Why Email Can’t Be Overlooked for Customer Acquisition

Even in the midst of an increasingly dynamic technology landscape, email is the backbone of modern customer acquisition.

Why email can't be overlooked for customer acquisition blog

In a world where consumers are being bombarded with ads and marketing messages, it’s getting harder and harder for brands to stand out from the crowd. As such, many digital marketers feel pressured to adapt new, unproven strategies to reach the right prospects and hit their customer acquisition goals. But is this wise?—Probably not. The truth is, it’s the tried-and-true methods of reaching people that still perform the best when it comes to converting prospects into customers. Which is why—even in the midst of an increasingly dynamic technology landscape, where consumers enjoy so many avenues to purchase—it’s email that still forms the backbone of modern customer acquisition.   

Email is ubiquitous tool for communication

Email is one of the most intuitive, inexpensive, and widely available modes of modern communication. It is as convenient for consumers to use (low-barriers to entry) as it is for businesses, and when it comes to marketing reach, it can be virtually limitless depending upon a brand’s access to first- or third-party data.

Email is effective—really, really effective 

As far as marketing channels go, none is as across-the-board effective at transforming consumers into customers as email. Email helps marketers reach people with timely messaging that encourages them to shop in-store and online. Moreover, email makes it simple for brands to stay top-of-mind with prospects, which not only increases the likelihood of direct sales, but it also broadens general consumer awareness (increasing the possibility of indirect or referral sales). It is that kind of efficacy that allows email to drive the best ROI of any channel available to marketers. 

Email acquisition is fast to set up, execute, and optimize

Compared to many other modes of new customer acquisition, email is quicker to set up, run, and optimize. Much of this speed is derived from AI, which makes personalizing email content content and product offerings based on individual interests, demographics, and real-time behaviors (pulled from continuously updated consumer profiles) a snap. Always-on predictive insights allow marketers to effortlessly optimize everything from the subject line and template design, to send time and send frequency. The best platforms for email acquisition will also accommodate enterprise-level volume, provide advanced sequencing, and offer continuous optimization so it’s straightforward to both acquire new customers and engage current ones.

Email offers marketers incredible personalization

Personalization greatly influences customer acquisition—the more personalized the message, the more likely it is to resonate with the consumer. And the more resonance a marketing message can create, the better its odds of transforming a consumer into a paying customer. In terms of reaching potential customers at scale and in a personalized way, few if any digital marketing mediums can compete with email. With email, marketers can personalize content based on a long list of factors including: content consumption, transaction history, location data, gender, age, and more, making it easy to provide hyper-relevant content to prospective customers at just the right moment in time.

Email is what people want

A personalized brand message or promotion is great—but if it isn’t delivered in the channel people want to see it, it’s going to fall flat. As far as marketing goes, the one channel consumers consistently prefer over all others is email. Why? Well, here are a few reasons. In addition to being flexible enough to adapt to the experiential preferences of an individual consumer (e.g., adjusting for dark mode), it’s easy to personalize, it isn’t restricted to arbitrary character limits (e.g., a sponsored post on Twitter), it requires more thoughtful consideration to produce than other forms of content (e.g. SEM advertisements), and it comes with certain protections (e.g., authentication checks, etc.) that make people feel more at ease it comes to engagement.

Email is more necessary than ever

One of the reasons digital is such an effective medium for customer acquisition is its connection to identity technology. This is especially true as consumers spend more time on an ever-widening array of digital devices and channels. Without identifiers, marketers would struggle to understand how their spend drives everything from engagement to acquisition to incremental revenue. The threatened loss of the cross-domain IDs (as announced by Google) and mobile-ad IDs (a.k.a. MAIDs, as announced by Apple) means marketers may soon be without one of their most effective weapons in the fight for new customers. So, where does email fit in the picture? Well, if cross-domain IDs and MAIDs disappear, email will be one of the few suitable identifiers left for marketers to tap into for customer acquisition. 

Using email as an identifier (as part of a broader, integrated acquisition platform) will allow marketer to be more responsive in their communication with prospects, provide more consistent messaging, and be more accurate in measuring results. Coupled with AI, marketers will retain the ability to personalize at scale, and more rapidly adapt to changing consumer engagement patterns. Would email be a perfect replacement for cross-domain IDs and MAIDs?—Of course not, but it will certainly help alleviate some of the pain marketers might otherwise feel.  

Customer acquisition is important. We’re here to help.

Talk to Zeta—Our experience using email as either a standalone acquisition solution or as part of a broader, omnichannel acquisition approach is second-to-none. Whether you need advice, actionable insights, or straight up results, the acquisition experts at Zeta are here to help.

Zeta Global Announces Successful Completion of Debt Refinancing

New term loan carries significantly lower interest rate, provides Company with additional capital and facilitates repayment of outstanding debt.

Zeta Global Logo

NEW YORK, NY – March 1, 2021 – Zeta Global, a marketing technology company that leverages unique data and predictive AI to help brands acquire, grow and retain customers, today announced that it has successfully closed a $222.5 million loan facility to provide additional capital to pursue new initiatives. This new debt is a combination of Term Loan A and Revolving Credit Facility, which gives the company increased flexibility.

“We are pleased to announce this refinancing, in conjunction with our banking partners, which serve a number of long-term advantages for Zeta’s business,” said David A. Steinberg, Zeta Global Co-Founder, Chairman, and CEO. “This will generate significant savings by reducing our interest by less than half the cost of previous loans and provide us with additional capital, which will serve to further expand Zeta’s cutting-edge capabilities. As we continue to improve the Company’s capital structure, we are working hard on new initiatives and are excited about the next chapter of Zeta.”

Previously, Zeta’s loans have been utilized as working capital to complete successful acquisitions and integrations of companies including AI pioneer BoomTrain, publisher commenting platform Disqus, content intelligence platform Temnos, and advertising suite platform Sizmek. All have strengthened the technology and data capabilities of the Zeta Marketing Platform, making it one of the leading marketing technology platforms in the industry today.

Chris Greiner, Chief Financial Officer states, “The strategic refinancing is a proactive step that meaningfully improves Zeta’s overall capital structure and strengthens our liquidity, reduces our borrowing costs and provides us with additional financial flexibility. We appreciate the continued support from our banking partners who see an abundance of opportunity in the future of our business.”

BofA Securities, Inc. served as Lead Arranger and Bookrunner. Barclays, Credit Suisse, and Morgan Stanley Senior Funding, Inc. are also participants in the facility. Matthews South served as the financial advisor to Zeta.

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ABOUT ZETA GLOBAL
Zeta Global is a data-powered marketing technology company that combines one of the industry’s largest consumer data sets (2.4B+ global identifiers) with results-driven artificial intelligence to unlock consumer intent, personalize experiences, and power business growth for Fortune 1000 companies, such as GM, Wyndham, Sprint and Progressive. Zeta has been recognized as a Leader in the Forrester Wave™ and competes with marketing cloud offerings from Oracle, SAP, Salesforce and Adobe as well as programmatic platforms including The Trade Desk. Founded in 2007 by David A. Steinberg and John Sculley, the Company is headquartered in New York City. For more information, please go to www.zetaglobal.com.

3 Next-Generation Lookalike Modeling Trends for Marketing and Advertising

Is lookalike modeling important to your marketing efforts? Here are 3 next-gen lookalike modeling trends you need to know.

lookalike modeling trends

The exploding use of lookalike modeling within digital in the last decade is tied to the evolution of machine learning’s ability to drive ROI across the funnel. Yet there’s still a lack of clarity on the best lookalike modeling trends to use and where to use these approaches. Additionally, as most of the attention goes to the algorithms that power machine learning, very little consideration is given to the actual inputs (data) that fuel lookalike modeling trends in the first place. Given the complexity of lookalike modeling, this pattern is concerning. 

Lookalike modeling is both an art and a science.

The inputs (and how those inputs are combined) influence the eventual predictive power of a lookalike model more than any machine-learning algorithm.

As complex lookalike algorithms continue to become readily available, data becomes the ultimate differentiator.

Having predictive and proprietary data that is relevant to your business is not only a significant competitive edge. Moreover, it increases the predictive power of lookalike models, irrespective of the application of the model (customer retention, personalization, acquisition, or other CRM activities).

For example, testing the 3,500 proprietary data signals contained within Zeta’s Data Cloud indicated a huge influence on the predictive power of Zeta’s lookalike modeling for both CRM and acquisition. (In other words, using the right kind of data in your lookalike models is both a real differentiator and an advantage.) 

So, with all of that said, here are 3 Next-Generation Lookalike Modeling Trends for Marketing and Advertising…

Trend #1 – Lookalike models transition from supervised to unsupervised learning approaches

Lookalike models are used to characterize the dominant traits of a specific set of records (be they audience segments, campaign convertors, or something else entirely), especially against another set of records opposite in nature.

For instance, lookalikes of a set of convertors are built by mathematically teasing out the dominant traits of said convertors and then comparing them to a set of non-convertors. 

The algorithms that power this comparison-based lookalike model are known as “supervised learning algorithms”, and they do a great job of describing “labeled” audiences.

In the example above, the labels indicate whether a record is a “convertor” or “not a convertor.”

But it is in situations where labeled data is not readily available that true marketing and advertising ROI is achieved. For example…

  • Why does a customer make multiple purchases from you, and what are the traits of those customers? 

Or…

  • What insights are you missing from your campaign because you’re looking in the wrong place?

Answering these questions (and addressing other situations where labeled data is not readily available) requires incorporating  “unsupervised learning algorithms” into lookalike modeling.

Unsupervised algorithms don’t require labeled data and they don’t need to be “told” what to find. They can analyze the available data to find hidden patterns within campaigns, audiences, and more.

The patterns discovered are a goldmine of actionable opportunity for marketers and advertisers which is why the shift from supervised to unsupervised learning algorithms is happening slowly but surely. 

Trend #2 – Keeping humans in the loop to ensure modeling accuracy

The algorithms used to power lookalike models regularly provide an accurate approximation of what’s happening in the real-world.

However, they’re not perfect.

When allowed to run loose without any human oversight, they can create inaccurate models.

For example, given a set of inputs, an algorithm designed to identify lookalikes of a prospect who signs up for a credit card can over-index on traits that aren’t compliant with fair credit lending practices.

As a result, marketers and advertisers might fail to reach key underserved populations. To ensure inaccuracies like this don’t happen in their lookalike models, marketers and advertisers are increasingly keeping people in the loop.

By allowing human eyes to review the initial findings of a model and approve (or reject) its use for downstream purposes, marketers and advertisers can mitigate their exposure to risk from the deployment of an inaccurate model. 

Trend #3 – Data distribution using sub-models will power lookalike modeling

“Data privacy” is a buzzword in marketing and advertising these days—it commands the attention of consumers, regulators, and agencies alike.

As a result, no marketing or advertising professional wants to obtain insights about customers or prospects that aren’t privacy compliant. This reality casts doubt on the future of data appending by way of sharing owned, first-party data with external, third-party data vendors that provide enrichment services. 

Going forward, lookalike models will be built and distributed using multiple sub-models which will determine where the data resides.

The outputs from these sub-models will come together in a secure, cleanroom location where they’ll be collated so a primary modeling decision can be made.

This will be a departure from the current state of lookalike modeling where all the data required to build a model is pooled in one location.

Wrapping up lookalike modeling trends for marketing and advertising…

In the years ahead, lookalike modeling will continue to embrace more sophisticated, accurate, and distributed techniques that increase ROI.

Marketers and advertisers would be wise to stay ahead of these emerging lookalike modeling trends so they can ensure they’re always obtaining the best business outcomes possible for the brands they represent. 

To learn more about lookalike modeling trends, please reach out to a member of our expert panel or visit our resources page for additional reading.

How To Decrease Cart Abandonment With Website Personalization

Looking for ways to decrease cart abandonment on your site? Learn how website personalization can help in our latest blog.

Decrease cart abandonment

In today’s ecommerce industry, cart abandonment occurs at an alarming rate—almost 70% of online shoppers walk away from their cart without completing a purchase. Moreover, cart abandonment costs the economy anywhere from $2 to $4 TRILLION dollars per year. While the reasons for abandonment are many—high shipping costs, expired discount codes, lengthy delivery timelines, etc.—there’s no better way to decrease cart abandonment than with website personalization. 

Consumers want and expect personalized experiences

Recent data shows 80% of consumers want personalized experiences from brands. Why? Because a 1:1 experience makes the buying journey seamless. Instead of browsing your inventory aimlessly, visitors can land on your website and find exactly what they’re looking for. And when you meet consumer needs and expectations in a more effective way, you increase the likelihood of a completed transaction.

5 Website personalization strategies that reduce cart abandonment

While there are several ways to improve website personalization, we believe the following five strategies are the best place to start.

1. Tap into known customer tastes with on-site recommendations

One of the biggest complaints consumers have is on-site overwhelm. Whether shopping for a summer dress or a new skincare routine, online shoppers regularly feel lost because there are too many products to choose from. This feeling of overwhelm cultivates frustration, and frustration often leads to cart abandonment. To combat this problem, invest in making smarter on-site product recommendations by tapping into known data about your customers. This data can be first-party or third-party, so long as it enables you to make recommendations that are more relevant and timely for the customer.

(Image source: Retailreco)

2. Leverage overlays at the first sign of potential abandonment

The moment a visitor moves to leave your site or interrupt the checkout process, deploy an overlay to remind them about the items still waiting in their cart. For price-sensitive consumers, provide an incentive such as a discount code or free shipping to get them to return to their cart and complete the purchase. By interacting with online visitors at this crucial moment in the customer journey, you can easily motivate them to finish their purchase.

(Image source: WisePops)

3. Offer additional complementary products at checkout

Using known cart information, you can offer shoppers complimentary products at the point of checkout to create extra incentive to complete their purchase. Consider add-ons such as socks for a sneaker purchase or a setting spray for a makeup purchase. These items are not only “nice-to-haves” that excite and delight the shopper (which pushes them through the checkout process), but they’re highly relevant because they’re tied to the primary purchase.

4. Optimize landing pages and menu bars

No matter how many visitors come to your site, each unique landing page needs to create a perfect first impression of your brand. That means you must design personalized landing pages tied to user browsing history, geolocation, time of day, etc. Doing so will enhance the customer experience and increase the likelihood of a purchase. Similarly, reorganize your navigation bar based on affinity or category preferences to help shoppers find products more quickly and efficiently, which helps increase the likelihood of a transaction.

(Image source: VWO)

5. Continue personalized messaging on additional channels

It’s important to note that personalization strategies to reduce cart abandonment shouldn’t end at your site. Oftentimes consumers get distracted or are browsing on mobile but want to complete the purchase on a desktop. An abandoned cart doesn’t always equate to a lost sale, which makes personalized email reminders an effective way to encourage cart abandoners to return to your site. Use messaging and creative specific to what the shopper was interested in, and remind them that their cart is ready for checkout. For an extra added incentive, consider including a promo code in your email nudge.

(Image source: Sleeknote)

Want to learn more about decreasing cart abandonment with website personalization?

Check out our recent blog post discussing Zeta’s approach to website personalization and how it can help markers enhance engagement across the customer lifecycle.

What Does a Next-Generation ID Graph Look Like?

What’s the difference between a traditional ID graph and a next-generation ID graph? We cover the differences in this blog.

There are two types of ID graphs in the world: the type that everyone is using today, and the next-generation ID graph that everyone will be using tomorrow. While discussions about ID graphing aren’t the most riveting in the world, they’re important for marketers. Especially, in a sputtering economy that’s struggling to recover from a global pandemic and recession. So, what does a next-generation ID graph look like? More importantly, how does it outperform the ID graphs that are out there today? Keep reading to find out.

A quick refresher on ID graphs

Any conversation about ID graphs starts with an understanding of mapping tables. Why?—Because all an ID graph does is map digital IDs from one company to another. The mapping is due to each company having different “name spaces” (= dictionaries of ids that map to their internal data stores). 

Identity resolution is the process of taking disparate IDs (addresses, emails, MAIDs, cookies, etc.) and relating them to a person-level or a household-level concept. Identity resolution effectively addresses the relationship among the identifiers (addresses, emails, MAIDs, cookies, etc.) and hence maps devices to the concepts of people and people to households. 

The more quickly and efficiently you can resolve the link between the identifiers and the concepts of real people or households, the more effective you will be in your marketing.

Batch-mode processing

Older ID graphs rely on batch-mode processing to give marketers the consumer insights they need. Unfortunately, batch-mode processing is no longer efficient or effective—it takes too much time.

When an ID graph operates using a batch-mode process, you (the marketer) are looking at a week-long turnaround time from when you submit first-party data to the data processor and when you get your enriched data back.

That’s at least five business days to process, clean, map, and then enrich your customer data. Then, and only then, is it ready to be syndicated to the various engagement platforms you use to match your content to your desired audience.

Latency is a big issue

Just because you have data in a database doesn’t mean it’s valuable.

Data isn’t valuable to a marketer—data is only valuable when it is used.

The utility of data is tied to actually matching content to people and improving this match.

Only then does data start to have an impact on reaching the right audiences, influencing media spend, hitting the prospects most likely to engage, and more. 

With batch-mode processing, you’re going to wait at least a week to get your enriched data back, and a lot can happen in that time.

A prospect who was in-market when you provided your data to the data processor, may no longer be in-market by the time your enriched data is ready for activation.

What to look for in a next-generation ID graph

Time matters when it comes to ID graphing, so look for a partner that can offer real-time, closed-loop enrichment and engagement (such as Zeta) versus a traditional batch-mode processor (such as Salesforce, Oracle, or LiveRamp).

A next-generation ID graph provider will be able to take from a robust, known-universe of customers and use the insights gleaned to help you obtain your next customers from unknown users. 

What about privacy? It is important with whichever partner you select, they respect people’s privacy rights—do they have consent to associate people’s activity to their identity?

Also look for partners that can help you with prospects with whom you do not yet have a relationship. After all, most advertising is to help acquire new customers who are demonstrating a propensity (i.e. interest and intent) to become your customer. 

Again, the distinguishing factor between the current generation of ID graph and the next-generation ID graph is the closed-loop, real-time optimization system.

This system reduces the latency between obtaining the data that lets you know WHO you want to talk to with your marketing, and actually activating that insight (i.e. putting your marketing right in front of them). 

So…

  • Do you really want to work with a batch-mode partner whether they’ll be days and weeks of delay between data enrichment and activation? 
  • Or do you want to work with a company that’s built to provide enrichment and activation in real time?

Remember, data of and in itself isn’t a source of value.

Data at rest does nothing for your marketing.

The amount of data you have in your database is merely a curiosity metric—it doesn’t actually create value. If you want to put that data to use, you need to work with a partner running a next-generation ID graph so you can activate your data, extract value from it, and measure the significance of the value your marketing is creating over time.

Zeta Appoints New Chief Data Officer to Lead Global Data & Analytics

We are thrilled to announce the appointment of Neej Gore as our new Chief Data Officer!

NEW YORKFeb. 16, 2021 /PRNewswire/ — Zeta Global, a marketing technology company that leverages unique data and predictive AI to help brands acquire, grow, and retain customers, today announced the appointment of Neej Gore as Chief Data Officer. Gore was previously Chief Business Officer at Boomtrain, the AI pioneer that Zeta acquired four years ago, and more recently President of the Data Cloud division at Zeta.

In his new role, Gore will lead the Company’s global data and analytics strategy, creating growth for brands by transforming data into actionable business insights, and continue the development of Zeta’s large identity graph. He will also be responsible for driving further innovation within Zeta’s Opportunity Explorer, a real-time market and consumer data solution that provides companies with the insights needed to thrive in today’s digital economy.

“I am thrilled to continue advancing Zeta’s Data Cloud, which we have proudly grown to be one of the largest proprietary consumer data assets in the world,” said Gore. “Data literacy and insights have become essential for every enterprise business to connect with consumers at an individual level, and to do that successfully, they must have strong identity and intent based data solutions. I look forward to furthering our mission at Zeta to help marketers acquire, grow and retain customers and combat their toughest challenges.”

Gore’s previous accomplishments – including the expansion and fortification of Zeta’s Data Cloud, and the success of the Opportunity Explorer – made him a natural fit for the new role, according to Zeta Co-Founder, Chairman and CEO, David A. Steinberg:

“As consumer behavior continues to rapidly evolve in today’s digitally accelerated world, data-led digital transformation strategies have become critical for businesses to sustain growth. Neej’s talent and expertise will help our customers navigate the future of marketing with actionable insights that range from predictive market trends, to individual consumer intent, and I’m eager to see how he helps enterprises take advantage of the future of intelligence.”

As Zeta further expands its data footprint with the appointment of Gore to Chief Data Officer, the Company will continue to invest in consumer privacy protection, transparency, and Privacy by Design, as described in detail in the Zeta Privacy Policy.