Machine Learn, Not Machine Burn

Our marketing machines are far from sentient, but they still let us reach our customers in far better ways.

You’re probably feeling stuck behind the curve if your team has yet to adopt AI-supported solutions. There can be a ton of risk involved, but there doesn’t have to be. It’s time to find a way to infuse and elevate your marketing with AI. Making the right choices in a hype curve is critical to ensure you’re not wasting dollars.

It all comes down to picking practical, purposeful applications to test.

No matter where you’re at in your marketing maturity, it’s never too late to take the leap. Defining tangible, addressable challenges for your marketing machines to solve is the foundation on which your AI-driven solutions will thrive.

See Frank Monteforte, Zeta Global’s VP of Product Marketing, highlight how you can optimize the use of AI in your marketing strategy by learning how to pick practical, purposeful applications to pilot on your marketing machine.


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Signal Data, Powered By AI: Marketing’s Future State Requirements For Maximum ROI

Signal Data, Powered by AI: Marketing’s Future State Requirements for Maximum ROI

Today’s marketers continue absorbing organizational responsibility and the technologies that come with that. The struggles are real, but marketers must find a way to work smarter to achieve core competencies to drive acquisition, optimize experiences and boost growth.

Successful marketers are integrating artificial intelligence into their strategies so that they can work smarter and do more with less. Along with newfound efficiencies, harnessing the power of AI and signal data can exponentially increase your ability to deliver on customer expectations, wants and needs.

Our Zeta Webinar featuring Cynthia Janelli and James Beauchamp will help you better understand how to:
  1. Make sense of the data to create meaning on context to the complete customer
  2. Connect the right tech ecosystem to engage consumers as unique individuals
  3. Improve the customer experience by proactively personalizing engagements with more contextual data
  4. Make media more efficient by leveraging first-party data toolsets in more agile formats

And feel free to take a look at their slides as well!

Please fill out the form below to view the webinar:

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Are Personalization and Individualization Causing Intimidation Within your Marketing Organization? It All Starts and Ends with DATA!

Are Personalization & Individualization Causing Intimidation Within your Marketing Organization?

It All Starts and Ends with Data

By: Michael Lewis, Group VP, Retail, Zeta Global

Just back from eTail West, I can’t help but wonder if we, as technology solution providers, are pushing the right message to marketers in 2019. Marketing today is all about personalization and individualization, right? My immediate answer is: absolutely! But, after speaking with retailers from eTail in February and NRF in January, I have to change my answer and say, “No, it’s all about DATA.”

What are retailers most struggling with when it comes to reaching that level of personalization they want to achieve with consumers? Data. Data. Data – all day long, it’s data. So, while we can talk about personalization until we lose our voices (which is actually what happened to me), if the data isn’t available, the personalization will never happen.

Why is data such a struggle for retailers? There isn’t just one simple answer to that question. We know the struggles in our everyday practice with brands.  Customer demographic data may be in one database, while point-of-sale data may be in another – no centralization.  Or, you may understand the criticality of the data, but it may take you a weeks-long project request protocol to get it from IT – no accessibility.  Or, perhaps the data is all in one place, and you have access to it, but you can’t engage with it – no activation capability.  Or finally, the data you have doesn’t tell you enough to personalize effectively. When I sat down with Forrester’s Brendan Witcher at NRF he had this to say about some of these issues’ retailers are facing. And, the situation wasn’t any different at eTail.


Roughly 50% of our retail audience do go beyond using “first name” strategies to deliver personalized experiences on their websites and/or email communications


At a private luncheon we hosted at eTail we surveyed our retail audience members about their current and future plans to implement more personalization into their marketing programs. We were happy to learn that roughly 50% of them do go beyond using “first name” strategies to deliver personalized experiences on their websites and/or email communications.  This was consistent with what we heard in our report with The Relevancy Group earlier this year. But we were also disappointed that the other 50% can’t reach that level of sophistication – often due to data struggles we highlighted above.

Are you one of those marketers struggling with personalization? Perhaps It’s because you’re not getting your data right, or, getting the right data. The critical first step is to know what data you have and, more importantly, profoundly understanding what you currently know about your customers.

The critical first step is to know what data you have and, more importantly, profoundly understanding what you currently know about your customers


Before launching a personalization strategy, make yourself the following checklist, because without “yes’” to these, you can’t go far:
  1. Do I know where all my data is?
  2. Is my data organized in a clear, consolidated view? Do I have everything in one place?
  3. Do I understand my customers well enough to identify who is valuable to me and who is worth cutting loose?
  4. Do I know which data points can lead to memorable experiences for our customers and market-moving results for us?
  5. Can I activate the data in a personalized way in my marketing tech stack?

If you can answer “yes” all those questions, it’s time to focus on personalization and individualization. And, if you are just starting there, don’t fret. You’re with about 50% of all brands in the U.S.  Here are my suggestions:
  1. Don’t try to be “hyperdynamic” on the first day.
  2. Know your customers as you have them, not as you perceive them to be.
  3. Test what data points are helping you identify the most valuable customers you have.
  4. Test what data points – combined with appropriate content – drive results.
  5. Consider looking outside for a partner who can help you “mirror” those valuable customers so that you can identify and win those consumers over to your brand.


Consider looking outside for a partner who can help you “mirror” those valuable customers so that you can identify and win those consumers over to your brand


Don’t let personalization and individualization leave you feeling intimidated. Review your data assets and strategy before you embark on a personalization journey. If you do it right the first time, you will undoubtedly succeed and turn your highly-valued customer data into individual connections who identify with your brand and want to purchase your products and services.

Consider looking outside for a partner who can help you “mirror” those valuable customers so that you can identify and win those consumers over to your brand.

Michael Lewis, Group Vice President, Client Services, at Zeta Global, leverages his expertise in retail and marketing to transform our clients’ customer relationships — helping them identify the right data to move from a “reactive” model to a highly personal and individual strategy that anticipates and predicts their next need with great accuracy. 
retail digital marketing

What’s Hot in 2019 Retail Marketing?

Learn why data should be at the core of your marketing strategy. National Retail Federation Expert and Forrester Vice President and Principal Analyst, Brendan Witcher, Breaks it Down for Marketers.

By: Michael Lewis, Group Vice President, CRM U.S. at Zeta

I had the pleasure of hearing all about the latest retail digital marketing trends from one of the industry’s top analysts, Brendan Witcher, of Forrester Research. Brendan and I sat down at this year’s National Retail Federation event to discuss what’s in and what’s out for retail marketing in 2019.

I asked Brendan about everything from the hottest trends he saw on the show floor to where he sees the industry headed in terms of personalization, artificial intelligence, data strategies, and customer experiences. Here’s some of what he had to say, beginning with his take on AI and what marketers should be thinking about for their AI strategies:

ML: Artificial Intelligence (AI) doesn’t seem to be going away anytime soon. What is the receptivity/investment/expectations for it with retail?

BW: AI was hot and buzzy with retailers a few years ago, and they are still interested, but they are starting to question when they buy AI what they are really saying. The better questions to ask are: What do I want when I apply this to in my business? How do I find incremental gains through AI? Where will it provide me with a benefit… Operationally? Understanding the customer? Efficiency in customer engagement or efficiency for my marketing campaigns?

We can’t scale anymore to keep up with the speed of customer. AI helps get us there. How do we use it in ways to help organizations stay in lock step with the customer?  Retailers should be looking for partners who provide AI solutions that build a better business or understanding of the customer.

Think about the outcome…think about how you will use it…what can you not do today? Look for a business challenge, and you will probably find an AI solution that will help. Most people don’t understand AI and the value it can bring to so many areas in the organization.


Watch our video clips below to hear more on the other topics we discussed at the event:
  • The customer journey management topic was introduced about 3-4 years ago, but are any marketers/brands getting to the individual level of that journey for each customer?

  • Are retailers mastering personalization in a space where merchandising priorities come into play?

  • Are there any new data sources or tactics being used in acquisition?

  • I’ve heard some panelists at NRF say they need to append more data to get closer to their customers, to personalize experiences for customers and that they need to make their media spend more efficient. That’s good news for those, like Zeta, who have been saying to analyze the data you have so that you can get to know your customers now that the stacks have been built. What are you seeing/hearing in this area?

How to Activate High-Value Customers Leveraging Natural Language Processing and Machine Learning

By: Winnie Shen | Director of Data Operations, Zeta Global

Moving Beyond First-Party Data

Every marketer understands the value of first-party data. It’s a given that we all understand how important our data is that we house in our own databases. The challenge comes when we need to grow beyond our existing data, enrich those audiences and expand sales. That means gaining a truly 360-degree view of our customers. Many marketers today operate between a “probabilistic” and “deterministic” landscape, lacking a complete view of who their customers actually are. Our goal at Zeta is to utilize your existing customer data while leveraging our deterministic behavioral signals to identify and activate high value customers and reactivate dormant users, creating new growth opportunities for our clients.

How to Activate High-Value Customers Leveraging Natural Language Processing and Machine Learning

Natural language processing (NLP) is the key to helping us understand the content consumers are engaging with. When we leverage it properly with artificial intelligence technology to look at behavioral signals across the open Web, we can identify clusters of individuals, most relevant to our client brands. Here’s an example of how we’ve done just that for one of our apparel clients.


Using NLP to Activate, Reactivate and Build Brand Awareness

Our client is a national clothing retailer with multiple subsidiaries. For this program, we were working with the following client segments: basics for all; full-figured apparel; fashion forward for younger consumers; and women’s apparel.

This client’s challenges were not unlike many other retailers or, for that matter, any B2B or B2C clients we have today:
  • To activate and find new users (across all brands)
  • To reactivate dormant users (for two brands)
  • To build brand awareness

Our approach to helping our client with these challenges included utilizing their first-party data and segmenting customers based upon the partner’s use cases. We divided our client’s customers into active vs dormant users to segment out those consumers we needed to re-engage.  Within the active segment, we further differentiated between high and low-spenders so that we could identify unique behavioral signals to the high-spender group and find similar new customers across our network who we could engage on behalf of our client.

How to Activate High-Value Customers Leveraging Natural Language Processing and Machine Learning

Using our Data Cloud methodology, we developed deep insights around our client’s customers and provided actionable solutions catered to the specific challenges our retailer was facing.

Zeta’s Data Cloud is powerful due to 3 key pillars:
  • Identity: The heart of our database is identity and the permission-based users we have the rights to market to. We resolve identities definitively back to email which is a persistent identifier and more effective than cookies which have a short shelf life and can exist across multiple devices.
  • Behavioral signals: We “listen” to behavioral signals across the open Web and understand those signals to derive intent and build audiences around those signals
  • Connectivity: We connect the dots by mapping signals to real individuals and activating audiences across digital channels

At Zeta, we monitor over 2.5 million unique monthly visitors which translates into 18 billion content consumption signals on a monthly basis. We use that information and leverage NLP to translate those signals into audience clusters.


What’s in a Customer Signal?

Let’s spend just a minute talking about the importance of signals and what exactly they are. Signals depend upon content, subject matter, frequency, and recency. We use NLP to help us understand the content itself. For example, we may review topics from a blogging web site that reports on how to create chic maternity looks without using maternity clothing. Some of the keywords we might include might be things like accessorizing, cute clothes, affordable apparel. Once we identify the keywords and concepts from lifestyle blogs, we translate them into audience taxonomies.

Each cluster is derived from multiple keywords at different confidence levels.  For example, silk blouses is related to women’s clothing at a higher confidence level than say dry clean which is a more general term and relates to women’s clothing at a lower confidence level.  We then score consumers based on their content consumption, frequency, and recency of that consumption against these audiences.

There are two things to note about our audience taxonomies.  First, they are custom and growing where we’re continuously building new audiences based on our client needs.  Secondly, they are fluid where consumers move in and out of audiences in a real-time basis.  As an anecdotal story to bring these points to life, we created a Black Friday taxonomy based on customer demand.  Once developed, we saw a 12% day-over-day growth of consumers moving into the audience the week leading up to Black Friday, illustrating the value of real-time signals across our network.

We use environmental, transactional and most importantly, behavioral data to help truly understand the unique individual.  Each data point alone provides us some context around a customer, but it is the combination of these signals that provide us insights around individuals that we can activate in real time.


In the case of our apparel client, we analyzed 27.4 million customers across four of their brands. We found that 37% of those customers were not digitally connected, meaning our client didn’t have a way to communicate with these consumers through digital channels. We were able to match 14% of the digitally disconnected users to our permission-based universe where we have the rights to market to those customers.

We then matched their database against our network and found 47% of the client’s customers were active in our network. We performed a deep dive of the active vs. inactive and high vs. low spender segments to develop insights that were less intuitive than others. For example, we saw that moving and phone and internet services indexed higher for the basics for all brand which meant these customers were likely new movers. If consumers recently moved, they may have purged a lot of their apparel and are looking for a wardrobe refresh. The second interesting find was around frequent travelers. We saw customers interested in cruises and vacations indexed higher as well.  When thinking about vacations, consumers often look for new apparel to bring on their trips, especially when traveling from cold to warm weather locations and vice versa.

For each brand we found some interesting insights:
  • Full figured women were very active in their lifestyle and aligned perfectly with the athleisure wear explicitly designed for them by our client.
  • Our fashion-forward women’s wear group were frequent shoppers, new moms with most likely changing body types.
  • The women’s apparel group were HOH shoppers who were price conscious, looking for a good deal and high quality.


Acquisition, Reactivation and ‘Real-Time’ Customer Experience Journeys

At Zeta, we have behavioral signals for customers in market for specific products and services and can overlay the behavioral information with demographics of users active within our network.  We can identify consumers who are looking for women’s apparel deals, are interested in fashion-forward merchandise, or are social media influencers. All of this rich data provides us acquisition opportunities for our clients.

But, what about reactivation? The second client challenge was around reactivation. We looked at dormant customers as defined by the client – 5.8 million customers. Of those inactive users, 30% were active within our network in the last 30 days, meaning the consumers were still active across the open web, but just not with our client. We then took that segment of users and performed the same behavioral analysis to gain insights that would enable us to reactivate those former customers.

We bring to life all the rich insights we developed through the customer experience journey, based on the specific client use case: acquisition and reactivation. We monitor behavioral signals on a real-time basis, identify audiences to activate against based on our insights and engage them through an omni-channel approach with 1:1 messaging. Finally, we set up a continuous feedback loop so that we can optimize and refine our solution for our clients.

If you are looking to grow beyond your first-party data like this client, let’s talk! Are you interested in how you can identify audience clusters to activate on a real-time basis and monitor behavioral signals using NLP? Visit us at to learn more.

Zeta Global Acquires Temnos

Enhances Zeta’s Artificial Intelligence Platform with Ability to Classify Entire Internet

NEW YORK, January 23, 2019 – Zeta Global , a data-driven marketing technology company delivering 1:1 personalization at scale, announced today that it acquired Temnos, an AI analytics company that works with publishers and advertisers to analyze, filter and organize content to make it more engaging to visitor and more valuable to marketers.

The strategic acquisition delivers highly-valued customer intent capabilities to Zeta’s AI platform, specifically around natural language processing, enabling classification of the entire Internet. Enhancing Zeta’s people-based audiences, Temnos provides deep analysis of the entire web, segmenting patterns that identify vital purchase intent information based on consumer life events.

“Our clients are the true winners in this acquisition of Temnos as we strengthen our AI platform to help marketers pinpoint their most valuable customers through audience interest and intent detection,” said David A. Steinberg, Zeta Global CEO, chairman and co-founder. “This is an extremely exciting time to be in the digital marketing industry as we continue to knock down barriers to create technology that identifies personal needs and speaks to the customer on an individual level, rather than guessing what they need and how they want to be spoken to.”

Additional commentary about the Temnos acquisition from Zeta’s CEO can be found here:

Five Temnos employees from engineering and product development will be moved to Zeta’s San Francisco office.

About Zeta Global

Zeta is a data-driven marketing technology company delivering 1:1 personalization at scale. Leveraging proprietary data, advanced analytics and artificial intelligence, Zeta Global helps Fortune 1000, and Middle Market brands identify, acquire, retain and expand customer relationships. Founded in 2007 by David A. Steinberg and John Sculley, the Company’s highly rated ZetaHub technology platform has been recognized in Gartner’s Magic Quadrant for Digital Marketing Hubs (February 2017) and in its Magic Quadrant for Multichannel Campaign Management (April 2017) competing with offerings from Oracle, IBM, Salesforce and Adobe. Operating on four continents with 1,300+ employees, the company is headquartered in New York, with offices in Silicon Valley, Boston, Nashville, London, and Hyderabad, India.
using automation to personalize at scale

10 Marketing Automation Do’s and Don’ts For Your Business

Today’s consumers expect customized experiences and on-demand engagement at the channel of their choosing.

Nearly all marketers now appreciate the impact personalization can have on improving customer relationships and conversion. According to recent research by Researchscape, almost all believe it has at least some impact while “Seventy-four percent believe personalization has a ‘strong’  or  ‘extreme’ impact on advancing customer relationships.”

marketing automation personalization at scale

Understanding the power of personalization is the easy part. Executing it is much more complicated. Serving thousands, or even millions, of individuals with customized content and tailored experiences is a formidable mission for even the most dynamic CMO. No marketing department or agency on the planet can deliver handmade marketing to every single customer at any significant volume.

There’s only one way marketers can personalize at scale: automation. But not all automation is created equal.

Smart Automation: How Marketers Can Personalize at Scale

Marketers have been drawn towards tools that enable them to send tailored content to their leads and customers for years. Some 49% of companies are already using marketing automation and more than 55% of B2B organizations use the technology.

However, most of them have yet to realize its true potential. They still rely mostly on basic rule-based marketing automation software rather than responsive, adaptive artificial intelligence (AI)-based solutions.


You should also read: The Artificial Intelligence and Personalization Buyer’s Guide

Are You Making the Most of Your Automation Budget?

Global spending on marketing automation will crest $25 billion by 2023. Unfortunately, much of that investment will be put toward suboptimal technologies or get hamstrung by ineffective policies. Make sure your ROI is optimized by following best practices and taking advantage of the most powerful tools available to provide compelling personalized experiences for your audience.

How Marketers Can Personalize at Scale

Editor’s note: This is an update of an article and graphic published last year by our partners at Boomtrain.

Consumers Want to Get ‘Personal’… Is AI Filling the Need?

As marketers, we’ve all heard about personalization, and personalized emails … and getting personal with consumers, but are we responding appropriately to propel our brands into the hearts and minds of consumers? Are we truly embracing person-based marketing, or are we faking it until we can make it? Perhaps we should be taking a closer look at how artificial intelligence (AI) can help us get there. Doing so, we may even learn how to significantly increase our revenue per subscriber.

We recently partnered with The Relevancy Group to find out how AI is being utilized for personalization and how confident marketers are in learning the capabilities of these machines. Our survey report of over 400 marketers entitled, “Powering Person-Based Marketing via Artificial Intelligence,” provides great insight into the minds of marketers who are having success and their strategies for creating a goal-oriented implementation and roadmap to ensure AI personalization efforts. Here’s a sneak preview of some of our key findings:

Email Marketers Using AI Personalization Outperform Human-Curated Personalization
  • AI email marketers outperform their human-curated peers in every email metric.
  • Marketers using AI are driving higher revenue per subscriber.

Consumers Demand and Expect Individual Personalized Experiences
  • Consumers are demanding relevance and a unified customer experience across all channels.
  • Lack of relevance is the key reason why consumers ignore or opt-out of email.
  • Customer experience heavily drives brand selection.

How are marketers using Machine Learning (ML)? This type of AI that uses data to train an algorithm so that it can learn how to accomplish a specific task on its own, is very highly rated. When AI is applied to massive amounts of structured and unstructured data to provide a person-based individual experience, marketers shared these experiences:

Confidence in AI Program Capabilities Continues to Grow   
  • Less than five percent of marketers surveyed said they were not confident in AI improving their customer experience.

So, if AI is proving to be such a powerful weapon in the fight to obtain person-based marketing, what is preventing every marketer from using it?
  • Management of copious amounts of in-house customer data.
  • Ease and time needed to deploy.
  • Integration with existing CRM data.

To get all the specific stats about how marketers are blazing a path forward with AI using personalization, please join our webinar on June 13th.  Our own David Schey, SVP of customer experience, will share insights from our customers’ success stories and help answer questions about how you can achieve success in your program.
Machine Learning

Machine Learning is the Future of Email Marketing

Learn how machine learning and AI make today’s modern email marketers do so much more while dominating their competition.

Machine learning is the single best new technology for today’s email marketers. 

Machine Learning for Email Marketers
It’s the secret to:
  • Getting your emails opened and driving engagement.
  • Knowing what content to send to exactly the right person.
  • Finding more hours in the day.
  • Moving all the needles all the time.

So, what will I learn from this ebook?
  • What Machine Intelligence really means for marketers is that machines are finally good enough to operate without so much oversight from us – they have become an extension of us.
  • Machine Intelligence gives you back time by tirelessly working and building, targeting, and delivering emails on a level no human can accomplish alone.
  • Machine Intelligence makes your emails cut through the noise by keeping your messaging relevant and timely for each user at an unlimited scale.
  • …and so much more.


Please fill out the form below to view the webinar:

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Financial Services Marketing

The Future of Relevance – Financial Services

More precisely target people on an individual basis – at scale – by going beyond CRM and context targeted tactics. In this whitepaper customized for the Financial Services industry you will learn how to utilize Identity Management best practices within a Precision People-Based Marketing (PPBM) framework to recognize the customer as a person.


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