The importance of data to a business’s success isn’t a recent discovery. For decades, the fate of American television shows rested solely in the hands of The Nielsen Company, which still monitors citizens’ viewing habits via customer surveys and meter readings today. However, thanks to an incredible influx of information from a variety of sources, including cell phones, computers, and even sensor-equipped trains, brands have more access to analytics than ever before. Harvard Professor Gary King even referred to this stream of statistics as a “big data revolution” (Harvard Magazine). While the amount of information is impressive, King doesn’t believe the quantity is the “revolutionary” part.
“The big data revolution is that now we can do something with the data.”
But for many companies, knowing how to properly use acquired information is a major problem. When brands consider the following factors of big data, they are better equipped to reach consumers:
Timeliness of the Data
“In the rush to avoid being left behind, I also see that many companies risk becoming data rich but insight poor, says data expert and author Bernard Marr (Forbes). “They accumulate vast stores of data they have no idea what to do with, and no hope of learning anything useful from.”
One major issue with businesses storing data but not taking action is that the information goes bad quickly. Companies will keep the information hoping it will be of some use though it’s “no longer relevant, inaccurate or outdated,” says Marr. In other words, “time is of the essence.” BDEX is different from other data providers in that brands can access real-time analytics the moment consumers browse and shop online. By knowing what consumers want at a given time, businesses are better able to meet consumers’ needs.
Source of the Data
There is a common misconception that first-party data is superior to third-party data. While first-party data is owned by the company that obtained it, the data does not change as it’s transferred from party to party. That’s why data expert Kevin Tan believes companies should focus “on the quality and transparency of the data, not the party label.”
“Advertisers that choose to work with high-quality data providers can obtain third-party data that is timely and clear. Used together with first-party data, top quality third-party data enables brands to build a fuller picture of target audiences,” says Tan. (Exchange Wire)
In order to determine the quality of the information they receive, brands should also know where their data providers get their statistics. Some sources, like the US Census Bureau, may contain a broad range of data, while others, like market research surveys, may provide more specific information. By making use of data from a variety of sources, brands have the ability to assess their target audience and create better marketing campaigns.
Accuracy of the Data
You may be wondering, “How do I know what data is usable?” After all, the sheer number of data resources suggests that some of the data will either 1) not pertain to every business or 2) be incorrect. And while it does not serve your business to cater to every online consumer, know that the specificity of the information big data, especially third-party data, can provide is unparalleled. Information is collected by a variety of tools ranging from desktop cookies and e-tags to smart phone IDs.
“All this allows firms to glean what sites users have visited, what they have shopped for, what postcode they live in and so on. From this the firms can infer other personal details, such as their income, the size of their home and whether it is rented or owned.” (The Economist)
While the amount of data can be overwhelming, utilizing big data will not only help you reach your consumers but anticipate what they want next.
BDEX is the first ever Data Exchange Platform (DXP) offering real-time data in a marketplace environment. All seller and consumer information is impartially scored to ensure that data is and high-quality and accurate. To learn more about BDEX’s unique services, or to become a BDEX buyer or seller, click here.
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.
Your customers expect you to understand their needs. 80% of modern consumers expect personalized experiences from their favorite brands. Despite increased budget for big data marketing initiatives, 43% of marketers feel they’re getting almost “no benefit” from their existing data assets. These two statistics illustrate a clear disconnect between what customers want, and what marketing teams are able to deliver.
The savviest marketing teams aren’t just deriving value from their internal, or first party, data assets, they’re obtaining high-quality, real-time insights from 3rd-party data vendors to develop a 360-degree view of their customers. In order to capture and retain today’s complex digital consumers, a big data-driven customer strategy is a must.
What Does a Big Data-Driven Marketing Strategy Entail?
Every time your customers swipe on a mobile device screen or post a status update to social media, they leave a trail of data on their preferences and behaviors. Each of these interactions offers the potential for your brand to gain insight into how to create personalized experiences for your customers.
By synthesizing first and third-party data insights in a data management platform (DMP), you can create a holistic view of your customer base. This allows you to understand patterns and stories that extend beyond your own touch points, and discover truths about how your customers interact with the world around them, by using these stories to create segments and understand your customers on an individual level. In this blog, we’ll discuss several of the best practices best-of-class organizations adopt when developing a marketing strategy that’s driven by big data insight.
1. Expand Your Data Collection
Transform your strategy from first-party data analysis to a program that’s focused on true cross-channel synthesis. By combining the broadest array of data sources possible, you can improve your strategic analysis and customer understanding.
2. Score Your Segments
By creating narrow segments of your existing customers, you can focus on your best clients. These are the individuals with the highest customer lifetime value (LTV), and who may be most likely to promote your brand on social media channels and other online forums. The creation of buyer persona profiles has traditionally been executed through qualitative research methods, such as focus groups. By allowing data to tell your story, you can eliminate organizational biases about what your best customers look like.
3. Focus on Customer Experience
When you have identified your best customers, it is critical to discover ways you can improve your client experience. You can discover insights on how your customers interact with brands through the inclusion of 3rd-party data. Are they mobile shoppers, or heavily-engaged app users? Tailor your engagement strategy to your client’s existing behavior patterns.
4. Get Personal
The best marketers know that big data has the potential to move your strategy from segments to true personalization. Use your big data insights to discover behavioral triggers, and tailor personalized marketing efforts to meet your client’s needs for relevant email marketing and programmatic advertising.
5. Measure and Optimize
With your programmatic advertising and email marketing metrics, your brand has the potential to move towards continual improvement cycling in your marketing program. Never stop collecting data, analyzing, and improving your efforts to deliver a best-of-class customer experience.
Are you ready to make the shift towards customer-focused, Real Time big data-driven marketing? Contact BDEX today for more information on high-quality, real-time big data assets from trusted 3rd-party sources.
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!
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