The way we use data to target audiences is constantly evolving. The first phase in targeting was fairly simple in that we relied on only a few simple demographics, like age and gender, to segment consumers. Then audience groups were formed. More advanced and specific, audience groups were, and still are, based on consumers’ shared interests. The newest chapter in data targeting, utilizing real-time insights, merges information about demographics and audience groups with real-time activity. But that’s just the tip of the iceberg. Real-time data isn’t just information about your consumers’ spending habits in the last month. True, real-time insights let you know what your target customers are searching for the moment they shop online.
In the mid-20th century, marketers focused on only a few consumer demographics when developing marketing campaigns. While factors like age and gender were more important sixty years ago when people sourced their news and entertainment from the same place, the traditional methods for obtaining consumer data are not as relevant anymore. McKinsey’s John Forsythe demonstrates the problems associated with using only a few, superficial demographics by citing the differences between Prince Charles, Queen Elizabeth’s son and her heir apparent, and Ozzy Osbourne, lead singer of heavy metal band Black Sabbath. While both men are British and the same age, a marketer obviously wouldn’t market to them the same way.
Marketing and brand expert Adam Paulisick also believes that simple demographics don’t provide enough information to properly target consumers.
“Segmenting consumers by age and gender or other demographics is inefficient at best, even for more traditional marketing campaigns because there are no hard and fast rules anymore for what a man or a women will intuitively buy (with few exceptions).”
While we might not know the “hard and fast rules” that drive what a consumer buys, we can know the next best thing: what product they are shopping for the moment they shop. Real-time data takes into account everything we used to know about consumers based on demographics and audience groups and merges it with live activity.
Keith Sayewitz, Chief Marketing Officer and Head of Sales at BDEX, a market-driven exchange platform that provides users with real-time data, explains the value of real-time analytics for marketers.
“For years a company depended on simple demographics to identify a certain consumer, like ‘soccer moms.’ Then audience groups were formed, so we discovered those soccer moms were interested in fitness. But now, with real-time data, we learn which of those soccer moms are in the market for a treadmill or are switching to vegan cuisine. This information is incredibly powerful because it allows for truly advanced targeting. We know that this customer is likely to buy a treadmill because she is in the market for one at this exact moment.”
Marketers can then create specific ads for the desired consumer, increase the probability for conversion, and, therefore, create more sales. The insights provided by real-time data are essential to brands, retailers, and agencies who want to stay up-to-date on consumer activities and truly understand their customers’ needs.
BDEX, the first ever Data Exchange Platform (DXP), is currently the only source for true, real-time data. For more information about BDEX’s unique services, click here.
Image Credit: NEC Corporation of America
Marketers understand that you simply can’t build audience groups on pure demographic factors. After all, Prince Charles of England and rocker Ozzy Osbourne are both British males of the same approximate age. However, it’s safe to say that a marketing message tailored for Ozzy wouldn’t necessarily convert the heir apparent, Prince Charles. Consumer preferences, motivations, and needs play a critical role in purchase decisions.
It’s clear that audience groups must be more sophisticated than demographics. Even deep demographic factors like income or family status don’t tell the full story. As Harvard Business Review’s (HBR) highlights, the sorts of audience groups that convert are rarely “created.” Instead, they’re “uncovered” through data analysis that incorporates behavioral clues from cookies, web analytics, user-generated content, and other big data sources.
Why Your Audience Groups aren’t Converting
Despite the fact that marketers understand what’s required to build audience groups, too few brands have segments that reflect reality. Information Week recently wrote about some of the “perils” of big data analysis biases, which can include:
● Selection Bias
● Inclusion of Outliers
● Overfitting and Underfitting
● Confirmation Bias
The term “data scientist” is ultimately accurate. To accurately understand patterns in reality, marketing teams must leverage enormous amounts of data to control against faulty results. If your big data audience segments are based on false positives from too-small or incomplete data sets, you could be suffering as a result. In one anonymous case study detailed by Information Week, a brand’s profit margin decreased significantly as a result of audience groups’ creation that didn’t control for bias.
Do You Trust Your Audience Analysis Methods?
Many marketers have developed some level of big data fluency. They understand some common analysis methods used to develop audience groups, such as clustering or linear analysis. Undergraduate studies of statistics has leant familiarity with concepts like sample size and statistical significance. An abundance of easy-to-use analytics tools allows marketers without extensive technology backgrounds to perform complex analyses in a point-and-click environment. However, a lack of big data resources has forced many marketing teams to rely on pre-formed audience groups from 3rd party vendors that are questionable in accuracy.
One large-scale study by HBR indicated that some 85% of product launches fail because of poor segmentation methods. Ineffective segmentation can have a significant impact on your brand’s profitability and outcomes. If you’re reliant on pre-packaged audience groups that you’ve purchased from a 3rd-party vendor, it’s likely time to refresh your segments. Join us as we review a new approach to building audience groups that convert.
1. Form Segment Hypotheses
Big data analysis for the purpose of segmentation is inherently scientific. The first step is to develop hypotheses about your segments. Based on what you know about your segment, you can develop a framework for analysis.
To avoid the risk of confirmation bias, your hypothesis should be based on known variables and goals. It could resemble the following statement:
“Individuals who are seeking a mortgage for a second home are often 30-50 years
old with an income of $100,000 or more per annum.”
A correctly-formed hypothesis serves to narrow your analysis, while still providing room to discover behavioral and motivational insights.
2. Obtain and Combine Data
By participating in BDEX’s Data Exchange Platform, marketers can gain immediate access to billions of data points in real-time. Marketers have the ability to set their own budget, and access insights on web behavior, preferences, and transaction history on consumers that match their existing contacts. Depending on your campaign goals and objectives, you can also opt to obtain contact information for additional prospects that match your goals and objectives. By connecting BDEX’s marketplace with your data management platform (DMP) tool, you can gain immediate access to fresh data insights.
Effective marketing segmentation today has little resemblance to the mass marketing messages of yesterday. By obtaining third-party insights, you can gain a comprehensive understanding of how your contacts behave. This can lead to an understanding that your buyers prefer self-guided product research, are likely to have two children, or other rich factors that reveal segmentation without bias.
By allowing big data to form your segments without bias, you can avoid the risk of inaccurate results. BDEX’s open marketplace forum allows analysis with minimal risk of bias, due to the sheer volume of available insights.
4. Launch Advertising
Once you have developed rich, up-to-date and accurate market segments, you can launch advertising to connect with your audience groups. Instead of relying on months-old segments created by a third-party vendor, your marketing team has the power to continually test, iterate, and improve your audience groups.
For more insights on the power of real-time targeting for marketing initiatives with BDEX, click here!
With the new year comes resolutions, and though vowing to exercise more regularly or cut down on carbs is a worthy personal resolution, it’s important to make professional promises as well. The BDEX teams believes now is the time to take advantage of Big Data.
But it’s not just us. Experts believe 2017 will be a pivotal year for Big Data as well.
“2016 was an exciting year for big data, as finally, Big data is no longer a hype or a buzzword. This means that organisations are actually developing real world solutions and applications with big data analytics that have a big impact on their bottom line,” Mark van Rijmenam of Datafloq tells KDnuggets. As marketers take Big Data more seriously, the doors open for more Big Data projects and Big Data solutions.
The BDEX Data Exchange Platform (DXP) has steadily grown to offer our customers the most comprehensive collection of timely, third-party data on the market. We’re happy to announce that our marketplace is more robust than ever. Look at a few of our updated marketplace statistics below:
Shopping Cart Retargeting, or targeting customers who have shown interest in a product on a retailers’ website, is a common data service. The BDEX Shopping Cart Engine, or C2E service, takes this retargeting to the next level by linking retailers with the email addresses of customers who did not even register or purchase on the website. Retailers can connect with potential customers who have shown an interest in their products, whether or not they wanted to purchase merchandise at that particular time.
Want to learn more about Big Data or BDEX? Visit our website, bdex.com, or email us at firstname.lastname@example.org.
Image Credit: Flickr/KamiPhuc
Marketers may be hesitant to invest in third-party big data insights due to poor reputation. Digiday blasted the products of many big data vendors as “cheap, plentiful, [and] inaccurate, citing cases 30-35% inaccuracy rates discovered through validation testing. However, even the most outspoken critics of third-party data admit that not all vendors are equal, and marketers can drive desired results if they don’t trade “accuracy for scale.”
With the right vendor, third party big data can be a crucial tool for generating lift in marketing results. The proof is in the meteoric growth of programmatic advertising, in which results are largely dependent on data quality and scale. Perhaps more importantly, marketers must remember that third-party data purchased from outside parties isn’t a new concept.
Marketing teams have bought insights for decades as a tool for tailoring print advertising and direct mail campaigns. While the best advertising formats and data scale have changed, the importance of outside perspective hasn’t. Join as we review reasons why validated, high-quality third party data assets are crucial to marketing results.
1. Third-Party Data Can Be First-Party Data
Third-party that generates poor marketing results or contains vast inaccuracies is usually far-removed from it’s source. It was purchased from the organization who originally collected it months prior, scrubbed, categorized, and distributed. However, with BDEX’s data marketplace, your team can purchase data from first-party sources in real-time. Instead of relying on aging insights or questionable segments, you can combine your data with another organization’s first party insights, resulting in far broader contacts and understanding.
2. Third-Party Data Introduces You to New Contacts
While emails, mobile, and programmatic advertising are important tools for customer retention, marketers are in the business of acquiring new customers. The goal of a marketing department is to attract people who resemble your most qualified customers. Third-party data can function much like the contact lists or leads marketers may have purchased in the past. With exclusive partnerships, you can gain access to the email addresses of pre-qualified consumers who are actively looking for your product or services.
3. Your Data isn’t Validated
Third-party data assets from trusted vendors can reveal uncomfortable truths about your organization’s data quality. The most commonly reported data management challenge is resolving quality problems “before they become an issue.” Even if your organization has above-average data management practices, there are likely inaccuracies in your contact profiles. By reconciling your insights in a data management platform against a third-party vendors, you can perform validation and cleansing actions needed to maintain accurate information.
4. Your Touch Points aren’t the Full Picture
Even if your organization engages in extensive first-party data collection practices, you’re probably not getting the full picture. Your insights are limited to what you’re able to collect through Cookies, user-generated web content, and customer touch points. If you’re in the finance industry, you may not know that your customer is expecting a child. If you’re in real estate, you may not know that a client is actively planning for retirement. In order to understand your consumers on an individual level, third-party insights are typically necessary.
Ideally, third-party data has the potential to elevate your team’s insights through validation and the addition of well-rounded insights. Instead of relying exclusively on your own touch points, you can gain insights from other organization’s data collection practices.
BDEX is a first-of-its-kind marketplace, offering marketing teams the ability to connect directly with first-party data vendors in a variety of industries. Buyers gain the ability to access objectively-scored, real-time insights, which can be downloaded directly into your data management platform (DMP) to immediately begin generating marketing lift.