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.
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
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.
Big Data’s incredible economic and social influences are evidenced in the variety of industries it’s revolutionizing. For example, healthcare providers can better “predict epidemics, cure disease, improve quality of life and avoid preventable deaths” (Forbes). Brands can better serve their existing customers while attracting new ones, and retailers can predict what trends will resonate with their shoppers.
However, those new to the data monetization side of the Big Data industry may feel a little overwhelmed since there are thousands of companies ready and willing to utilize their data. Before you take the plunge and decide where and how you should sell your data, consider these important data factors: location, price, and privacy.
Where You Sell Your Data Matters
You’re probably wondering, “Where do I sell my data?” After all, the “personal data economy is fairly new.” While you can sell data to a variety of websites, the process can be time-consuming, as tech blogger Chris Hoffman points out. And if you’re selling a limited amount of information, weighing the amount of time spent selling versus the value of the actual data is important.
But as the data monetization industry grows, more and more options become available. Data marketplaces, or online stores where people can buy and/or sell data, are alternatives to the traditional DMP. Data marketplaces allow a wider range of businesses to take advantage of data monetization. Some marketplaces, like BDEX’s, don’t even require revenue sharing.
The Price Must Be Right
Determining the value of your data is perhaps the most difficult part of monetizing data. If you set the price too high, buyers will choose other providers, but if the price is too low, your chances of creating a decent margin are squashed. In a marketplace environment, data sellers can determine the price of their data based on that of the competition. BDEX even shows their data sellers the optimal price point of their data so they raise or decrease the price when necessary.
Customer Privacy is Essential
Sharing data should be a mutually beneficial experience for all involved, including the consumers. To ensure that your consumers’ information is protected, you should encrypt the data or hire a third party to do it for you. You should also be sure that the website or marketplace that buys your data is doing their part to protect the data as well. Data sellers who take advantage of the BDEX marketplace can rest assured that their customers’ information is anonymized and protected.
BDEX is changing data monetization. Sellers can enable activation and monitor their data, while buyers can access tremendous scale and even integrate the BDEX DXP into their own DSP. When they utilize BDEX’s data monetization services, data sellers have complete control of what data they sell and its individual price point. For more information, email us at firstname.lastname@example.org.
Image Credit: Flickr/http://401kcalculator.org
Many data platforms claim they can provide their customers with real-time insights, but their definition of “real-time” is often debatable. True, real-time data is not only obtained in real time but offers brands, retailers, and agencies up-to-the-second information on their customers’ behavior. After all, if you acquire information about an online shopper one minute but the information is 30 days old, the data’s value is greatly diminished. But if that same online shopper searches for sandals on one website one minute, and the marketer learns that information a minute later, the data is priceless. “Organizations can reap a lot of benefits by accessing real-time analytics purely because of their close relevance to market realities” (Techopedia).
Real-time data can be learned a variety of ways, perhaps most obviously, through mobile IDs. Every Apple device has a UDID, or Unique Device Identifier. “Originally, the UDID was intended as a sort of serial number for Apple devices. But, as the industry began to explode, app developers turned to the UDID to help track and target mobile users.” Apple later denied app developers access to users’ UDIDs and created a data set called IDFA, or Identifier for Advertisers. Unlike the UDID, the IDFA is not easily linked to devices or users. In fact, users can even opt of advertising tracking altogether if they wish.
Despite mobile advertising regulations, mobile ID tracking provides valuable data for marketers, especially when tracking real-time behavior. With over 100 million mobile device IDs tied to AAIDs and IDFAs, the BDEX DXP has some of the most comprehensive and diverse mobile data on the market.
“Ninety percent of today’s consumers bounce back and forth between devices when making purchases. When you consider that 65% of the revenue generated online comes from purchases that are made across multiple channels, you have little choice but to target users with ads regardless of the device they’re using to access these channels” (Shopify). To target the same consumers across multiple channels, however, marketers must link those consumer’s various IDs. Not surprisingly, connecting the ID “dots” is easier said than done.
There are over 80 million email-to-mobile ID and email-to-cookie ID matches available in the BDEX marketplace. Thanks to a plethora of data provided by more than 75 sources and custom BDEX identifier tags, marketers can link their consumers’ information across multiple sites and platforms and use that data to advertise via mobile, email, display, or any other channel.
While interest and intent data is certainly valuable, when you add a real-time element to the equation, the information learned is not only a predictor of what a consumer may buy but an indicator of what he/she will buy. With millions of new data points received daily across thousands of categories, the BDEX Data Exchange Platform offers the most comprehensive and time-relevant data on the market. For more information about our platform, visit our website. Want to get in touch? Email email@example.com.
Image via Flickr/Jean-Pierre Bovin
Data quality is among the most common pain points associated with marketing initiatives. For teams engaged in email marketing, programmatic marketing, or other big data-driven projects, quality issues can significantly reduce results. If your organization’s efforts to produce targeted, real-time messaging are generating poor lift, it could be important to look towards your third-party data vendor as a potential source of the problem.
In best case scenarios, third-party data can allow marketing teams to develop 360-degree understanding of their target customers. However, directing dollars towards the wrong third-party vendor can actually damage efforts to programmatically generate advertising messages. If your vendor’s insights are out-of-date, generated through poor data logic or clustering technique or inaccurate, your results could be worse than if you were solely reliant on first-party insights in your data management platform (DMP). In this blog, you’ll learn the differences between data types, and how the wrong vendor can lead your team astray.
Understanding the Classes of Big Data
While sources and volume can vary significantly, there are a few terms commonly used to describe the origin of data that may be applied to a big data-driven marketing campaign. Understanding the following classifications can allow marketers to understand sources of risk in their marketing campaigns, and make the right choices about data acquisition at a large scale.
1st Party Data: These insights are generated by your company’s web, mobile, and transactional records. Typically, these insights are the most accurate, and are housed in a data management platform (DMP), which is typically integrated with a CRM.
3rd Party Data: These insights are obtained through an external data provider. The data is generally anonymized, and may be matched with your contacts in a data management platform. Vendor sources can vary significantly, but purchasing from a large-scale vendor can result in insights that are out-of-date and suffer from quality issues.
2nd-Party Data: These insights are among the most rare. 2nd-party data could originate from long-term data sharing agreements between organizations to continually combine and match profiles.
For many big data campaigns, the single biggest source of risk is 3rd-party data. When completing audience profiles with old or inaccurate insights, your audience profiles could be significantly diluted. Sources of risk in 3rd-party data quality can originate from the following factors:
1. Sourcing Methods
Third-party data vendors often have “mountains of information” available, according to Dunn & Bradstreet (D&B). However, their sourcing methods can be a bit of a mystery, even to some external representatives of the organization.
In one case study, a 3rd-party data vendors classification of “new parents” proved 10-20% inaccurate, per D&B, because it was based on individuals who’d recently purchased a certain magazine subscription. In other cases, vendor’s sourcing is based solely on online browsing cookies.
Regardless, your marketing results could be questionable if you’re not able to quickly establish each of the following with a prospective data vendor:
● Where does the data come from?
● Does the data represent online and offline behaviors?
● Do you rely on multiple data points to build audience groups?
2. Quality Assurance Methods
Quality assurance represents a major source of effort for data science teams. While purchasing third-party insights that are cleansed can provide convenience for marketing teams, your vendor’s quality standards need to be impeccable to yield gains.
Understanding your vendor’s approach to data verification, elimination of old data assets, and comparison is crucial. The best indication of data quality is results. Proof of recent conversions is the most objective way to measure third-party data assets.
3. Refreshing Methods
Generally, most data vendors “refresh” their data assets on a periodic basis, by pulling new insights into their data management platform. For vendors that source from a variety of sources, these “refreshes” may occur very occasionally, such as every several months.
In a world where consumers have access to immediate purchases via mobile devices, recent data is crucial. Insights that accurately reflected your audience’s behavior three months ago are not accurate today. Unless your vendor’s data is updated in real-time, it’s out of data.
BDEX: A New Approach to Real-Time Data Exchange
BDEX offers a first-of-it’s kind marketplace for real-time big data exchange. Instead of having to rely on third-party vendors to aggregate data from a variety of sources, brands are able to purchase insights directly from the source as they are generated. With objective, third-party scoring of conversions, prospective customers can gain peace of mind that the data is sufficiently high-quality to generate lift.
For more information on purchasing data via BDEX, click here.