Big Data Trends to Watch in 2019 on bdex.com

Big Data Trends to Watch in 2019

Artificial intelligence and innovations like BDEX Cross-Device Matching will enable marketers to take content personalization and in-store marketing to new levels and open vast stores of unstructured data for mining.

Saying big data means a big business has never been more accurate. Worldwide, revenues for big data and business analytics solutions are projected to hit $166 billion this year and $260 billion by 2022, led by U.S demand.

Today, data signals come from both the physical and digital worlds to bring unprecedented insight into not just which customers are in the sales funnel, but where they are in the funnel. 2019 is shaping up as another big year of growth for BDEX as word spreads of the superiority of our platform and customer service. We expect our approach will continue to win customers and raise standards across the data marketing industry.

In the meantime, here are some other data marketing trends that could gain steam in 2019.

Harvesting voice search

Audio recognition has come a long way since IBM’s Shoebox in 1962. Gartner predicts that voice search technology could boost digital commerce revenue by 30 percent in the next few years. Starbucks has added voice ordering capabilities to its iOS app to the Amazon Alexa platform to help customers place their orders.

Over 66 million Americans are expected to be using audio recognition by 2019 and generating billions, if not trillions of data points as a result. That’s not surprising given that 33 million Amazon Echo, Google Home, and other voice-first devices are expected to be in use by the end of 2018.

Honing location-based marketing

Thanks to geofencing and BDEX Cross-Device Matching, brands can know when a consumer who was shopping for their products online four days ago is in or near a point of sale. That means they can send coupons and other advertising directly to a target customer’s smartphone or other mobile devices to help close the sale or inspire an add-on sale.  BDEX is committed to developing the infrastructure that enables brands to sustain their conversations with consumers throughout their path to purchase, whether that is online, near or in a store. If you missed it, read this recent  BDEX blog post about the vast potential of location-based marketing and why Ralph Lauren, McDonald’s and Walmart are investing in it.

AI enabled in-store marketing

Consumers will begin consenting to have their faces scanned so they can participate in loyalty rewards programs such as coupons, express checkout lines and other levels of service enabled by artificial intelligence, predicts one executive quoted by Forbes.com contributor Gil Press in the Forbes.com article “120 AI Predictions for 2019.” Other predictions in the article include the growing use of AI to mine in-store video for customer insights that could lead to more frequent floor changes and determine what content works best at what point in the sales funnel. Adobe Analytics is among the companies leading the charge when it comes to using AI to sift through trillions of signals to determine what content works best at each stage of the consumer’s path to purchase. Such technology will enable new levels of content personalization in 2019.

Dark data and the rise of CDOs

Advances in applying AI will be critical mining dark data, or the vast stores of unstructured data stored on corporate servers that can’t be utilized for marketing or other purposes until its tagged and organized. Businesses that find ways to economically structure and exploit that data will gain a key competitive advantage, so expect more to name chief digital officers, or CDOs in 2019. Organizations with a CDO could gain an edge over their competition by collecting and monetizing their dark data to a far more effective degree and BDEX stands ready to help them.

BDEX is committed to building the infrastructure marketers need to power human connectivity. Call (917) 410 6616 or email us at info@bdex.com today to learn how Cross-Device Matching and other BDEX solutions can help you put the right messages in front of the right consumers at the right time.

The Value of the BDEX ID Graph on bdex.com

The Value of the BDEX ID Graph

How our ID graph uses deterministic matching to power human connectivity

One of the great ironies of digital marketing in recent years has been that device proliferation has actually made it more difficult to market to people. Cisco recently estimated that on average, there will be 13 networked devices per person in North America by 2021. Most Americans already use cable modems, wireless routers, smartphones, tablets, laptops, and smart TVs at home and millions will add voice assistants and connected appliances in the coming years. And that’s just at home. Many also shop from the office using desktops or from the field using work-issued mobile phones.

If you don’t know how to connect cookies, mobile IDs and other device IDs to a Customer ID, how can you chart your customer’s path to purchase? How do you know whether you are reaching 13 people or just one switching between multiple devices? How do you know whether you are squandering your advertising budget?

Enter identity resolution

The answer is “Identity resolution,” which can enable brands to control who gets what message with much more precision. Consider cable television companies who want to offer discounts to entice new subscribers without alienating existing subscribers. Identity resolution could help them suppress their ads to existing customers.

This is why Forrester Research declared identity resolution the next battleground of corporate marketing in a recent report called “The Strategic Role of Identity Resolution.” It’s also why BDEX has built the most comprehensive, accurate and up-to-date Identity Graph, or ID Graph,  in the industry.

Of course, as MarTech Today explains, not all ID graphs are created equal.

Deterministic matching

At BDEX, we’ve built ours using deterministic matching, which uses authenticated customer information, such as anonymized log-in data, email addresses, and credit card purchases to match and recognize individuals regardless of which device they are using. For example, if someone uses their email to download an app or log into a website using a new iPhone, our ID graph knows to attribute that device to the Customer ID. This allows BDEX to assure customers that our device matching is 100 percent accurate.

By contrast, many ID Graphs use probabilistic matching, which calculates the probability of a user being connected to devices based on IP address, device type, browser type, location, operating system, and other data signals. While it can be used to analyze more data more quickly, probabilistic matching is not perfectly accurate.

The gold standard of identity resolution

Many deem deterministic matching the gold standard of identity resolution and at BDEX we consider ourselves the gold standard of deterministic matching. Our data platform contains more than 800 million mobile-to-email ID connections thanks to more than 70 partnerships with app developers and other primary data sources.

This means you can send us a batch of Customer IDs and we will return a list of matching device IDs within hours. Our subscribing customers can query our ID Graph in real-time to see all the devices attributable to their target customers in milliseconds. They can match a single ID or all their IDs in a single query and pay only for the matching IDs returned.

BDEX manages more than 800 million mobile IDs, 1 trillion real-time data sets and 1.3 billion email hashes. That makes us the most comprehensive Identity Graph in the United States and explains why some of the biggest brands in marketing come to us for identity resolution.

Anyone can sell you data, but only BDEX can provide the identity resolution needed to power human connectivity and get the most out of your marketing dollar.

To learn more about how BDEX can help you with Cross-Device Matching email us at infor@bdex.com or just fill out our online contact form.

The Elements of Effective Targeted Marketing, Part 1 on bigdataexchange.com

The Elements of Effective Targeted Marketing, Part 1

Identifying your ideal customer

The first, essential element of any targeted marketing strategy is identifying the ideal customer for your product or service. Actually, this is crucial for anyone who wants to build a successful business.

And it applies no matter what you’re selling; whether it’s a car, a washing machine, diapers, or legal services. Any successful strategy relies on having a basic understanding of the specific target market.

How to identify your target audience

1. Compile the demographics and habits of your ideal customer

Start to identify your target audience by thinking about the characteristics and behaviors that make a person your ideal customer.

These demographic and psychographic factors include:

  • Age
  • Gender
  • Cultural heritage
  • Geography
  • Occupation
  • Marital status
  • Income
  • Lifestyle
  • Type of residence
  • Education level
  • Interests
  • Common problems

To summarize the findings, think in terms of one to a few people who represent your customer base, and then build an ideal customer avatar for each one.

For example, a 35-year-old married woman with two children and a full-time job. You must also try to detail what kind of residence she lives in and where its located, as well as her interests and common problems, such as being too busy to … [insert pain point]. The more specific you can get, the better.

These avatars will be influenced by …

2. Studying your existing customers and accessing third-party research

If you have an established business, you’ll want to study your existing customers. Who is buying or ordering your product? Is it single men, married women, Millennials, Baby Boomers, outdoor enthusiasts?

Look at which of your products have the best sales record and think about why they do better than others, and with whom. Understanding the buying habits of your customers helps you determine the best way to reach them and with what message. There are of course differences between the demographics and psychographics of someone looking to buy a minivan versus a BMW, for example.

In addition to your own, highly-valuable experience with current customers, there are third-party research services that can add layers of contextual demographic and psychographic information tailored to your industry, products or services, and geographic area.

3. Conduct a competitive analysis

You should also do a competitive analysis by looking at similar businesses in your area (or your industry). For example, a dealership that sells Hondas would research what competing dealerships are doing, in terms of pricing and deals, as well as other marketing specifics. Who are your competitors targeting in their marketing? What kind of marketing vehicles are they using?

You’ve defined your ideal customer and the media and products/services they use. What’s next?

Studying what you believe to be your ideal customer won’t tell you the full story. If you own a car dealership, simply advertising to everyone who falls under the basic profile of a car buyer won’t be very effective.

That’s still a pretty wide group. Not everyone in that demographic is actually looking to buy a car right now, and you’ll end up wasting vast resources marketing to people who aren’t even thinking about a purchase.

As we discuss in the next installment of this series, the basic profile of an ideal customer interface with both predictive analytics and the latest actionable, real-time data that pinpoint individuals who are actually ready to buy.

Click here to read part two.

BDEX features the first-ever Data Exchange Platform (DXP). The BDEX DXP and DAAS platforms enable companies to acquire impartial, quality-scored, third-party data reaching the right people at the right time like never before. We offer cross-device matching, auto dealership services, DAAS, real-time targeting, and custom segment building that is ideal for any industry, including auto dealers, retailers, brands, agencies, out-of-home, and franchises. Contact us today to get your customized marketing data.

What Does a Big Data-Driven Customer Experience Look Like?

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.

Image Credit

Are You Using the Most Advanced Data to Target Consumers?

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

When Real-Time Data is Actual Real-Time Data

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).

Mobile Data

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.

Cross-Device Matching

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.

Moving Beyond Interest and Intent

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 info@bdex.com.

Image via Flickr/Jean-Pierre Bovin