email platform infrastructure

Overcoming a Critical Retail Marketing Challenge: Customer Acquisition

Editor’s note: This article and interview were orchestrated by Zeta Global’s SVP of Customer Experience, David Schey. Connect with him and get more insights on LinkedIn.

An interview with Brendan Witcher, Principal Strategist, eBusiness & Channel Strategy, Forrester

Earlier this year we sat down with Brendan Witcher, principal strategist, eBusiness & Channel Strategy at Forrester to talk about retail trends at NRF. We recently checked back in with Brendan to see if retailers are making good on their promises when it comes to acquisition strategies in 2018.

Let’s recap the trends Brendan outlined at NRF…
  • In 2017 – Personalization and omnichannel were key trends with retailers.
  • In 2018 – Personalization and omnichannel are still big, but…maybe retailers don’t understand their customers well enough to personalize the experience or, maybe they don’t understand their business well enough to optimize a retail omnichannel strategy.

Brendan’s Advice for Retailers at NRF: “Focus on the “unsexy” work you haven’t gotten done to optimize your personalization and omnichannel programs.”

 “Focus on the “unsexy” work you haven’t gotten done to optimize your personalization and omnichannel programs.”  

We think retailers were listening. At Zeta, we’ve been hard at work with our retail clients all year helping them focus on optimizing personalization through their use of data. We have a phrase we use a lot around the water cooler here: “We know your customers, you just don’t have them yet!” Yes, it does sound a little out there, but it’s true.

How do we do it? We focus on people-based audience acquisition. We leverage customer signals, deterministic data and native artificial intelligence to deliver 1:1 personalization at scale. We target specific customers by identifying who you want to talk to, not who you think you want to talk to.

We think it’s pretty cool that a little after the mid-year mark, retailers are transforming their data programs from “unsexy” to “sexy” work. But, we wondered if Brendan is seeing the same pivot from the retailers he is talking to on a daily basis. Here’s what he had to say…

We asked Brendan if retailers are doing the work they set out to do, specifically are they:
  • Finding value in their customer data?
  • Capturing their data correctly to create better customer experiences?

He told us that retailers are making progress on the objectives they stated earlier in the year:
  • To be more data-driven
  • To engage with customers at the individual level

In doing so, he also said that new challenges have arisen that have slowed their progress, mainly:
  • Cultural roadblocks
  • Siloed organizational agendas

How do you get around that? Brendan suggests obtaining quick wins with data and showing how data-led marketing can have the greatest impact. He went on to say that some of the same marketers who are facing these retail omnichannel strategy challenges above are building the business case to have their organizations lean heavier on data—in both their strategic decision making and their tactical campaigns.

Brendan’s Keys for Success?
  1. Find and focus on the areas that have high impact on your customer.
  2. Make sure your organization is operationally set up to execute on the digital tools you have.

To learn more about how we can help you achieve personalization at scale through your data, contact us for a personalized demo.

How to Choose the Best CRM Solution for Your Enterprise

When it comes to customer relationship management, not all technology is created equal—especially when operating on an enterprise scale. The solution you ultimately choose will provide the foundation for understanding your customers and meeting their growing expectations. That, in turn, will determine the ROI of your marketing and success of your brand for years to come.

Choose wisely.

Diamonds in the Digital Rough

The marketing technology landscape is expanding at a terrific pace. Thousands of solutions provided by no fewer than 6,242 different vendors are available to today’s CMO—27% YoY that’s likely to continue.

Included in the flood of evolving technology are at least 200 customer relationship management solutions, including established providers and disruptive new startups. How does a marketing leader at a large business with an enormous audience chose the right one?

Key Considerations for Choosing an Enterprise CRM

Enterprises have some unique challenges in meeting the ever-changing expectations of today’s connected consumer. It’s one thing to recognize the value of personalized, relevant experiences—but delivering them to hundreds of thousands ,or even millions, of individuals around the world is a daunting task for the most capable CMO.

enterprise CRM quote

Choosing an enterprise CRM that enables you to serve 1:1 experiences on a massive scale can mean the difference between earning loyalty and being forgotten. When comparing your options, take special care to consider the following factors:

Data Treatment

The key to understanding your customers as individuals, anticipating their needs, and engaging them in real-time lies in data.

Big data has been at CMOs’ top-of-mind for years now; finding ways to organize, interpret and act on the mountains of consumer information now available remains a high priority.

Almost every CRM has some amount of data analytics capabilities. But that can range from rudimentary web analytics to sophisticated deterministic data science.

Ideally, an enterprise CRM will provide access to a large pool of proprietary data that can be used to supplement and enhance your own first-party customer data. Enterprises often struggle with large silos of disparate data—a good CRM option also will be able to flexibly adapt and unify those scattered resources into a single view of your customers.

Today’s consumers are active on a broad selection of channels and devices at any given time. An effective enterprise CRM must be able to accumulate real-time signals from any input and translate them into thoughtful omnichannel responses.

Finally, a great enterprise CRM needs to be extremely secure when it comes to data and align to quickly-evolving social and regulatory privacy standards. Given the sheer volume of data a large organization handles and the sensitivity of the information within, enterprises can’t afford to take chances. Recent history is full of high-profile breaches that compromised corporate and customer data and tarnished brands—don’t let your marketing technology platform be your biggest vulnerability!

Automation Capabilities

Automation is what enables an enterprise to take a powerful, relevant, personalized customer experience and scale it up to thousands or even millions of individuals around the world.

Most CRMs have some automation capability, many of them lack the capacity to constantly process and manage a compelling relationship with every customer. Seek out a provider that has the sophisticated AI technology needed to capture and interpret a flood of real-time customer signals and decide when, why and how to respond.


Most enterprises have an enormous tech environment that includes legacy systems, scattered databases, and third-party vendors. Even large organizations with robust IT teams find integrating new tools and platforms into their stack to be incredibly difficult.

An ideal CRM tool for enterprises is one that can flexibly adapt to your existing technology and data infrastructure. A quick onboarding process and the ability to unify customer data all in one place is a huge advantage in the perpetual battle for consumer attention and loyalty.

What the Experts Say

Shopping for the best CRM for your enterprise is an arduous process, but choosing the right one can quite literally determine the success of your company for the indefinite future. Fortunately, there’s no shortage of resources and expertise to pull from when selecting a solution that will bring the most value to your customers.

One such authority is the prestigious MarTech Breakthrough Awards, which recognizes leaders and innovators in the diverse and ever-changing world of marketing and advertising technology. This year, Zeta Global’s technology platform ZetaHub was awarded ‘Best CRM Solution for Enterprise’—standing out in a pool of over 2,000 nominees.

marktech breakthrough best CRM for enterprise

“The days of linear marketing are long gone, and multichannel marketing is now a necessity, but we find that many enterprise organizations are struggling with the challenge of managing this more complex customer journey,” said James Johnson, Managing Director at MarTech Breakthrough. “Zeta Global’s ZetaHub shines when it comes to enabling multichannel dialogue, empowering global brands to engage with customers and prospects across email, mobile, social, direct, and web. Congratulations to Zeta Global on its 2018 MarTech Breakthrough Award!”

Read the complete press release from MarTech Breakthrough here.

Click here to see Zeta’s announcement of the award.

Every day we work closely with our enterprise clients in Retail, Travel, Finance, Insurance, Media and beyond to better understand their customers and develop lasting 1:1 relationships. It’s not hyperbole: to see for yourself how our solution makes people-based marketing at scale possible, request a demo today.
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.

How to Follow a Customer-Centric Acquisition Marketing Approach — An Interview with Eric Presbrey

Eric Presbrey, president of Zeta’s ZX division, is charged with helping leading brands build digital audiences and create new customers. The Zeta ZX division works across all digital platforms, devices, formats, audiences and channels integrating Zeta’s platform with its Data Cloud containing 650M+ consumer profiles to build targeted audiences. Today, Eric is sharing how ZX can help marketers acquire the right customers for their individual brands.

Q: What are the most significant challenges marketers are facing today?

Marketers are in a never-ending quest to engage new customers and encourage them to spend more with their brand. This challenge persists no matter the economic, social or cultural state of the consumer. However, the way marketers address this challenge is a moving target.

The current state we live in is a “see me, know me, and serve me” culture. This means marketers can no longer treat the individual consumer as a group and expect them to engage with their wallets.

To address the demands of the individual consumer and the current “me-first” mentality, brands need to redefine the way they approach acquiring new customers. They need to understand and deliver meaningful and unique customer experiences at scale. This requires connecting consumer data and orchestrating an always-on, personalized media strategy rather than limiting their approach to channel-based marketing.

At Zeta, we interpret billions of individual consumer signals and convert those signals into actionable digital engagement communications at scale. Our real-time ability to see customers behaviors and engage them across the digital eco-stem allows us to see, know and serve our clients’ customers.

Q: How is Zeta changing the face of acquisition?

Traditionally, acquisition has been viewed as a separate stage from the marketing continuum, but in reality, it is connected to the customer lifecycle at the earliest stage of the customer journey. At Zeta, we are connecting many of the same Customer Relationship Marketing (CRM) principles to the beginning of the customer journey at the individual person level. We refer to this front end of the customer journey as Customer Acquisition Marketing (CAM).

We view acquisition as a crucial component in addressing the key challenge of marketers — finding new customers and get them to spend more with that brand. Our real-time ability to view customers behaviors and engage them across the digital ecosystem allows us to see, know and serve our clients’ customers. Our experience delivering identity-based digital communications takes the principles of CRM and applies them to the acquisition process. We leverage our panoptic view of the consumer to develop highly-targeted digital connections using artificial intelligence to generate personalized content. We create meaningful results for clients by targeting customers within the right context and optimizing programs around the recipients’ most likely time to engage with an individual brand.

Q: In your role at Zeta, how do you view acquisition and which marketers stand to gain the most?

Typically, acquisition budgets are allocated by channel and not consumer. For those companies that understand the value of individual consumer engagement over channel marketing, there can be tremendous gains. Marketing to an individual based on profile tendencies, typical time of engagement, offer and content type, and message continuity across multiple digital channels will deliver much higher ROI.

Zeta’s people-based marketing approach targets audiences across multiple coordinated channels designed to deliver increased engagement results for our clients.

Within our permission-based DataCloud, we track thousands of deterministic data points, behavioral signals, consumer preferences and consumer intent data. We process that information in real-time creating an active customer record. This active record enables us to connect with a prospective customer when we know they are in market for specific services or products such as new car insurance, a mortgage or a cell phone. This powerful insight can then be leveraged across email, programmatic display, social or addressable TV.

Marketers who align around the individual and leverage the data to activate smart, coordinated, cross channel acquisition programs will win the early stage of the customer journey.

Q: You have a favorite saying: “We know your customers, you just don’t have them yet.” What does this mean? What is Zeta delivering to marketers that other vendors are not able to achieve?

At Zeta we have developed and refined the world’s largest addressable, 100% permissioned, people-based data cloud. We have the ability to connect with every prospective customer for any brand that is interested in growing their customer base with qualified new customers.

We have your customers; we see what they do, what they are interested in and what they may be likely to do in the future. We know when, how and why they are likely to engage, and we serve them with highly personalized content, ads and video that will interest them. This solution helps us develop sophisticated new customer marketing programs for clients that focus on delivering new customers who are ready to engage with their brands.

Q: What one thing should marketers be considering in 2018 to build their brand and increase ROI?

I’m going to sound like a broken record here, but…marketers must align their programs around — and market to — customers, not channels. Too often, marketers are guessing at attribution. A channel-based program supported either independently or by multiple ad and marketing providers, produces fragmented results because the data correlation is a guess.

Aligning acquisition programs around the customer and audiences rather than a channel, results in more accurate measurement and success of the program. Obtaining accurate attribution data, marketers can make better financial decisions around targeting, program strategy and media mix optimization…and connect more effectively with each prospective customer.
Behavioral Personalization

Behavioral Personalization Doesn’t Just Make Sense, It Makes Money

Behavioral Personalization is fundamentally shifting the landscape of customer communication.

Personalized content is giving marketers an unprecedented level of control over the levers that drive the Big 4: user acquisition, engagement, retention, and monetization. And the retail sector is one of the biggest beneficiaries of this new technology. Whether captivating new customers, retaining your consistent fans, or winning back lapsed consumers, inserting cutting-edge behavioral personalization promises a positive response.

Most segmentation is retroactive; using last month’s analytics to predict next month’s behavior. Today, this isn’t enough. Users have an abundance of choices, and their shifting preferences are a reflection of that environment. Behavioral Personalization Engines can ingest, analyze, and act on data in minutes, not weeks!

Our platform can also optimize for behaviors. So if you’re trying to drive purchases, social likes, or another KPI specific to your marketing campaign, the artificial intelligence technology can identify the segment of your audience that’s most likely to engage.

Contact us to learn more about our platform and how we can help your brand never miss a growth opportunity.

What you’ll learn:

  • How is this technique different?
  • Why are businesses choosing this solution?
  • How to boost revenue and see results

Discover why behavioral personalization is radically changing the face of marketing and how it drives revenue in our guide. Download below.

Download the eBook below to learn more.

[contact-form-7 404 "Not Found"]
product recommendation amazon

How to Ace Product Recommendation like Amazon

The best way for an eCommerce venture to succeed is by providing relevant products and content to the audience. Making the shopping experience as personal and tailored as possible for each individual consumer. Product recommendation has become the driving force for any eCommerce business.

Recommendation and personalization improves sales, conversion rates and revenue by a vast margin. And the leading example in this sector is Amazon.

Amazon is an eCommerce industry pioneer. And, when it comes to recommending products and personalizing the whole customer experience in relevance to an individual, no one does it better than Amazon.

A few examples of recommendation from Amazon (On and off their website/app) –

  • What Other Customers are Looking at Now

  •  Customers Who Bought Items in Your Recent History Also Bought

  •  Your Recently Viewed Items and Featured Recommendations

  •  Customers Who Bought [the chosen product], Also Bought –

And, now here are a few juicy bits about how a recommendation engine impacted Amazon’s sales and profit number –

  • 35% of’s revenue is generated by its recommendation engine. (Source)

  • This has contributed to a 29% increase in Amazon’s earning in the second fiscal quarter from the previous quarter. Learn more about it here.

These figures  lead us to only one statement and one question. Amazon has mastered the art of selling tens and hundreds of product to every individual customers with the help of its AI based recommendation engine. It’s considered as one of the best recommendation engine on the planet.

So now how do you emulate Amazon? How can you also cross-sell or upsell more products to your existing customer-base? Let’s find out.

Building your own AI recommendation engine

Yes, this is the perfect way to go, but only if you have a lot of capital and time to spare. Building your own AI engine might take years to happen, implementation on the other part, would take another 6-10 months time.

Ask yourself do you really have enough time and money that you can wait so much. Build an entire team from scratch to build an AI engine from scratch? No, right?

Building your own AI recommendation engine, is the ideal thing to do in a perfect world. Anything home brewed is as good as it can get, but one has to grasp the magnitude of the situation at hands. Development of your engine would take years and by that time you and your so called competition would be miles ahead of you.

So what do we do?

Well, there is an alternative. Read on to know more.

Using AI based product recommendation engine

AI based recommendation

As I said above,  problem at hands when it comes to emulating a recommendation model similar to Amazon is the capital and time investment. Developing such an in-house engine could cost millions of dollars as well as devoting thousands of hours to build it.

But with the advent of AI marketing brands like Boomtrain, the tech has become accessible to brands all across the globe.

Today an AI engine does the heavy lifting, otherwise done by marketers and engineers manually.  You don’t have to worry about spending hours and hours implementing a recommendation engine on your website. We’ve got you covered.

How does this work?

AI engines sits on top of your website and starts monitoring all user activities. Using technologies such as machine learning and deep learning, AI learns all user habits and what sort of products they are interested in. It analyzes all the key signals a that may emanate from a customer’s journey, like products bought, products browsed, pages visited, time spent of the website, etc.

Using these data-points AI stitches together cohorts as well as targets users on an individual level. As soon as the cohorts are ready and every user has been individually analyzed, the AI engine kicks into top-gear. It dynamically starts suggesting products on-site, as well as on other platforms such as emails and mobile based Push. Your work here is to just designate target pages and sections where such recommendation would take place.

And we are yet to discuss what’s the best part of AI based recommendation engines.

AI recommendation engines runs on your system all the time (yes, 24 X 7), forever learning and looking for new data-points based on user-behavior. It will constantly keep optimizing recommendations in search of higher conversion ratios and user-engagement rates.

Now, here is a brief of how AI recommendation engine will help your brand similarly to what Amazon has done –

  1. Reduce cart abandonment rates,

  2. Boost cross selling of products (if X bought this, he might also be interested in Y),

  3. Recommendation of  new products that a user might find useful but has failed to discover,

  4. Increased customer loyalty. You can learn more about it here.

  5. Address omnichannel brand communication to boost user engagement,

  6. Implement a 1:1 Brand to User personalization model.

In conclusion, using a recommendation engine that could emulate something that Amazon does, can be really beneficial for your venture. It will help you understand your customer’s journey better by seeing how they behave on your website, the time when they are most likely to make a sale, the time when they are most likely to open your emails, etc.

And hence, a recommendation engine would use this data to its advantage and target users with precise products that are likely to be bought by the user.

Personalization vs Segmentation: Why Segmentation is Not Personalization?

Often people use segmentation and personalization interchangeably. And, why not? Both marketing tactics’ goals are similar: Speaking to your customer in a relevant tone, so that user engagement rates increase.

The need for first person marketing (1:1 marketing experience) has never been this crucial as it is with a tightly-knit digital world. And, this has given prominence to marketing tactics like Personalization and Segmentation among marketers.

Marketing segmentation used to be the go-to tactic a few years ago. Marketers would collect demographic data from users, using which marketers would group them into categories and come up with different user personas. These data could consist of user behavior, their online journey, IP addresses, location, etc. An individual who has a purchase history of vintage products, would have brand communication filled up with more vintage products. Another user, who purchases more electronic products, would have those kinds of product in his or her emails, push notifications, etc.

Sure, segmentation is way better than the older marketing tactic like generic promotional emails or cold calls. But what if your user base is in millions, How can you be sure that all these users will fall under some or the other customer persona developed by you? There will at least be a few thousand users who will show completely different behavior compared to the masses. And it’s important to address them to, here’s why –

With the advent of digital age, the modern shopper, user or customer expects us to solve all their problems. Even if that is related to finding something as small as a pair of jeans. With the world being as connected as possible, most people tend to buy more online than offline. But, they still expect the same treatment as they get at brick and mortar stores.

This is where terms like marketing personalization were coined. A tactic where a brand talks to its customer on a one-to-one basis and treats them as an exclusive part of the brand experience.

Making a sale today is highly based on a brand’s image. People tend to shell out more, if the brand experience is stellar. They don’t mind the price if they are treated as someone important with respect to the brand. And personalization is a way to promote your brand image in that way. It provides a 1:1 experience where the brand directly speaks to the customer using unique data points.

It improvises on what we, marketers have done using segmentation. Now, let’s tell you exactly how personalization triumphs segmentation.

Personalization creates a deeper bond with a user than segmentation

Segmentation is a decent marketing tactic when it comes to providing a good product experience to your users. But, experience based segmentation comes as close as to adding the $$name$$ (let’s take Ryan as an example) to your email’s subject line and then add the same products for a given user cohort.

Such communication with users puts forth a lack of effort, basically your subject is a direct translation of – “Hey Ryan, we know your name and nothing else about you.”.

Personalization on the other hand takes a lot more time, but when it’s done with dedication the results are spellbinding.  A personalized email goes way deeper, with marketing collateral developed in a manner that’s unique and exclusive to every user.

Pro-tip: With today’s AI and Machine learning engine you can automate personalization efforts with these engine doing the task for you on a scale of millions of users.

Personalization gif

Sometimes, I take over 30 minutes to tailor and send an email to a customer, and damn it if I don’t break through the boredom of those of generic emails and get a elated responses from the reader!

After such experiences, the benefits are relevant to both parties, the seller and the buyer. I feel I have the best job in the world, and the consumer feels loved and important.

Personalization makes you a first person marketer

Here is another reason why Personalization is better than Segmentation:

It’s your first step toward becoming a first-person marketer.

Another marketing jargon, no, no, no! It’s a fundamentally a totally different approach to consumer communication.

A first-person marketer looks at a list of customers as individual. He or she addresses each and every user different, so that they are entitled to a unique experience.

This is what Segmentation lacks completely, it treats a group of users as an individual and messages loses it meaning with a few users from a user cohort. And therefore, for any marketer segmentation efforts have a higher failure rate than personalization.

On the other hand personalization is segmentation stripped down to the truest of its form.  It’s about tailoring a relevant experience at the most personal and individual level. Personalization allows marketer to focus on things that really matter to most of their customers.

Personalization is a step up from Segmentation

There’s a strong connection between personalization and segmentation. They might be different marketing tactics, but personalization has built upon what segmentation lacked. Without segmentation today, personalized marketing would probably not have seen the light of day.

The right approach to provide user a killer communication experience is a three-step process starting with data-collection and ending on personalization. Personalization can only be implemented into your marketing strategy, only after you have learned segmentation of customers.

Here is a simple step-by-step ascending structure of how personalization is implemented and what are the things that come before one has to implement personalization.

  1. Data-collection: The key to both segmentation and personalization on a large scale is to collect and have a robust set of customer data. The richer the data, the better will be your understanding of your audience. It will allow you to develop better segmentation and personalized marketing experience for your users.

  2. Segmentation: Once you have gathered enough data, you can start segmenting your users and grouping them under various major personas. The personas will have some type of similar correlation with the data you have gathered.

  3. Personalization: Once your audience segmentation has taken place, you’ll have enough data to identify which personas and segments have a potential to adopt to a personalized experience. You start with the most valuable customers and move down the order one-by-one. This enables to retain customers and also promote customer loyalty.


It all comes down to being a smart marketer in the end. Orchestrating your marketing strategy wisely to provide customers and users alike, a 1 to 1 experience of your offering is the ultimate goal of a marketer. Such an experience makes the user feel important and increases their trust on a product.

Moreover, it builds a strong brand image, and helps indirect marketing as well, like word-of-mouth promotion of your product. So, always try to collect user data, segment and finally personalize your user communication to provide your customers a highly effective interaction on all your inbound and outbound channels.

predective marketing

Predictive Marketing – Learn How AI Can Help Digital Marketers Ace Their Game

Artificial intelligence has never shown such prowess that it does today.

Predictive analysis is one of the key outcomes of this surge and AI is in the middle of the whole deal. One of the key branches that came out from Predictive analysis is predictive marketing. Predictive marketing has changed how marketers and sellers approach a prospect customer or user.

What is Predictive Marketing?

Despite the buzz around predictive marketing, a lot of people still don’t understand the term whole-heartedly.  People still find these complex terms as some sort of technology that their brand isn’t ready. Let’s end that today. 

Our definition of Predictive marketing is:

Predictive Marketing is the process where an AI engine embarks on collecting data on consumers and potential customers (visitors) behavior, web-journey, and engagement. Based on the collected data, AI and machine learning deliver relevant optimization and recommendation on the fly. This automatically drives higher user engagement and boosts your conversion rate. It recommends marketers and sellers what actions are more likely to succeed and which are more likely to fail.

In simpler terms, Predictive marketing can help you achieve your targets faster and enables marketers and sellers to concentrate on things that truly matter.

Digital marketing is three-step process, which is, Attract, engage and sell. And, Predictive marketing helps you out with all the three steps.  Let’s take a look at one of the best examples in the industry, Amazon.

Amazon has a very powerful AI engine that monitors all the users landing on their website. Once we have shown our interest towards a product, the engine starts interacting with us. If we bounce off the website without making the purchase or abandoning our cart, Amazon’s AI engine triggers a win back based conversion campaign. Later, we start getting targeted emails and advertisement about the same product, pushing us users to make the purchase. Thus, increasing the chances of completing the sales cycle.

Now let’s look at a few things that Predictive marketing can do and how it makes work easier for your marketing and sales team.

Things that Predictive Marketing is rapidly changing?

Predictive marketing and analytics

  • The Marketing rule of 3Rs – Marketing is all about providing the 3Rs, right information to the right user at the right time. If these 3Rs are pointed out with higher accuracy and precision, the chances of a user preferring your brand over your competition are higher. For example, if a message is customized and triggered based on the customer’s behavior, there is a higher chance of converting the customer. This, in turn, increases your brand value and visibility among competitors. And, in the end, the brand with better visibility will always lead when it comes to closing a sale or tying a user with their system.

  • Predictive Marketing cuts down capital burn rate – One of the flaws of our human nature is, we sometimes tend to work on our instincts and like to take these shot-in-the-dark approaches. This might lead to a lot of success but most of the time we end up wasting a lot of precious resources available to us. That’s not the case with AI and machine learning, as these technologies only take decisions and make amendments based on hard data. Therefore, decreasing the instances where you end burning capital or increasing the chances of garnering a low ROI on your investments towards marketing.

  • Predictive Marketing bridges the gap between Sales and Marketing teams  – Today a lot of brands face a similar issue, their marketing team and sales team have totally different views on common problems. The information that is gathered by AI, as said before, is based on hard data. The information gathered takes crucial data points into account like customer sales stage, their on-site behavior, last seen on website data, etc. Such a data set allows us to measure our efforts collectively and therefore both teams could work in sync based on things that worked and things that do not. Thus resulting in improved efficiency between the marketing and sales team efforts and helping them work towards a common goal, increased conversions.

  • Increased user engagement based on User’s situationOne of the best part of an AI engine is the part, that could it virtually extract any sort of data necessary. Set down the rules and let AI take over. It could map the content and communication based on the user’s situation/stage with a brand, like, Stage in the conversion funnel, industry-vertical, prospect’s role in the firm, stages of sales cycle, geographic location, behavior and engagement habits, prime-time channels and more.  

  • Improving Emotional Connect with readersEach person has their own approach and is often biased on how they approach a user’s based on their own emotional state. This results in an approach that becomes jarring in the long run. Whereas AI can make an effort based on every kind of interaction with a consumer, for instance, it can monitor if a user is facing a complex situation and recommend a solution to combat such situation. For example, if an AI engine looks at a user reading more about leadership skills, it could direct an approach where it serves the user more content about the very topic to win over the mindset of the user. This is one of the examples where the reader can emotionally connect with the brand and prefer it over its competitor.

  • Optimization on the goAI engines is the crux of predictive marketing. It is always analyzing and implementing optimization on the go. It enables you to spend less time on setting rules and targets for your marketing campaigns by being involved on its own with your existing infrastructure. For example, AI can concurrently make changes to your existing email campaigns by looking at the data points like CTOR rates, Open rates, user activity based on time, etc. Whereas if this task is to be handled by a user, it becomes tedious, as you’ll have to keep monitoring the data points over time and making manual amendments.


It is pretty evident that AI and predictive marketing is rapidly changing the landscape of marketing. Marketing has been around for ages and predictive marketing is the newest innovation in this space. We have a lot of case studies that argues the same for AI’s capabilities. It has helped us understand that there exists a gap between our marketing strategies. Now with the help of AI, we exactly know what has to be done and we have been arming our sales team with what they need to close deals. And what better than predictive marketing to bridge the gap between these two teams who have always be co-dependent on each other for their efforts.

Telling Better Digital Stories – Harvard Business Review’s Customer Engagement Story

Last week we released our first ever customer engagement deconstruction study on Spotify. We got a lot of readers and received tons of positive feedback on the study.

We are following it up with the addition of another brand to the series. So without further ado, let’s get started.

Today, we will take you through the customer journey of Harvard Business Review. HBR is one of the most authoritative publication when it comes business, management and entrepreneurial skills.

Why did we choose HBR for our deconstruction series?

  • HBR is regarded as one of the best publications in the Americas when it comes to management based articles. The publication is headed by a team from Harvard University.

  • It is regarded as one of the first management magazines that gave prominence to well known industrial terms today, like Globalization, strategic intent, information technology and more. HBR’s magazine circulation is over 100,000 copies a month in the US alone.

  • It’s even more staggering that their website, has a monthly viewership of 11 million. Out of these 11 million readers, they have a 40% returning user count.  

  • HBR’s tech stack is highly discreet. We are astonished at how they were able to garner high traffic and deploy a good customer engagement strategy.

  • They have one of the best on-boarding experiences when it comes to media houses and publication groups and hence it was a no-brainer to pick up Harvard Business Review for the next contender in our customer engagement deconstruction.

Glimpse of what you’ll find in the full deconstruction

  • What makes HBR’s on-boarding experience intuitive for its readers?

  • How does HBR tie users with their sales funnel?

  • How does HBR interact with their readers on a regular basis?

  • How does HBR push a user towards subscribing to their complete suite of publications?

  • Where does HBR falter with it’s customer engagement strategy and how it can correct these instances.


ai shopping

How Artificial Intelligence is Shaping Up Modern eCommerce

Last fall, I was reading about how the battle is heating up for the best Artificial intelligence based home assistant. One thing that took me by surprise, was Amazon’s home assistant, Alexa.

Alexa is one of the few AI based assistants for modern shopping that can shop on your behalf. It lives in 2 Amazon products, namely the Amazon Echo and the Amazon Dot.

Gone are the days when you have to rush to your nearest grocery store because you ran out of milk for breakfast for next morning. Now, it’s as simple as saying, “Alexa, order a crate of milk and get it delivered tomorrow.”

Under the hood, Alexa will use Amazon and make an order on your behalf and it will be at your home the next morning.

Isn’t this fascinating, that Alexa only needs to verify your voice pattern to make an order on your behalf. Truly, the future is here.

This is just an example of how Artificial intelligence for eCommerce industry is completely disrupting traditional customer engagement techniques. Sorry, not just engagement techniques, but also the complete customer lifecycle.

Today, AI involvement begins from outreach, advertising, marketing and ends with reducing cart abandonment, churn rates and improving customer retention rates.

With a 68% rate of cart abandonment and average user purchase cycle of 2 months, I am hard-pressed to find an eCommerce website that’s not getting restless to increase it’s customer engagement rates and drive higher sales.

So let’s show you a few ways in which artificial intelligence (AI) will change the modern shopping experience in the eCommerce landscape.


Ways in Which Artificial intelligence is Changing eCommerce

Product and User Personalization

Personalization is nothing new to eCommerce. If you have used Amazon and other eCommerce companies rather frequently, you know what I am talking about.

But, with the advances in AI and machine learning technologies, such deep personalization has finally found its way into the fast growing eCommerce space.

Many eCommerce companies use collaborative and rule-based targeting and filters to provide user personalization.

The problem with such technologies are, limitations to one channel and ever changing user preferences. These techniques can gather customer details only from a certain channel, for example, an eCommerce brand, might only be able to gather user data based on what activities users perform while they are on the website.

Whereas AI based personalization for eCommerce takes the multi-channel approach. An AI engine, such as Boomtrain, sits on top of the multiple customer touch points to analyze how users are interacting with the brand. Be it a mobile application, website, or email, the AI engine is monitoring all the devices and channels to create a unified customer view. This unified customer view helps in delivering a seamless customer experience across all platforms.

So the next time when you check out a study table on the website, you might receive a push notification on your phone, informing you about a flash sale for study tables. And, now you can directly make the purchase on the phone, saving a lot of steps for both parties.


AI is Bridging the Gap Between Personalization and Privacy

Whenever it comes to personalization, there is always a trade off with concerns to user privacy. There has been a strong display towards the importance of user privacy in recent years. And, brands are striving to take transparency, security and honesty to a whole new level. But to do that, they can’t forsake user personalization, as it is the crux of any successful e-Commerce venture.

To combat this problem, large brands are taking advantage of AI. It’s a known trend nowadays, that users are ready to share their details, if they are getting something truly valuable in return.

Think Google Now. If given access to your account, it can sync your calendar, emails and search habits. Now, every morning you are greeted with a small briefing of what’s on your plate, which orders are arriving home today and if you’re gonna be late to office today due to unusually high traffic.

This is the same magical approach that Amazon took with Alexa, they offered a modern shopping assistant that put the user’s day to day routine first and helped them with daily house chores. Later on, they added the intelligence bit in Alexa that converses with the users and buys things on their behalf. The end result, 82% Americans know about Amazon Alexa based products, Echo and Dot. Moreover, out of the 82%, 20% of the people are using it on a day to day basis.

At the end of the day, AI enables these brands to provide magical experiences throughout a user’s day, and for such an experience, any user is happy to share their personal details. There can’t be a better example, of how AI is bridging the gap between user personalization and privacy.


AI is Key to a Connected Shopping Experience

With the world moving towards a more connected era, as we speak, it’s hard not to add AI into the mix.

Once AI is integrated with connected devices (like IoT devices like Amazon Dash, nest thermostat and Home assistants), the consumer world will start moving towards a completely different direction.

The next gen of IoT devices and smart devices, will learn from user behaviour, habits and pick their lifestyle patterns to serve a better overall experience. Devices will strangle data from everywhere to predict the right opportunities for transactions.

Using innovations in the mobile first based world, these engines will pick data from device sensors rather than today’s app ecosystem. Chatbots and NLP will start picking up human emotions, habits and know whether you are happy, mellow or charged up, to recommend products in a smarter, non-intrusive manner.



At the end of the day, a retailer has to accept that Artificial intelligence for eCommerce is accessible to everyone. It’s upto us if we want to provide a better customer experience. If an ecommerce business has to thrive in such a cut-throat competition, then he or she has to make the shopping experience more personal.


Thanks for your interest in Zeta. To see a demo please complete the form.

Thank you!

Your request has been sent. We will be in touch with you shortly.

Back To Homepage