At A Glance
Consumer behavior shifts faster than traditional model inputs can track it, which leaves marketers spending against audiences that are less likely to respond. Experian's AI enhanced modeling applies AI to find and validate stronger predictive signals across our existing data and audience products, producing a 10% average model lift across hundreds of models. For marketers, that means better targeting and less wasted spend, without a new workflow.Consumer behavior keeps shifting across channels, and the signals that point to your most relevant audience aren’t always obvious. Experian’s AI enhanced modeling applies AI to find and validate stronger predictive signals across our data and modeling technology, so marketers can reach higher-potential consumers with less wasted spend.
A consumer may not fit an expected profile exactly, but still show behaviors that suggest strong relevance for a campaign, product, or offer. When audience strategies rely too heavily on static or less predictive signals, marketers can miss valuable opportunities, spend against less relevant consumers, and increase the risk of audience fatigue.
Stronger audience strategies start with stronger model inputs. This article looks at why signal quality matters, what better model inputs can mean for audience performance, and how AI can help identify more useful predictive patterns.
Why do traditional attributes alone leave opportunity on the table?
Traditional attributes, like demographic and static data, remain valuable. They help marketers understand who consumers are, how they live, and what they may care about.
Audience relevance is typically influenced by a combination of attributes rather than any single factor. A consumer may not match an obvious buyer profile yet still show signals that suggest they are likely to act. When audience strategies rely too heavily on familiar or less predictive signals, marketers may overlook high-potential consumers and continue spending against audiences that are less likely to respond. That can limit reach, reduce efficiency, and increase audience fatigue.
Advances in AI and modeling are helping marketers move beyond obvious or static signals toward more current, actionable audience intelligence, improving model performance, and strengthening the predictive power that supports better marketer outcomes. By making it easier to test more combinations and compare which inputs are more likely to predict a desired outcome, AI can help turn hidden patterns into useful signals for audience planning and activation.
How does AI find more useful predictive patterns?
AI helps modeling teams identify meaningful combinations and transformations of data signals that can be difficult to find through manual data science work alone. It surfaces correlations, suggests signal combinations, and accelerates the review of possible model inputs. That gives modeling teams a faster way to design, test, and compare more potential predictors for a defined objective.
AI also gives modeling teams another way to look at the data. Every data scientist brings valuable experience, context, and judgment to model development, but all people also bring their own perspectives and blind spots. AI can supplement that expertise by suggesting feature combinations or data patterns the team may not have known to explore.
In that way, AI acts less like a replacement for human expertise and more like an added team member. It introduces new possibilities, expands the range of inputs under consideration, and helps modeling teams see relationships that may not be obvious at the start.
Those suggestions still require human review, testing, and validation, but they can help data scientists learn from the data in new ways and produce stronger outcomes for marketers. For marketers, better inputs mean audiences that reflect current behaviors, interests, purchase patterns, and intent more accurately, which supports stronger campaign performance and better outcomes.
More data only matters when it leads to better signals. AI helps prioritize validated signals that improve predictive outcomes, rather than expanding inputs without a clear purpose. AI models can help identify nonlinear interactions and subtle patterns that may otherwise go unnoticed. With the right data foundation and validation process, those patterns can become stronger model features that support more relevant audiences.
Why does data quality determine AI model performance?
AI is only as useful as the data behind it. Predictive modeling depends on accurate, compliant, expansive, and relevant data. Strong signals need to be tested against known seed or deterministic data, which gives models a reliable benchmark for comparison. That validation is what separates useful predictive signals from interesting patterns.
By applying these AI-driven advancements to our modeling approach, Experian has seen a 10% average model lift across hundreds of models, validated against known seed or deterministic data.
For marketers, these improvements can translate into more efficient and effective outcomes across the use cases they rely on. With more predictive models powering audience inputs and decisions across planning, enrichment, modeling, onboarding, and activation, marketers can focus efforts on higher-potential consumers and move more quickly toward their goals.
What do stronger signals mean for marketers?
More useful predictive signals help marketers focus effort and spend on consumers who are more likely to match a desired outcome, such as purchase, response, retention, or upsell.
This is where Experian’s AI enhanced modeling comes in. AI enhanced modeling is built into our data foundation and modeling technology that applies AI to identify and test more predictive, current, and actionable signals across our data and audience products.
As part of our data foundation, AI enhanced modeling:
For marketers, this means better model outcomes across the use cases and applications you already rely on, including onboarding, modeling, Enrichment, Marketing Attributes, and audience activation, without adopting a new workflow.
How does AI improve model development speed and performance?
Consumer behavior will keep shifting, so audience strategies need model inputs that capture those changes and show marketers which consumers are more likely to act.
AI uncovers signal combinations that traditional exploration may miss, analyzes large and diverse data sets, and compares potential predictors faster. When paired with strong data, modeling expertise, and validation, these inputs support better model performance and more relevant audience decisions.
Our AI enhanced modeling brings together AI, data, identity, modeling expertise, and validation to identify more predictive, current, and actionable signals across the products and use cases you already rely on. This gives you better audience intelligence, more relevant activation, and stronger marketing performance, with responsible data use built into the process.
To see how AI enhanced modeling can strengthen your predictive audiences, talk to our team today.
About the author
Jeremy Meade
VP, Data Operations & Governance, Experian
Jeremy Meade is VP, Data Operations & Governance, at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies.
FAQs
Experian AI enhanced modeling is our approach to applying AI within our existing data foundation and modeling technology. It identifies and tests more predictive, current, and actionable signals across our data and audience products, without requiring a new workflow.
Experian AI enhanced modeling has produced a 10% average model lift across hundreds of models, validated against known seed and deterministic data.
Experian AI enhanced modeling doesn’t replace human data scientists. AI surfaces signal combinations and patterns a team might not think to test. Every suggestion still goes through human review, testing, and validation before it becomes part of a model.
Experian AI enhanced modeling strengthens existing use cases across onboarding, modeling, Enrichment, Marketing Attributes, and audience activation, using the workflows marketers already rely on.
Latest posts
With the long-term effects to the economy unknown, many consumers are feeling the financial impact, while others are looking for opportunities, resulting in a transformational shift in spending. Some brands are experiencing decreased or paused marketing budgets, and you may be trepidatious about making the right decisions in your efforts to grow share of wallet. Recent events have been an impetus for change and we’re seeing brands make modifications to traditional marketing strategies. Some are developing innovative technologies and utilizing new sources of data and analytics. As we look at how these changes impact marketing results, we see the gap grow between those brands who are equipped to pivot and implement new strategies quickly, versus those who are not. So what steps can your organization implement now to make the smartest choices for both your customers and your business to secure more share of wallet? Here are four ideas to accelerate the success of your next financial marketing campaign: 1. Meet your customers wherever they are: Digital-first strategies have never been more relevant than they are right now. While consumers have fully embraced online engagement, marketers are even more focused on reaching high-value segments in the channels they utilize. By using an informed, data-driven strategy that includes preferred marketing communication channels and decision-making styles, engagement increases across those channels your target audience frequents the most. For example, are they heavy social media users? Do they prefer streaming TV? Or do they tend to rely on financial advice vs. performing their own research? To drive take rates, your audience must be exposed to a tailored message, in the right channel, and possibly multiple times. 2. Use messaging that resonates: As consumers refocus priorities, their expectations of brands with whom they do business are ever-increasing. Reflecting an understanding of the current needs and interests of your customers and prospects is an undertone that can only help strengthen their view of your brand. Consumer behavior has changed and is unlikely to revert to what was, so you want to be relevant, but you also do not want to be seen as ‘tone deaf’. As a result, consider revising your segmentation strategy to leverage predictive insights, such as household economic indicators, financial behaviors, lifestyle propensities and interests to help shape your message into one that truly makes an impact. 3. Prove the worth of your campaign: New consumer journeys are being formulated and showing ROI is imperative as your marketing budget is scrutinized. Having the right industry-relevant metrics and reports to analyze and share with leadership are key. Demonstrate that your campaigns are contributing to bottom-line success—and justify future campaigns—by using data-driven measurement insights collected across multiple reads and countless touchpoints. Marketing budgets are being scrutinized now more than ever, so showing ROI is critical. Having the right metrics and reports to analyze and share with leadership are key. 4. Follow government regulations—leverage Fair Lending-friendly audiences: Whether you’re cross-selling or prospecting, now is the time to identify the right audiences with rich data insights to not only execute impactful campaigns but adhere to government regulations that protect consumers and your organization. Trusting that the data you are activating follows Fair Lending Laws, including the Equal Credit Opportunity Act (“ECOA”) and the Fair Housing Act (“FHA”) is crucial. The Federal ECOA prohibits creditors from discriminating against credit applicants on the basis of several prohibited factors. Developing people-based segments that are not derived using these factors positions you to follow these regulations. Check out our previous blog post about Fair Lending-friendly audiences here. As you transition to new operating models, access to current and accurate consumer data can provide confidence in campaign potential, help you avoid business risk, enable you to respond to market changes and make better decisions. Experian can help you implement these strategies and put your brand unique position for growth. From start to finish, we provide the marketing solutions you need to plan, build and execute successful, Fair Lending-friendly campaigns to cross-sell to existing customers and acquire new customers. *Experian Fair Lending-friendly audiences do not constitute legal advice or otherwise assure compliance with the FHA, ECOA, or any other applicable laws. It’s recommended to seek legal advice with respect to the use of data in connection with lending decisions or application and compliance with applicable laws. Contact us today
Cross-device matching and pixel-based foot traffic attribution reporting empower digital marketers with greater control of location-based campaigns.RALEIGH, N.C. (PRWEB) AUGUST 04, 2020 Tapad, part of Experian a global leader in digital identity resolution, and Reveal Mobile, a leader in location-based marketing, today announced a collaboration that combines Tapad’s digital cross-device matching technology and pixel-based attribution features with Reveal Mobile’s VISIT Local, the software that hundreds of digital agencies and brands use for location-based analytics. The partnership is designed to drive improved performance by optimizing ad targeting and messaging for location-based campaigns. Powered by Tapad’s privacy-safe cross device matching, marketers using VISIT Local to power location-based campaigns can enhance how they reach shoppers. When one member of a household shops for groceries, clothes, household goods or any other consumer item, a conversation between multiple members of the household typically takes place beforehand. With cross device matching, marketers can reach everyone who has influence over what to buy and where to buy it. VISIT Local users can expand location-based services with a single click to include devices that share the same household, including targeting across multiple devices owned by the same user, allowing advertisers to maximize messaging and increase their share of wallet among consumers. “VISIT Local has always given our customers access to high-intent location-based audiences. With the addition of cross device matching from Tapad, advertisers can boost audience sizes up to 300 percent while maintaining full confidence in quality and relevance,” says Brian Handly, CEO of Reveal Mobile. “VISIT Local users can now apply multiple criteria and attributes to a single location-based audience, giving them the advanced control and transparency they need.” As reliable attribution becomes increasingly complex for marketers and ad buyers who need to prove value, the addition of Tapad’s pixel-based foot traffic attribution to VISIT Local enables the measurement of actual campaign effectiveness by tying ad views to in-store foot traffic. This new feature, which will be available in VISIT Local this fall, lets Reveal Mobile customers understand who visited a retail location as a result of being served an ad, providing a more accurate view into return on ad spend during and after advertising campaigns. “Tapad’s goal is to empower marketers with digital advertising efficiencies at scale across devices,” says Mark Connon, COO of Tapad. “With cross device matching and pixel-based foot traffic attribution, marketers using VISIT Local can better address the consumer’s preferences and habits, and deliver them consistently actionable information on user behavior. These capabilities advance location-based advertising in ways marketers need and want.” In addition to these new features, VISIT Local’s location-based audience builder now enables marketers to create custom audiences made up of people who have visited different places on different dates. This gives VISIT Local users the ability to segment and create the most highly targeted audiences possible. For example, a marketer who wants to advertise for a chain of restaurants can easily target visitors of different competitors in different cities. Or a marketer who wants to advertise vacation destinations can target people who have been to various resorts at different times of year. Or a marketer who wants to advertise the release of new music can target people who have been to concert venues in different cities on different dates. “Many of our customers need to create highly custom audiences so they can run experiments, test messaging, and run increasingly competitive campaigns,” says Handly. “Everyone who uses VISIT Local can now apply multiple criteria and attributes to a single location-based audience, giving them the advanced control and transparency they need.”To learn more about Tapad’s digital identity resolution products, visit our identity solution page. To learn more about Reveal Mobile’s location-based marketing offerings, visit http://www.revealmobile.com. About TapadTapad, Inc. is a global leader in digital identity resolution. The Tapad Graph, and its related solutions, provide a transparent, privacy-safe approach connecting brands to consumers through their devices globally. Our one-of-a-kind Graph Select offering enables marketers the flexibility and freedom of choice to correlate devices to varied objectives, driving campaign effectiveness and business results. Tapad is recognized across the industry for its product innovation, workplace culture and talent, and has earned numerous awards including One World Identity’s 2019 Top 100 Influencers in Identity Award. Headquartered in New York, Tapad also has offices in Chicago, London, Oslo, Singapore and Tokyo. About Reveal MobileReveal Mobile is a leader in location-based marketing, analytics, audiences, and attribution. Creator of VISIT Local, VISIT Match and VISIT Data, the company’s products help digital agencies, brands and retailers of any size leverage location data to understand and reach the right audiences. Reveal Mobile is CCPA compliant and a member of the Network Advertising Initiative, which conducts an annual privacy certification. The company is based in Raleigh, NC. For more information, visit https://revealmobile.com. Contact us today
Overview Chartable leverages The Tapad Graph to improve cross-device attribution rates and remove non-addressable IPs for clients. Challenge Chartable needs to differentiate between consumer and potential business IP addresses to provide accurate household modeling and reduce excess data for their customers. Podcasting generally only has access to IP addresses as a form of digital ID which limits its ability to connect activity to individuals and extend it across all devices. The Tapad + Experian solution Using Tapad, now a part of Experian, Chartable is able to cut through the noise of IP data and discard any addresses deemed a shared IP or business. Then, Tapad + Experian connects individual users to their other digital IDs and users in their household; creating a richer attribution model for Chartable customers. Increase in podcast attribution rates Contact us today