Real-Time Segmentation and Personalization: BDEX for the Email Marketer

Modern email marketers struggle with low open and click-through rates, with just 3.26% of email subscribers clicking on email offers. Perhaps even more frustratingly, few marketers have the right tools to integrate email marketing insights with other sources of data. Marketing Sherpa has found that data integration to segment contacts and perform lead-to-customer analyses is modern email marketer’s greatest challenge. Deliverability, retaining subscribers, and achieving measurable ROI are other primary pain points.

List segmentation and relevance are the most important keys to email marketing success at organizations of any size, according to industry-wide surveys of marketing professionals. Best-of-class email marketers rely on multiple personalization techniques, including behaviorally-triggered campaigns, dynamic personalized content, and advanced segmentation to deliver the most relevant messaging possible.

Delivering the right email messages to your subscribers at the right times requires effective data integrations with CRM, marketing software, and third-party big data insights. Join us as we explore how 3rd-party data exchange can significantly improve email marketer’s campaign performance metrics.


Big Data Insights for Effective Email Segmentation

Over half of Fortune 500 marketers are relying on existing email marketing metrics and gut instincts to optimize campaigns. Companies that use email segmentation effectively have 39% higher open rates and 28% fewer unsubscribes. However, the marketing insights in your email marketing platform or data management tool aren’t necessarily an effective indicator of your contact’s current needs. Aspects of consumer identity and needs triggered by life events can drastically change, making your previously relevant email offers completely irrelevant.

Email marketing expert Mike Hotz writes that the four following types of data are, at a minimum, required to create effective, behaviorally-based email segments:

Email interaction
Web interaction
Purchase (transactional) data
Identity/Demographic Data


However, as Hotz highlights, “refreshing and reevaluating” your segment data is critical. Identity data from your CRM software that indicates possible need may not be trustworthy, based on the age of your insights. The only way to create genuinely up-to-date email segments is to capture recent interactivity, purchase, and identity data from across multiple devices through third-party data exchange. Segmentation is only an effective tool if it’s reflective of your contact’s current pain points and priorities.

Email Personalization With Data

For many brands, consumer adoption of mobile technologies has drastically shortened the sales cycle. Consumers can research, select, and make purchases in a matter of seconds. As the American Marketing Association writes, marketers increasingly need to target mobile moments, where consumers act upon needs or wants based on a literal glance at their smartphone. Delivering relevant email communications during these micro-moments of need can allow marketers to truly connect with their contacts.

Leading email marketers understand that access to recent, cross-platform data insights is necessary to build accurate contact segments and deliver appropriately relevant messaging. By integrating your marketing data management platform with the BDEX Data Exchange Platform, you can gain unprecedented insights into your consumer’s needs and preferences now. You’ll no longer be reliant on email marketing metrics from last quarter.

To learn more about the BDEX impact on marketing, check out Real-TIme Data Insights for AdTech: Effectively Targeting Micro-Moments.


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BDEX presenting at the Emerging Technologies & Business Showcase


BDEX is honored to be chosen to present at this year’s Emerging Technologies & Business Showcase hosted by the Florida Venture Forum.

Florida Venture Forum, Space Florida, and Enterprise Development Corp of South Florida have selected twenty-four Florida-based companies to present at the Emerging Technologies & Business Showcase (ETBS), to be held at the Hyatt Regency in Coral Gables on November 4.

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Real-Time Data Insights for Adtech: Effectively Targeting Micro-Moments


Despite a habit of early adoption in the Adtech space, conversion in this $133 billion-dollar industry isn’t getting any easier. Smart Insights recently reported the average click-through rate (CTR) for display ads is just 0.1%, though averages are higher for rich media advertising. Adtech professionals are struggling to become more competitive in light of changing consumer expectations and increased consumer adoption of ad blocking technologies. The adtech pros who succeed are taking a deep dive into big data technologies for improved targeting.

Consumer needs and preferences can change minute-by-minute, and adtech professionals need access to up-to-date insights on “behaviors, lifestyles, actions, motivations, and other factors” to generate precisely the right offers at the right time. Remaining competitive in adtech requires insights that are minutes or seconds old, not months or years. In this article, we’ll examine why real-time data exchange and the Data Exchange Platform (DXP) is necessary to micro-targeting, segmentation, personalization and other emerging trends in adtech.


Why Micro-Moments Matter

Google Vice President Sridhar Ramaswamy wrote recently that the adtech industry has a tendency to focus on the wrong things entirely. “Micro-moments,” defined as the points in time when consumers perform “short bursts of digital activity” are increasingly common among individuals with access to mobile and internet technologies. Delayed gratification is becoming increasingly scarce for consumers who can research, compare, and purchase products while waiting for the subway during their morning commute.

Unless brands have the ability to present perfectly relevant offers during these micro-moments, they’re unlikely to connect with the 69% of consumers who admit that quality, timing, and relevance are key purchase factors.


Big Data for Micro-Targeting and Personalization

Being able to identify and present advertising that’s targeted towards consumer preferences in micro-moments requires access to real-time, cross-platform insights that can paint an entire picture of consumers. Grouping consumers by demographics via traditional data vendors in your data management platform isn’t sufficient for today’s customers, who may book a trip abroad while waiting for dinner at a restaurant. Months-old segments based on your DMP vendor’s desktop browsing data won’t allow you to capture the interest of consumers who’ve already spent their annual vacation budget via smartphone. Targeting consumers during micro-moments requires a comprehensive understanding that’s only possible through real-time data exchange.

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The Power of the Data Exchange: 3 Ways Retailers are Winning with Big Data Insights


With an average website visitor conversion rate of just 3%, retailers struggle to convert sales. Online retailers lose an estimated $18 billion in revenue annually due to last-minute cart abandonment. Remarketing, the use of real-time insights to provide targeted recommendations, is just one effective big data methodology that can yield a 55% increase in spend from cart abandoners.


Few industries are more impacted by quickly-changing consumer trends than retail. The complexity of consumer preferences means that big data is “especially promising and differentiating” for organizations in this sector, according to IBM’s Rebecca Shockley and Keith Mercier. In a retail environment where consumers take a multi-channel approach to product selection and purchase, creating a 360-degree view of target customers is particularly critical to retaining business.


62 percent of retailers report that increased adoption of analytics is creating a competitive advantage. While retail adoption of third-party data actually lags slightly behind other industries, retailers who optimize for modern cross-channel shoppers are likely to gain an immense lead.  In this article, we’ll explore some ways that modern retailers are utilizing big data insights to understand cross-channel behaviors and create a targeted customer experience.


Understanding Modern Cross-Channel Shoppers

Retailers are struggling to create complete pictures of today’s multi-channel customers, according to eMarketer. 35% of marketers report they just “don’t understand” a customer’s journey. Retail companies struggle to understand how customers behave on mobile, desktops, and at brick-and-mortar locations. In an age where over 40% of adults are multi-screen users, fragmented or incomplete data insights can severely inhibit effective targeting.


The BDEX Data Exchange Platform (DXP) can assist retailers in understanding the customer’s journey, even if their product research takes place across multiple channels or devices. Customer behavioral data, first and third-party transactional insights, and even online product reviews can facilitate a multivariate understanding of what is most likely to convert. With access to a wide array of insights, retailers can gain the right insights to correctly target consumers the first time they land on a website.


Retailers are increasingly discovering that analytics, given access to the right third-party data insights via the Data Exchange Platform, can be a powerful tool for understanding complex consumer behaviors. Retail optimization has always been a complex science, but being able to incorporate a broader range of data sets can allow marketers to finally uncover a complete picture of customer behaviors.


Analytics-Driven Targeting

Predicting the preferences and needs of consumers is a challenge across industries, from entertainment to retail. Big data evangelist James Kobielus describes the complexity of modeling the quicksilver nature of human preferences, or zeitgeist, due to the “fickleness of taste.” Retailers are especially well situated to utilize “experience analytics” to predict how demographic preferences can change, and target offers accordingly.
Three examples of experience analytics relevant to retail include:

  • Life-event detection: The detection of marriage, pregnancy, or other events that can drastically change retail habits via analysis of behavioral and identity data.
  • Behavioral pricing: Using a combination of consumer transaction history, behavior, and other qualitative insights to predict deals that are most likely to elicit a positive response.
  • Psycholinguistic Analytics: An algorithm which works to detect patterns in human language and social media behavior to uncover probable consumer preferences.


For retailers to achieve success with any analytics project or initiative, obtaining sufficient third-party insights is crucial. Without identity, descriptive, qualitative, and quantitative data insights, retail analytics teams will be unable to uncover sufficient patterns to predict purchase behavior and target offers. The retailers today who gain a significant edge on their competitors are those with the ability to procure enough accurate and recent third-party insights on their target markets.


The Data Exchange Platform (DXP) provides retailers with the ability to purchase minutes-old insights on the right consumers, creating a rich understanding of who they’re trying to sell to. Consumer behavior is complex, and data exchange can be a powerful tool for obtaining the right insights. By purchasing fresh and quality-scored insights in a true marketplace environment, retailers can ensure they’re gaining access to actionable data.


Retail analytics is only as effective as your big data procurement. For more information on the buyer benefits associated with the BDEX Data Exchange Platform, check out Exiting the Black Box Mentality: How the Data Exchange Platform Can Benefit the Buyer.


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Exiting the Black Box Mentality: How The Data Exchange Platform Can Benefit the Buyer

Marketing teams worldwide will increase spend on analytics 83% over the next three years, according to the most recent report from CMOSurvey.


Despite these plans to increasingly integrate big data analytics in projects, CMOSurvey indicates that marketers are struggling with a host of issues, including a pervasively limited return on investment. Despite spending increases on data insights, the majority of marketers report a low-to-moderate impact on project outcomes.  Most companies perform no formal evaluation of their analytics efforts or big data quality, and B2B marketers are nearly twice as likely to integrate measurement as professionals in the B2C space.


It’s safe to assume that data-driven marketers recognize that big data quality is closely tied to outcomes, but lack practical and convenient means of measurement. In fact, many of the most common challenges are directly tied to these companies data procurement methods, which can facilitate a lack of trust and testability.


Common Challenges in Marketing Analytics Initiatives


Insights from research firm Spencer Stuart indicate that out of over 1,000 marketing leaders surveyed worldwide, the following challenges were most commonly reported:

  • 32% struggle with trusting in “black box” analytics.
  • 18% are limited by “indirect” data channels that make collection difficult.
  • 13% find limited applicability in big data to traditional advertising methods.
  • 12% are unable to predict the outcomes of “creative ideas,” which could be connected to a lack of unbiased scoring on existing data sets or metadata on insight freshness.


Most of these analytical marketing leaders are combining first and third-party insights in a data management platform (DMP). While the DMP may be considered a leading solution by marketing teams, they can contribute to perceptions of analytics as a “black box” methodology. Inconsistent results and a lack of unbiased data quality scoring from third-party vendors compounds poor trust factors. While marketers understand the potential of big data analytics, they’re unable to drive these results with existing tools and vendors.


How Buyers Benefit from a Data Exchange Environment


Marketers have the budget to procure the right data insights, but available resources often cause their projects to fall short of ambitious conversion goals. In the age of big data, companies should understand their rights as buyers, and advocate for their teams to procure sufficiently fresh and quality insights.


Simply put, there is no shortage of data insights available to companies with a budget for analytics initiatives. Consumer data simply isn’t a limited resource or a highly-prized commodity. By moving towards a model of data exchange, buyers can eliminate artificial barriers to necessary insights for success. The Data Exchange Platform (DXP) can be integrated with existing data management platforms, providing teams with the ability to:


  • Buy insights that are seconds, not months, old.
  • Filter prospective data sellers by unbiased, third-party scoring of resulting conversions.
  • Create robust, comprehensive customer profiles based on qualitative, quantitative, identity, and behavioral insights and continue optimizing audience groups.
  • Continue adding and subtracting data insights from multiple vendors, according to project budget.
  • Take an iterative, agile approach to customer profiling to meet program targets.


By removing artificial barriers between data vendors and prospective buyers, marketers can eliminate the lack of transparency and options which damage analytics projects. Instead of purchasing from data brokers or aggregators, buyers can access real-time data directly from the source. In an age where each click online contributes to vast stores of knowledge on consumer identity, behavior and preferences, marketers shouldn’t face difficulty in data procurement. In fact, the abundance of big data insights should create a market in which buyers are able to advocate for their rights to high-quality insights.


For more information on how the BDEX Data Exchange Platform (DXP) can increase transparency and trust in marketing analytics initiatives, contact us today.


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