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.

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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

Desperate for the Right Insights: How Data Exchange Can Solve Your Procurement Issues

Big data procurement is a pain point for analytical marketers. Chief Marketer reports that “getting a 360-degree view of the customer” is a primary struggle for today’s marketing leadership. While it’s clear that integrating a wide array of data insights is the right solution, many marketers are simply unable to obtain the right big data assets via traditional procurement methods, such as data management platforms (DMPs), internal assets or leading third-party vendors.

 

The most sophisticated marketers understand there’s more to customers insights than “RFM – recency, frequency and monetary value.” To effectively maximize conversion potential, subject matter expert Karl Wirth recommends including insights on relationships, persona and intent. You must understand how your prospects are researching across platforms, individual motivational factors and pain points, and the context that surrounds each of these qualifiers. It’s abundantly clear that big data means big opportunities for marketers, but only if they’re able to procure sufficiently recent and comprehensive insights.

 

What Comprehensive Big Data Procurement Looks Like

While analytics experts have multiple ways of categorizing the types of data that provide marketers with comprehensive understanding of their target customers, marketer Jim Robert’s definitions are among the most intuitive:

  1. Identity
    A consumer’s identity includes basic demographic characteristics, such as age, gender, and race. It also includes geographic details on the area of residence, and insights such as employment, job title, and income.
  2. Quantitative
    Quantitative data is most likely to be first-party insights stored within an organization’s DMP based on their interactions with a customer, but can also be sourced via data exchange with third-party vendors. This includes data on transaction history and communications with the brand. It will also include online activities across desktop and mobile devices, including historical engagement with branded content or company’s sales teams.
  3. Descriptive
    Descriptive data offers a more comprehensive view of an individual’s life than pure identity data. It can include parenthood status, including the number of children and whether an individual owns pets. It can detail whether someone owns or rents their home, their education level, and work history.
  4. Qualitative
    Many marketers are familiar with the concept of “attitudinal data,” but qualitative insights actually encompass much more. A consumer’s opinions, brand preferences, and motivations may be included among these insights. Qualitative profiling can also lead to an understanding of brand preferences, consumer pain points, and individual priorities.

 

While you can gain a basic understanding of customers by procuring just identity and quantitative insights, it won’t be a truly comprehensive understanding of how your customers operate. You won’t understand why they make the decisions they do, or how they’re most likely to research based on education level.

 

Each additional type of data insight can change a consumer’s goodness-of-fit with a marketer’s target market. While consumer identity factors may dictate that they can afford to purchase a product, descriptive and qualitative factors may affect their priorities or reveal that budgets are most likely directed elsewhere.

 

DXP: Simple Procurement of Comprehensive Insights

For marketers struggling to build comprehensive profiles and filter targeted advertising opportunities towards the most qualified customers, the Data Exchange Platform can represent the solution. Instead of relying on limited or aging insights in a DMP environment, marketers can procure big data via a wide range of third-party resources all in one place via the DXP. No other platform can give marketers the breadth of data availability like the DXP due to it’s inherent access to so many data providers at once and it’s ability to merge data points from multiple sources across a single data taxonomy. This facilitates the first steps towards a true, 360-degree understanding of who brands are trying to connect with.

 

It goes without saying that better understanding leads to better conversions and sales. By ensuring their messaging lands in front of genuinely qualified prospects exactly when they’re motivated to buy and actively searching, conversion rates can finally exceed organizational targets. Instead of struggling to drive sales with data that reveals only part of the picture, marketers are given the opportunity to finally achieve the understanding they need.

 

For more insights on customer understanding through big data analytics, we recommend our blog: Re-Imagining the Consumer Needs Through Data.

 

image credit: nec corp via flickr/cc

 

 

Is Your Big Data Dated? The Importance of Truly Real-Time Email Marketing

For contemporary email marketers, big data management is a critical tool for segmenting email lists and delivering relevant content offers. However, a recent survey of 1,300 email professionals indicated a serious ineffectiveness in how marketers apply big data assets to decision-making. VentureBeat’s analyst Jon Cifuentes described the issue as an “education problem,” citing issues with both major vendors and the data management skills of email marketers.

According to the subject matter experts at TowerData, the most commonly-reported data management issues among email marketers include:

  • Centralizing multiple sources of big data
  • Managing storage, application, and access processes
  • Applying real-time data for best results

 

For organizations who already have storage, application, and access managed via a data management platform (DMP), the cause of poor email marketing metrics is most often connected to data quality. Tower’s research indicates that brands too often rely exclusively on first-party insights, or outsource their data assets entirely to a third-party vendor. While the addition of the vendor’s third-party data can enhance understanding of contacts, these organizations are often sacrificing data recency for the sake of perceived simplicity.

 

Email isn’t Getting Simpler

 

Marketing experts have acknowledged that yielding positive returns on email marketing campaigns is growing more difficult, and the average open rate is just 16.5% across industries. Data is a “common denominator” for email marketers, but the companies who see positive returns are those who are bold enough to look beyond first-party insights and seek out solutions beyond the dated offerings of many major vendors.

 

Delivering email marketing messages that earn opens, click-throughs and sales requires an up-to-date understanding of prospective buyer’s needs that is typically only possible through a real-time Data Exchange Platform (DXP).

 

How Real-Time Big Data Impacts Email Marketing Metrics

 

For modern marketers, applying real-time data to email marketing efforts is among the top five ROI-driven priorities discovered in The Relevancy Group’s research. Additional studies indicates that the majority of marketers believe real-time data will have a bigger impact on email metrics than any other channel. By participating in a real-time Data Exchange Platform such as BDEX with a variety of vendors in an open marketplace agreement, brands can significantly improve their segmentation and targeting efforts without needlessly complex data management processes.

 

According to Adobe’s Mickael Bentz, real-time data is just as critical as technology when it comes to effective email marketing. For execution of high-return email marketing, you must look beyond internal understanding of customers to create “context-aware” communications. Important sources of real-time data, in addition to your own CRM insights, should include:

  • Surrounding context insights, such as weather or stock status
    User web analytics from desktop and mobile devices
  • Behavioral and event-triggered data, including career searches, loan applications, and transactional insights.

 

For organizations who utilize a marketplace such as BDEX to purchase insights directly from vendors, improving your email marketing campaigns requires a simple, two-part process:

 

  • Obtain: By integrating BDEX’s marketplace directly with your database of emails, you can select from a variety of real-time data insights driven by your contact’s web behavior, transactions, behavioral-triggers, and other factors. You’re able to purchase as much — or as little — as you wish, ultimately depending on your budget for the email campaign.

 

  • Match: Matching data insights with your contacts can be managed within your data management platform, allowing you to refine your segments and develop targeted offers in real-time.

 

Instead of relying on a third-party vendor to develop segments based on months-old search habits or other factors, marketers gain the ability to create real-time segments for truly targeted offers.

 

If your data insights are limited or aging, there’s a good chance that typical data management technologies aren’t enough to yield best-of-class email marketing practices. By shifting towards a real-time segmentation and offer delivery model, you can ensure you’re sending the right messaging to the right contacts, at precisely the right time.

 

For more information on how BDEX can integrate directly with your existing DMP or DSP technology, click here!

 

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When Your Audience Doesn’t Reflect Reality: Big Data Audience Building

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.

3. Analyze
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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5 Incredibly Costly Big Data Marketing Mistakes

Low-quality big data assets can lead to incredibly costly marketing mistakes. Research by Experian indicates that low data quality has a direct impact on revenue for 88% of modern organizations. Average losses are approximately 12% of revenue. For organizations who are shifting towards data-driven marketing and customer experiences, low-quality data can lead to costly mistakes.

How Bad is the Average Marketing Big Data?
Per eConsultancy, 22% of information on contacts, leads, and customers contains inaccuracies. Perhaps most concerning, the average organization’s quality index is headed in the wrong direction. Twelve months ago, the average inaccuracy rate was just 17%. Incorrect data can have a real impact on your team’s ability to build segments, understand behavioral triggers and preferences.

In contrast, organizations with a high degree of data accuracy are more likely to appreciate:
● Efficiency
● Cost-Savings
● Customer Satisfaction
● Informed Decision-Making
● Protection of Brand Reputation

Poor-quality or old customer data can lead to a series of costly marketing mistakes. Join us as we review some devastating errors that can be directly attributed to inaccurate customer data.

1. Low Advertising Conversions
Low conversion rates on programmatic advertising is a symptom, not an issue. Poor click-throughs and conversions can be attributed to a lack of mobile advertising, poor segmentation, irrelevant data, or other factors. However, far too many marketing teams fail to take appropriate action in response to low advertising conversions. Instead of working to improve the breadth or quality of data, they continue generating ads. Before running more ad campaigns, marketing teams should take appropriate action to ensure they can achieve better returns.

2. Inconsistent Brand Experiences
Without accurate or up-to-date data, your brand communications could send the message that you don’t know your customers. You may generate programmatic advertising for products your customers already own. You could send an email blast for baby products as their children are approaching preschool age.  Marketers need to actively combat a brand experience that’s inconsistent with a customer’s needs and activities. If you miss the mark repeatedly, you’ll struggle to build customer loyalty and sales.

3. Poor Email Deliverability
The average return on investment (ROI) for email marketing at mid-sized organizations is 246%. However, organizations have the potential to significantly exceed these benchmarks with appropriate timing, segmentation, and other big data-driven activities.  Email communications to outdated contact lists have the potential for a high bounce rate, or percentage of emails that are undeliverable. Email segmentations that are vastly inaccurate could also increase your risk of being pinged as spam. In the mind of a consumer, spam is simply “unsolicited bulk email.” If your messaging is irrelevant or feels too much like a mass communication, it’s likely unwelcome.

4. Mobile Neglect
Far too many big data marketing strategies are focused on desktop advertising, email receipt, and experiences. In reality, consumer behavior demands mobile marketing. As of 2015, adults now spend more time engaged with mobile devices than desktops, laptops, and other connected devices combined.  There’s a good chance that, at least 50% of the time, your desktop-optimized advertising is consumed on mobile devices. This can lead to poor user experience (UX) and returns on investment.

5. Poor Verification Methodologies
All too often, major brands go viral for all the wrong reasons. Poor data verification can lead to mistakes that are embarrassing, insulting, or even hurtful to their loyal customers. OfficeMax sent coupons addressed to “Mike Seay, daughter killed in car crash.” The addendum to the customer’s name was unfortunately true. The company ultimately issued a public apology to the customer.   Manual data verification processes are rarely effective in the big data age. Fortunately, using a data management platform (DMP) or another tool to perform quality checking against 3rd party data can eliminate much of the risk of similar mistakes.

If your organization’s data quality is average or below average, you’re at risk for many of these expensive marketing mistakes. By taking the appropriate internal steps to improve your quality standards, you can improve the ROI and impact of your marketing efforts.

BDEX offers high-quality, real-time big data assets from trusted 3rd party vendors to safeguard against low-return marketing investments. By downloading the right data resources directly into your DMP, you can improve the accuracy of your customer records, gain deeper insight into your buyers, and build better segments.For more information on becoming a BDEX buyer or seller, click here.

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