experian’s Activity Feed helps you measure performance — and understand how ads impact shopping behavior — by providing you with ad exposures in one environment (web or connected TV) that you can connect to an action in another (in-store purchase). Learn more about Activity Feed and see it in action here. Benefits for media agencies and marketers With standardized metrics, advertisers and media agencies have an easy, reliable way to compare metrics and assess the effectiveness of various campaigns across RMNs. This “apples to apples” comparison helps them determine which channels are truly driving better ROI so they can effectively optimize spending. Standardization also improves collaboration with retailers and leads to more effective campaigns. Consistent guidelines can help teams create, carry out, and optimize retail media strategies and easily compare platform effectiveness. Benefits for industry stakeholders Industry stakeholders like technology providers and regulatory bodies can greatly benefit from standardized retail media measurement practices. Consistent measurement provides a common framework that improves transparency and trust among parties. With reliable and comparable metrics, standardization helps everyone speak the same language when it comes to performance evaluation and decision-making. This uniformity facilitates smoother interactions and partnerships between the buy and sell sides, so it’s easier to negotiate and collaborate. Strategies for implementing retail media standardization Standardizing measurement will require industry-wide coordination around several strategies, as outlined in best practices frameworks from standardization proponents like IAB/MRC and the Albertson's Media Collective. Unify reporting and performance measurement To address the lack of standardization in performance metrics, RMNs must adopt uniform definitions and calculation methodologies for key metrics. Unified reporting in retail media requires successful stakeholder collaboration to: Agree on critical KPIs and reporting metrics like impressions and conversion rates Adopt standardized data formats and reporting tools Educate stakeholders Ensure data quality and compliance Continuously improve based on industry feedback The IAB/MRC framework provides a basis for standardizing metrics for media delivery and engagement, as well as sales and conversions. This consistency helps advertisers compare performance across platforms effectively, enhancing transparency and decision-making. Standardize product specifications It's important for advertisers to have consistent product specifications, as it makes it easier to create and deploy ads across multiple RMNs. To achieve this, RMNs should align ad formats, file sizes, animations, and video specifications with IAB guidelines. Following these standards will help RMNs eliminate compatibility issues, simplify adoption, and save time and resources. It's also vital for RMNs to maintain flexibility for unique ad formats in order to encourage innovation while still benefiting from standardized specifications. Introduce third-party verification and disclose capabilities Introducing third-party verification for ad placement, fraud detection, brand safety, and competitive separation can improve an RMN’s credibility and transparency. By disclosing the third-party providers used and the types of verification offered, RMNs build trust with advertisers and give them the confidence they need to invest. Additionally, RMNs should disclose their staffing, processes, technology, inventory management, targeting, creative management, and self-service offerings. Transparency in these areas helps advertisers make informed decisions, optimize ad buys, and increase efficiency. Using existing IAB verification and capability disclosure guidelines ensures reliability and a more trustworthy, efficient advertising environment. Future retail media standardization trends The future of retail media is poised for significant growth, especially as standardization guidelines are widely adopted and implemented. Here are some trends we expect to see as retail media ad spending grows. Widespread RMN adoption and spending Standardization could spur greater RMN spending and drive broad adoption by advertisers who hesitated before due to concerns about metrics and performance comparability. New partnerships and collaborations Standardization may lead to new partnerships that weren't possible before: Brands and retailers might team up to blend advertising and sales data for better-targeted campaigns. AdTech companies could also partner with multiple retailers to offer unified advertising solutions. Retail media networks and analytics firms could collaborate to provide deep insights into consumer behavior and campaign performance. Partnerships among retailers, including smaller ones seeking retail media measurement uniformity, may drive further standardization and create new advertising opportunities across product categories with audience overlap. Ad format innovation Agreeing on common standards simplifies how ads are measured and understood. Standardization may drive down costs and free up space for more imaginative, engaging ads in the future. For instance, the IAB/MRC’s common language is helping to promote consistency and clarity and fuel innovation across the board. Incrementality focus As standardization becomes more widespread, there may be a growing trend toward incrementality measurement, which measures the additional impact of advertising campaigns compared to what would have happened without them. Standardized metrics can help advertisers accurately gauge and optimize campaign effectiveness and maximize their marketing investments. Growth of cross-platform ad targeting Standardization may drive the growth of cross-platform ad targeting. With consistent metrics and measurement standards, advertisers will be able to track and compare their ad performance across platforms more accurately. This unified approach will improve ad targeting precision and ensure a consistent impact across RMNs. Commerce media Commerce media is changing retail advertising with its focus on verified data and real-time transaction insights, making campaigns more efficient. This shift could push for more uniform measurement standards across platforms and level the playing field. As commerce media gains traction, its emphasis on targeted advertising and ROI measurement might pave the way for universal metrics and clearer guidelines across retail networks. Where does this leave modern advertisers? Retail media is still at a crossroads. If standardization doesn’t occur soon, its growth may slow. For now, advertisers are resorting to custom strategies or relying on whichever network they feel is most effective for their products. They are likely to continue investing significantly in retail media, maintaining or increasing spending in the next year. 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Light up your holiday advertising campaigns with Experian’s 19 new audiences

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Holiday Budget Savvy Airline Travelers Vacation/Leisure Travelers: Domestic Trips Air Travel (FLA/Fair Lending Friendly)4 Vacation/Leisure Travelers: Frequent Spenders Hotels: Frequent Spend When you work with Experian, you work with a single data provider that gives you access to audiences across multiple verticals and categories, such as travel and retail. Targeted advertising this holiday season with Experian audiences The holiday season is the busiest time of the year for advertisers. Experian's data, ranked #1 in accuracy by Truthset, allows advertisers to reach people based on demographic, geographic, and behavioral attributes (e.g. websites visited and purchase history). By using Experian’s audiences in your holiday advertising campaigns, you can reach last-minute shoppers, discount-seeking shoppers, gift-givers, and holiday travelers. Just as shoppers seek the perfect gifts, with the right strategy, your holiday advertising campaigns can capture the right shoppers this holiday season. Can’t find the audience you’re looking for or need a custom audience? Connect with our audience team for more information. Connect with our audience team You can activate our syndicated audiences on-the-shelf of most major platforms. For a full list of Experian’s syndicated audiences and activation destinations, download our syndicated audiences guide. Explore our other seasonal audiences that you can activate today. View now Footnotes Online survey conducted in June, 2024 among n=1,000 U.S. adults 18+. Sample balanced to look like the general population on key demographics (age, gender, household income, ethnicity, and region). n = 204 Gen Z, n = 234 Millennials, n = 270 Gen X, n = 272 Baby Boomers. Online survey. Online survey. “Fair Lending Friendly” indicates data fields that Experian has made available without use of certain demographic attributes that may increase the likelihood of discriminatory practices prohibited by the Fair Housing Act (“FHA”) and Equal Credit Opportunity Act (“ECOA”). These excluded attributes include, but may not be limited to, race, color, religion, national origin, sex, marital status, age, disability, handicap, family status, ancestry, sexual orientation, unfavorable military discharge, and gender. Experian’s provision of Fair Lending Friendly indicators does not constitute legal advice or otherwise assures your compliance with the FHA, ECOA, or any other applicable laws. Clients should seek legal advice with respect to your use of data in connection with lending decisions or application and compliance with applicable laws. Appendix Here are the complete audience segment names (taxonomy paths) for all audience segments discussed in this blog post. Holiday shopping styles Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Last-Minute Holiday Shoppers Retail Shoppers: Purchased Based > Seasonal > Holiday Shoppers: One Stop Holiday Shoppers/Power Shoppers: In-Store Retail Shoppers: Purchased Based > Seasonal > Holiday Shoppers: One Stop Holiday Shoppers/Power Shoppers: Online TrueTouch: Communication Preferences > Purchase Behavior > Impulse buyers Retail Shoppers: Purchase behavior > Shopping Behavior > In-Store vs. Online: eCommerce Diehards Retail Shoppers: Purchase behavior > Shopping Behavior > In-Store vs. Online: Brick & Mortar Diehards Discount-seeking shoppers NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Cyber Monday NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Black Friday NEW! Retail Shopper: Purchase Based > Seasonal > Holiday Shoppers: Big Box/Club Stores Shoppers NEW! Retail Shoppers: Purchase Based >> Discount Holiday Shoppers NEW! Retail Shoppers: Purchased Based > Shopping Behavior > Online Coupon Users TrueTouch: Communication Preferences> Purchase Behavior > Online Coupon Site Retail Shoppers: Purchased Based > Shopping Behavior > Department Store Deal Shoppers Online Spenders Retail Shoppers: Purchased Based > Shopping Behavior > Department Store Deal Shoppers In-Store Spenders Retail Shoppers: Purchased Based > Seasonal > Holiday Shoppers: Post holiday Gift givers NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Luxury Gift Shoppers NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: High Spenders NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Moderate Spenders NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Charitable Donations Retail Shoppers: Purchase Based > Shopping Behavior > Gift Shoppers High Spend Spenders Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Heavy Buyer/Spenders: Online Retail Shoppers: Purchase Based > Seasonal > Holiday Shoppers: Heavy Buyer/Spenders: In Store Holiday travelers NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday International Travelers NEW! Retail Shoppers: Purchase Based > Seasonal> Holiday Travel-Train NEW! Retail Shoppers: Purchase Based > Seasonal > Holiday Budget Savvy Airline Travelers Retail Shoppers: Purchase Based > Travel > Vacation/Leisure Travelers: Domestic Trips Lifestyle and Interests (Affinity) > Travelers > Air Travel (FLA/Fair Lending Friendly) Retail Shoppers: Purchase Based > Travel > Vacation/Leisure Travelers: Frequent Spenders Retail Shoppers: Purchase Based > Travel > Hotels: Frequent Spend Latest posts

Aug 15,2024 by Lucy Simmonds

An interview with Webbula’s Jordan Feivelson, Vice President of Digital Audiences

In our Ask the Expert Series, we interview leaders from our partner organizations who are helping to lead their brands to new heights in ad tech. Today’s interview is with Jordan Feivelson, VP, Digital Audiences at Webbula. Jordan is a 22-year advertising industry veteran who has worked for media properties such as WebMD and Disney. Over the past ten years, he has transitioned to the data and programmatic space, including growing the data business for Kantar Shopcom and Adstra.  What types of advertisers might benefit from utilizing Webbula audiences across various verticals? Can you provide examples of how different industries successfully leverage your data to achieve specific campaign goals?  Most advertisers can leverage Webbula’s award-winning attributes for their activation initiatives. Webbula offers approximately 3,000 syndicated segments covering categories such as Demographics, Automotive, Political, Mortgage, B2B, Hobby/Interest/Lifestyle, and Interests & Brand Preferences (brand name targeting).  Audience insights and marketing strategies  What specific types of audience segments does Webbula provide? How can advertisers leverage these segments to craft more effective, personalized marketing strategies?   Webbula has incredible depth and breadth within its verticals, giving marketers the tools to deliver targeted messaging effectively. Our Demographic, B2B, Mortgage, Automotive, and Interest and Brand Preferences segments each contain 500-1,000 segments, all built on deterministic, self-reported, and individually linked data. We ensure the best accuracy with multiple deterministic data points tied to the real world (ex., first name, last name, postal address, and email address).   Some examples of our unique syndicated audience types:  B2B: A view of the latest industry trends with detailed cuts of the professional world, such as companies with and not within the Fortune 500 companies and job positions that are directors and below. This also includes custom capabilities, including ABM (list of target companies in an activation campaign or by industry code (ex. NAICS, SIC).   Interest and Brand Preferences: Consumers who have shown interest and affinity to hundreds of brands (ex., Nike), genres (ex., comedy, hip hop), sports teams, and more.  Mortgage: A detailed view of homebuyers’ purchase range, loan type (ex. jumbo loan, standard loan), mortgage amount, interest rate, and more.   With Webbula’s audience data, brands can create a comprehensive picture of their audiences down to the individual level and reach them accurately.   Data quality, sourcing, and differentiation  How is consumer data sourced and curated at Webbula? Are there data quality standards that Webbula establishes for consumer data, and how do you ensure your sources and methods meet these standards consistently?   Webbula’s data is aggregated from over 110 trusted and authenticated sources, including publishers, data partners, social media, and more. The data collected comes directly from consumers who self-report information through surveys and other methods. We apply our hygiene filters to mitigate fraud and accurately score the data.  Data Collection: The data collected comes directly from consumers who self-report information through surveys, questionnaires, transactions, and sign-ups. This ensures that brands display ads to audiences based on self-identified, cross-channel behaviors, not modeled assumptions.  Hygiene Solutions: Webbula applies multi-method hygiene solutions to mitigate fraud and accurately score the data before onboarding, ensuring that all data meets the highest quality standards.  Examples of Data Sources:  Questionnaires: Self-reported data through surveys, offer submissions, and telemarketing.  Transactions: Deterministic data from aftermarket parts, online purchases or services, and more.  Sign-ups: Individually linked data from information entered through sweepstakes, infomercials, newsletters, and forms.  What differentiates Webbula's data from other data providers in the market? Can you explain the unique value proposition that Webbula offers in terms of data depth and breadth?   Due to our extensive experience in data cleansing, we provide the most accurate data within the programmatic ecosystem. TruthSet, the leading programmatic accuracy measurement company, has ranked Webbula as having the highest number of top attributes compared to other data providers with 150M+ HEMs. Additionally, Publicis Groupe and Neutronian further validate Webbula's data quality, underscoring its position as a leader in the industry.  Webbula's data stands out in the market due to its unmatched accuracy and quality, achieved through years of expertise in data cleansing. Unlike other providers, Webbula’s foundation lies in its robust email hygiene process, ensuring that all data entering the programmatic ecosystem is thoroughly cleansed.   Privacy, compliance, and future-proofing  What measures does Webbula take to maintain data privacy and compliance? How do these efforts benefit advertisers in an evolving regulatory landscape and ensure ethical standards?   Webbula was created over a decade ago with a future-proof, privacy-compliant foundation. We understand the industry’s rapid changes, including government and state legislation and cookie depreciation. Our goal has always been to build long-term partnerships and ensure we are prepared for industry changes. We rely on validated offline data sources, making us resilient to external influences.  Success stories  Can you share success stories where advertisers saw significant campaign improvements using Webbula’s data? What were the key factors that contributed to these successes?   Our success is measured by client feedback and increased client spend. Webbula has helped several key advertisers achieve six-figure monthly thresholds by providing the most accurate data to meet campaign KPIs. Clients consistently return to use our data, validating our belief that “the proof is in the pudding.”  Thanks for the interview. Any recommendations for our readers if they want to learn more?  For those interested in learning more about Webbula, reach out for a personalized consultation. Contact us Latest posts

Aug 13,2024 by Experian Marketing Services

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