Use AI techniques to personalize and optimize your communications to reduce subscriber churn.

Stop Subscriber Churn in Its Tracks with These 4 AI-Powered Campaigns

Churn is a natural part of every business. However, no organization likes their users to churn. So, what should you do (especially after you’ve been trying tactic after tactic to no avail)? Use AI techniques to personalize and optimize your communications.

According to a recent “State of Marketing” report, there’s a 50% chance that customers will switch brands if brands don’t anticipate their needs. The goal of marketers is to build strategies and campaigns that will (1) keep active customers engaged, (2) re-engage “at-risk” customers, and (3) bring churned customers back into the fold.

So, what can growth marketers at subscription companies do to reduce churn?

1. Intervene before it’s too late!

“Newsletters are stupid,” said by Alex Shultz, Facebook’s VP of Growth. He believed that most companies today are sending marketing emails that are just spam. Why? Because that same newsletter will be sent to everyone in their email list — to someone who has been enjoying your product for three years and to someone who has just signed up to your site yesterday. No distinction at all, no personalization, no understanding of who that individual person is. Schultz said that companies should be focusing on notifications and triggers-based emails, SMS, and push notifications in reaching out to their customers.

Growth marketers will keep their customers engaged when they provide delightful, relevant content while personalizing it based on their customer’s expressed and perceived preferences. One way to do that is by relying on 1:1 marketing, with no two users receiving the same message at the same time.

IN SHORT: Keep customers interested in your products or services by sending personalized offers or incentives using targeted email or push notifications. (Hint: NEVER rely on a single channel to drive repeat engagement.)

2. Strike while the iron is hot. Quick, send them that enticing incentive!

According to a Pegasystems survey on customer engagement, 56% of top-performing companies are investing in AI to personalize and continuously learn from customer interactions. Today’s AI-powered productivity tools make it possible to anticipate customer needs which allow marketers to tailor highly-personalized campaigns to keep customers engaged.

One example is by using trigger-based email marketing, an example of a customer-centric, behaviour-based marketing approach. Recent Forrester Research showed that trigger-based email marketing campaigns can generate 4x more revenue and 18x greater profits. Subscription upsells are one way of retaining active customers by sending them personalized messages containing information on products they might be interested in. Offering incentives to customers to switch to the next subscription tier can also help in convincing them to upgrade their subscription.

IN SHORT: AI can easily help growth marketers gauge their customers’ willingness to accept an upsell.

3. Out of sight, out of mind? Go remind them.

Abandoned carts may mean that the customer has forgotten he added an item to his cart or he really didn’t want the item.

Growth marketers can still turn abandoned carts into revenue. Remember, these customers have already expressed an interest in the products and are engaged with the brand, all they need is a little nudge to complete their purchase.

With the help of AI, growth marketers can send targeted recommendations that are similar to the one that the customer already added to his cart. These recommendations may include product information on new arrivals, price drops on items with which the customer has engaged, or “back-in-stock” notifications. Even if the customer didn’t really want the abandoned item in his cart, his interest may be piqued by the new recommendations. These triggers are especially good for mobile push notifications since they are “newsworthy”.

4. Win them back.

Win-back campaigns involve the re-activation of churned or “about-to-churn” customers. Winning back churned customers so they can be active again is never an easy task. Move back from using traditional marketing campaigns which lack sufficient real-time data and insight.

AI helps in analyzing vast volumes of customer data especially in identifying the characteristics of high-value past customers. But for AI tools to work effectively in your win-back campaign, you need to feed it with the right data and algorithms.


Growth Marketers Guide CoverA well-designed AI system can streamline an organization’s complex processes. Leveraging marketing AI can provide a significant, tangible lift to an organization’s customer engagement efforts. You can learn more about how Growth Marketing drives increased user engagement by downloading our whitepaper.

 


 

5 Predictions on How AI Will Reshape Marketing

5 Predictions on How AI Will Reshape Marketing

According to the Tata Consultancy research cited in the Harvard Business Review, companies implement AI primarily to increase the effectiveness of information technology, marketing, financial trading, and customer service. Though AI promises many things in the field of Marketing, today’s deployments are far more pedestrian and focused on anticipating customer purchases or improving the efficiency of various marketing activities like monitoring social media.

However, AI’s impact in marketing over the coming years will be wide-ranging and far more significant than it is today. Here are the 5 key changes that we see taking place.

#1 Customer experience becomes more personal, less robotic

AI will make the Customer Experience more personal, and paradoxically less robotic.

This may sound counterintuitive, but customers are quite comfortable with bots. Research by Pega Systems shows that 55% of all customers surveyed were comfortable with a business using AI to interact with them. 19% were uncomfortable and 26% were neutral. Many respondents felt that bots can help improve customer service particularly in retail, healthcare, and telecommunications. Anyone who has had to navigate through a phone tree when calling their local phone provider will empathize with this sentiment.

However, customers would rather not encounter bots that cannot give them a contextual experience. Aftersales support, for example, is an area where customers would rather deal with a human being. They want real conversations.

Recent innovations in AI are aimed at addressing such gaps. The rapid innovation in technologies like Siri and Alexa are harbingers of things to come.

#2 From driver-assist to self-driving marketing campaigns

Just as AI technology in cars is moving from driver-assist to self-driving cars, AI in marketing will evolve from improving tasks like segmentation to helping orchestrate an entire campaign.

Most AI technologies for Marketing are designed to enable marketers to streamline manual and repetitive tasks. In the future, this will change. We will see AI playing an important role in orchestrating entire campaigns. The campaign builder technologies of today will be replaced by AI-powered campaign builders that will use data to personalize messages and offers, choose the best channel mix and the best times to execute those campaigns.

Forward-thinking marketers are already taking advantage of AI to connect customer experience from the top of the funnel down to the bottom. In our recent survey, for example, marketers revealed that they are using AI to overcome their top challenges in orchestrating customer experience at the top of the funnel. More than 40% of surveyed marketers are using AI for audience expansion, while 39% are using it for audience targeting.

#3 More time on strategy, less on manual operations

AI will give marketers more time to spend on strategy and less on manual operations.

Collaborative filtering and offer optimization are just some of the many aspects of marketing that AI can optimize. Any problem that involves the analysis of large amounts of data to see patterns, AI is a good tool to tackle that problem.

This leaves marketers with the not only the time but also convenient access to results from the analysis of large amounts of data. Marketers should interpret these results and factor them into their future strategy.

#4 More creative story-telling with expanded reach

Marketers will once again become creative storytellers, with AI helping them scale their storytelling to millions of users.

According to MarTech Advisor, 95% of content has no impact on engagement and is largely wasted. Marketers should combine the “old school” skill of storytelling with new AI-powered techniques like sentiment analysis to both create and deploy the most engaging content that people will consume.

AI can also be applied to distribute this content in a highly personalized manner based on the preferences and content consumption behavior of the recipient.

#5 Thrive or die based on the use of AI

Brands will either thrive or die based on how well they adopt and use AI in marketing.

Recent research by Deloitte shows that AI has sparked a renaissance in modern retail. An industry that was not so long ago in a “retail apocalypse” has bounced back and grown faster than overall GDP every year since 2009. Brand leaders have invested in AI to better personalize the retail experience for their customers.

Most industries will face a similar challenge and will need to figure out how to adopt AI or be at a competitive disadvantage. Data access and activation will be a key determinant of success. Our research shows that businesses that use more than 75% of their customer data in their marketing and 1.4 times more likely to exceed revenue goals than those who don’t.


Interested in learning more? Download the full report here.

Download Blueshift's report on the state of AI, Marketing, and Customer Data - lots of marketing stats

From Acquisition to Retention: Top AI Techniques for Today’s Marketing Leaders

Top AI Techniques for Today’s Marketing Leaders (From Acquisition to Retention)

In our recent survey, more than 60% of marketers revealed that they are planning to increase their usage of AI going forward — proof that more and more marketers are realizing AI’s potential to enable greater marketing success.

However, very few marketers are taking advantage of advanced AI capabilities that can not only enable them to do more than just acquire new prospects but also convert them into loyal and more valuable customers.

Incorporating AI into All Aspects of Marketing

How marketers integrate AI into their strategies can determine their overall marketing success. They should consider AI as an integral component of their entire marketing game plan instead of treating it as a mere tool to bolt on when needed. Even before they consider specific AI techniques to implement, they should first look at their strategy for using AI by asking the following questions:

  • How can AI help us better find and engage new prospects?
  • How can AI enable us to engage customers?
  • How can AI turn our existing customers into more valuable customers?

Here are our recommendations on using AI for these three key aspects of marketing.

1. New Prospect Acquisition

Acquiring new prospects can be a very difficult endeavor no matter the size of the business. Increasing [brand] visibility and generating quality leads are two of the biggest marketing challenges businesses face.

Traditionally, marketers employ highly manual, time-consuming, and blunt approaches to win new customers. To get a decent list of prospects, for example, they use demographic data such as industry and job title to purchase lists, get referrals, and harvest their website visitors. After pulling this data into their systems, they then have to start engaging with these prospects to further narrow down this list to pinpoint and target the right customers.

AI can give marketers the capability to obtain relevant and useful information quickly using behavioral data. In fact, almost half of surveyed marketers (43%) use AI primarily to acquire new prospects using audience expansion techniques such as the following:

Look-alike audience expansion.
AI can be applied to the demographics, preferences and behavior of your existing customers to develop predictive scores of your best customers. You can then use this set as a seed list on a large network like Facebook to acquire similar audiences there.

Targeting and re-targeting users.
Almost 40% of surveyed marketers use AI techniques to better target audiences on large networks such as Facebook and Google. AI can be applied to prospect behavior to develop predictive scores that can then be used to re-target prospects with specific offers on the large networks. Similar techniques can be used to re-activate existing customers and prevent them from churning.

Percentage of marketers using AI in their marketing today and how they are using it

Tip: While these AI-powered techniques are helpful, marketers should put the same or even more emphasis on the other stages of the Buyer Journey. Which brings us to the next point.

2. Delivering Personalized Customer Engagement

One of the biggest challenges for marketers today is around delivering personal and content-rich experiences at every touchpoint in the customer journey. AI has a lot to offer today to enable marketers to intelligently and insightfully engage their customers on a highly targeted basis, with recommendations and micro-segmentation.

Marketing Stats - Percentage of Marketers using advanced AI in thier marketing

Using AI-enabled technologies like collaborative filtering, for example, marketers can predict customers’ interests based on the preferences and behaviors of others similar to them. But despite the proven capabilities of collaborative filtering, only 6% of marketers are using it. Similarly, only 16% of marketers are using predictive techniques to learn user preferences or affinities for various products and services based on their behavior and to segment them using these affinities.

Tip: To win today’s customers, marketers should provide them with highly personalized content. To be able to do so, they should apply advanced AI technologies like collaborative filtering and predictive affinities to the engagement phase of the Buyer Journey.

3. Activating Your Customer Data to Retain More Customers

According to Harvard Business Review, “acquiring a new customer is anywhere from 5 to 25 times more expensive than retaining an existing one.” So if marketers want to save on costs while keeping their sales up, they should focus on creating more value out of their existing customers. To do so, they should harness both historical and real-time customer data—but herein lies the problem.

The majority of marketers (54%) are using less than half of the customer data they have. As a result, they are not taking advantage of the potential in this data to help them improve customer engagement and increase share-of-wallet. The study results also show that those marketers who have been able to get advanced access to their data are 2.4 to 2.8 times more likely to deployed AI techniques like predictive affinities and collaborative filtering.

Marketing Stats - Markters with greater access to customer data are up to 3xs more likely to use advanced AI in their marketing

Tip: To make the most of their AI investments and deploy leading-edge AI use cases, marketers (particularly non-technical marketers) should have advanced access to data and should activate more customer data.


Data Fuels AI-Powered Marketing

Marketers will only unlock the potential of AI if they can first get advanced access to their data and then apply AI techniques to improve engagement all through their buyers’ journey.
Download Blueshift's report on the state of AI, Marketing, and Customer Data - lots of marketing stats

Get the full report here

over 75% of businesses have seen an increase in revenue tied to their use of AI in their marketing.

Blueshift featured on ZDNet: AI, Marketing, Revenue, and GDPR


The full article, “Survey shows that three-quarters of businesses improve revenue with AI”, can be found here on ZDNet:
https://www.zdnet.com/article/survey-shows-that-three-quarters-of-businesses-improve-revenue-with-ai/


AI-Powered marketing generates more revenue

In this coverage by Eileen Brown (@eileenb) from @ZDNet of our latest research report titled “Activating Customer Data for AI-Powered Marketing” (Download it here), over 75% of businesses have seen an increase in revenue tied to their use of AI in their marketing. In short, brands who aren’t using AI in their marketing are actually leaving money on the table.

Percentage of respondents that exceed revenue goals

Respondents that exceeded revenue goals

The right data is your first-party data

“The ‘right data’ to use is first-party data, gathered from their own customers acquired with the customer’s consent and trust.”

These leading brands have already come to realize that “the ‘right data’ to use is first-party data, gathered from their own customers acquired with the customer’s consent and trust.” They have embraced the seismic shift towards first party data, the explicit consent needed, and the ability to actually collect and using relevant data.

Customer data, GDPR, and AI

As anyone who handles customer data knows, GDPR is here, and companies will be held accountable for maintaining compliance. Having a strong customer data strategy not only helps with GDPR compliance, but will be the key to using AI in your marketing.

The Age of AI-Powered marketing is already here.


Read the full article:
https://www.zdnet.com/article/survey-shows-that-three-quarters-of-businesses-improve-revenue-with-ai/


Download the full report here:
Download Blueshift's report on the state of AI, Marketing, and Customer Data - lots of marketing stats

3 Crucial Elements Marketers Must Consider When Implementing AI Strategy, Organization, and Technology

3 Crucial Elements Marketers Must Consider When Implementing AI

Watch this rare webinar with Analysts from Forrester Research and VentureBeat hosted by Blueshift about getting the most out of your customer data with AI
This blog is the second installment of a 2-part series on how artificial intelligence (AI) can help marketers put their customer data to work discussed in a rare joint webinar with Forrester Research and VentureBeat.

In the first part of this series, we explained how marketers can win their customers’ moments if they fully harness all their customer data — which is easier said than done since most marketers admit to only using 10% of their customer data.

“50% of Marketers State Data Unification as their Greatest Challenge to making the most of their customer data.”

Having existing data silos is one of the main reasons why marketers cannot fully leverage all their customer data. Customer data often sits in disparate and geographically dispersed systems. “Marrying” all this data can be extremely difficult. At a recent Forrester webinar, half of polled marketers said that data unification is their greatest challenge when they want to make the most of their customer data.

half of polled marketers said that data unification is their greatest challenge when they want to make the most of their customer data.

Armed with artificial intelligence (AI), however, marketers can successfully break data silos and effectively generate and orchestrate customer insights and actionable intelligence quickly.

But hold on…don’t end up like countless other marketers who have battle scars from trying to bring AI into their organization. I have personally spoken with dozens of marketers and product leads who have “battle scars” when trying to implement AI into their marketing stack in the past. Before you implement AI, first consider these three crucial dimensions (Strategy, Process, Technology) in order to make the most of your AI investments and avoid costly mistakes.

 

Strategy

It’s fairly straight-forward… don’t jump to a tool before you know what you want. Start with a strategy for fully maximizing the potential of AI. Determine what the marketing team –– or, better yet, the organization as a whole (more about this in the next section) –– is trying to accomplish and how, using AI, it can deliver business results. A key question to ask  here is, “How will AI help me scale my results?”

The ultimate goal should be to become customer-led and data-driven because customer experience is the new battlefield. According to Forrester, many organizations aspire to become customer-centric and data-driven (70%), yet few can turn data into profitable actions (29%).

The ultimate goal should be to become customer-led and data-driven because customer experience is the new battlefield. According to Forrester, many organizations aspire to become customer-centric and data-driven (70%), yet few can turn data into profitable actions (29%). AI can bridge this gap and enable marketers to become customer-led, insights-driven, fast, and connected. AI will give them greater visibility into customer behavior, make appropriate and contextual offers, and deliver personalized and unified experiences across all channels. And based on the insights generated, AI empowers marketers to further optimize their offerings and overall strategy.

TIP 1: Think about how you will measure the success of your efforts (KPIs).

TIP 2: Your strategy must include a “Crawl, Walk, Run” approach when rolling out AI that has clear KPIs at each step.

 

Organization

AI adoption impacts not just marketing processes but the entire business. Determine the organizational gaps that must be closed and address the factors and misconceptions that may hinder the organization from implementing AI.

It's about people and processes... Determine the organizational gaps that must be closed and address the factors and misconceptions that may hinder the organization from implementing AI.

TIP 3: Draw out the customer journey (physically draw it out) and include all steps in the process beyond just what happens in marketing. Understand where the bottlenecks are and address the key pieces that you wish to have AI help you solve. (this could be data unification, post-sale tracking, behavior tracking, multi-channel engagement, customer experience)

To evaluate the organization’s readiness to adopt AI, look at its people and processes:


People: Lack of AI skills is the primary reason why companies hesitate to implement AI. In fact, only one-third of surveyed marketers said that they have the right skills and capabilities to adopt AI. It is also a challenge to recruit people with the right blend of business and technology skills who can easily adapt to a customer-centric culture.

Process: Marketers should study how AI will impact existing processes. For example, how will AI allow for greater transparency? How will it enable siloed departments to obtain better visibility into what others are doing? How will it help me scale what I am doing?


Additionally, it is important to ensure that everyone in the organization has the right understanding of AI. For instance, they should be aware that AI alone cannot externalize knowledge. It requires both people and technology. Which brings us to the next point.

 

Technology

AI is not merely a plug-and-play component in your marketing stack. Look at all the components in your marketing stack to understand how AI will interact with your data, your team, and your campaign execution.

AI is not merely a plug-and-play component in your marketing stack. Marketers should know how to deploy it successfully and set the right controls and monitoring systems. Should they turn on a model and let it generate results for people to review? Or, should they embed it into an application that automates processes such as personalizing content and optimizing email campaigns? (Ideally, you would have a system that would do both. Automation is key to getting the most out of AI, otherwise, you are stuck with insights and no action…and who wants that in this market?) How will they put the right controls and monitoring to ensure that models are working properly and delivering results?

TIP 4: Don’t jump right in to look for technology partners UNTIL you have a clear strategy and understanding of your organizations real needs.

Most of the “battle scars” I referred to earlier stemmed from prematurely jumping into a new platform without proper internal preparation.

AI shouldn’t be something you fight with. The technology must be something you work with to really scale your efforts. Picking the right technology isn’t easy, but there is plenty of help…

 


Get expert help

AI gives marketers profound competitive advantages. For one, it enables predictive scoring to determine important indicators such as purchase intent, customer engagement, customer retention, and customer churn. Using cutting-edge tools like Blueshift, marketers can generate and manage results such as these in an intuitive dashboard, putting insights at their fingertips so they can quickly make profitable frontline actions.

Enabling AI-powered marketing can result in an optimized customer journey, greater efficiency, smarter decisions, increased speed, and continuous performance improvement. Implementing AI, however, can be a complex initiative. Don’t rush it. Commit to it and by looking at strategy, organization, and technology before implementing AI, marketers can ensure they get the most out of their investment and avoid being burned by AI.

Watch this rare webinar with Analysts from Forrester Research and VentureBeat hosted by Blueshift about getting the most out of your customer data with AI


Further Reading and Referenced Sources:

  1. Forrester Research, VentureBeat, and Blueshift discuss AI, customer data, and cross-channel marketing in this webinar: AI-Powered Marketing: Put Your Customer Data to Work.
  2. Two-thirds of businesses do not have skills to adopt AI” via ComputerWeekly.com. Despite the growth of artificial intelligence (AI), only a third of businesses say they have the necessary skills to adopt the technology.
  3. Gartner Report: “Customer Experience Is the New Competitive Battlefield” that discusses the evolving strategy of building better digital and offline customer experiences to better define your brand.

 

Making sense of AI and customer data and getting executive buy in

Making Sense of AI and Customer Data and Getting Executive Buy-In

“Brands who fail to leverage more of their customer data also fail to retain relevance and loyalty with their customers.”

Forrester, VentureBeat, and Blueshift joined together in a webinar titled “AI-Powered Marketing: Put Your Customer Data to Work” to discuss how brands can make the most of all their customer data across all marketing channels. The crux of the conversation revolved around using Artificial Intelligence to make the most of your customer data and the inherent problems and myths marketers today face when trying to cut through the hype and really make AI work for them.

webinar ai powered marketing and put your customer data to work with blueshift featuring forrester and venturebeat

In this article, I will address three hotly discussed questions that our viewers asked on the topic of AI and Customer Data. For AI, we’ve moved from a state of novelty to a state of necessity, and these questions revolve around how to get Artificial Intelligence into an organization and how long should it take. So you don’t have to read all of it, I summarized the responses from analysts at Forrester, VentureBeat, and our own co-founders.

What is the best way to “sell” the need for an AI strategy or investing in AI to the C-level?
TL;DR: To get the most use of your customer data, you need AI (there’s just too much of it) — and getting buy-in for AI is a complex process, but when approached with a solid measure for success and a “crawl, walk, run” approach, it gets very doable.

How do you differentiate Machine Learning and AI (deep learning, etc.)? A lot of content presented today has more to do with machine learning than AI, don’t you think?
TL;DR: they’re not exclusive topics…but it’s time to cut through the AI-hype-cycle, and understand what AI and Machine Learning really are and how they help you.

Once you sign the dotted line for an AI platform, how long would one allocate toward implementation and planning and executing campaigns?
TL;DR: Implementing an AI platform gets better with time and shouldn’t be a “one-click solution”, however you can start seeing results in weeks. It takes partners who will guide you through the process and help you plan/organize/execute on the data and systems you have.

Full, more thought provoking answers below…

And if you would like to watch the full webinar, you can check it out here.


What is the best way to “sell” the need for an AI strategy or investing in AI to the C-level?

Manyam Mallela, Chief AI Officer at Blueshift
Crawl, walk, run: Start with a specific use case to show results and build from there.
“The best way to get executive buy-in for newer artificial intelligence technology platforms is to show how AI improves immediate KPIs. Start by targeting and building personalization in one or two campaigns using segment-of-1 marketing, and do this without having to hire more data analysts/engineers/scientists,” says Manyam Mallela “Once a specific KPI improves, it’s easier to make the case for a wider roll out of AI in the organization.”

 

Rusty Warner, Principal Analyst at Forrester Research
Focus on how it will improve the customer experience in a specific way and test it.
“There are two levels to selling the need for AI into the C-level. First, start with the benefits AI will bring to the organization as a whole. Focus on what it will do to improve the customer experience (or, digital experience), then look for a specific use case so you can prove the value of the technology.” says Rusty Warner “Second, many of the barriers have been lowering as executives have begun to understand more what it takes to bring in AI and the the value it can surface.”

Before you touch your marketing platforms, understand what your KPIs are (Marketing 101) – what are you trying to accomplish and how will you measure this. Have a plan! In addition, marketers must be able to easily activate customer data quickly in their campaigns across all channels. Selecting a “single-point solution” that only solves one issue backs you into the current situation most marketers face today of a “frankenstack” of band-aided technologies with overlap in functionality and disconnection between their data sets.

 


How do you differentiate Machine Learning and AI (deep learning, etc.)? A lot of content presented today has more to do with machine learning than AI, don’t you think?

Vijay Chittoor, CEO of Blueshift
For marketers, it’s the difference between manual, “driver assisted” automation, and truly autonomous “self-driving” automation
“When looking at the difference in Artificial Intelligence and Machine Learning, think of the evolution of “smart cars”/driverless cars.” says Vijay Chittoor “Machine learning would be similar to “driver-assisted” cars where the machine learning is in the passenger seat. It’s helping in the driving but not actually doing any of the driving for you. For instance when backing up, you might get an alert of nearby objects from machine learning – you, as the diver, must still make the decision of what to do. Contrary to “driver assist” (machine learning), a “self-driving” car would process all the incoming data, assess the situation, and decide on the the best action to take…autonomously. This is what Artificial Intelligence is — the “self-driving car” that ingests, analyzes, and takes action on its own using predictive scoring/models that would have the best outcome.”

 

Stewart Rogers, Analyst of VentureBeat
It’s the difference between finding and applying a pattern, or, taking a pattern and actually improving upon it
“Machine learning is finding patterns in the data, and by finding patterns in the data, we can apply that pattern to other data. This is useful for predictive analytics, for example.” says Stewart Rogers “With Artificial Intelligence (AI), on the other hand, we have a system that takes the pattern and then makes the best version of it order to optimize or improve upon the data so you get a better result.”

Most legacy marketing platforms use a form of marketing automation that’s more driver-assisted where it’s a simple triggered response to an event being fired or an action being taken, like a yes/no logic in a workflow or a simple “if/then” logic that must be manually built for every outcome by a marketer. There’s no “thinking” involved, no decisions based on continuous learning. Sure, it’s automated, but it’s time consuming, very manual, full of list pulls and exports, and has no real intelligence behind once it is executed. You’re just applying a pattern to a problem and letting it run.

New platforms use the “self-driving” model, where artificial intelligence runs the show — essentially making the marketer smarter and able to really scale their efforts by making informed decisions at remarkable scale across channels. Modern technologies continuously learn and optimize for better performance.

 


Once you sign the dotted line for an AI platform, how long would one allocate toward implementation and planning and executing campaigns?

Manyam Mallela, Chief AI Officer at Blueshift

It’s not something you get by just pushing a button, however you can see value and results in weeks, not months
“We have seen over 90 percent of our clients go live with high impact campaigns in less than 4 weeks with a continuous rollout after that based on their priorities.” Manyam Mallela, Chief AI Officer at Blueshift “Blueshift’s unique architecture allows faster on boarding by not having rigid data schemas or limits on size and types of data.”

Activating and getting value out of AI doesn’t come from just a push of a button… But, at the same time, seeing value from AI shouldn’t be a year-long effort. Modern platforms built from AI help marketing and product departments initiate complex campaigns with ever-changing data quickly. And most of all, these campaigns get better. Older, bolt-on solutions introduce lag at every step, and anyone who has the battle-scars from trying to bolt AI onto their “Frankenstack” knows the struggle and countless months spent just trying to get a single campaign out.

The more an organization thinks intelligently about their customer data (from how it’s structured, to where it’s stored, and how it is used), the better prepared they are to truly put their customer data to work using AI. No need to fret though, even if your customer data isn’t all housed in a massive data lake or in one system, there are platforms that will help you unify your data, create a true Single Customer View, and then give marketers the autonomy to actually run campaigns quickly and with the most up to date data.


webinar ai powered marketing and put your customer data to work with blueshift featuring forrester and venturebeat

CIO to CMO

CIO to CMO: Your AI is Only as Good as Your Data

“Artificial intelligence is only as smart as the data it receives, which means that the biggest gains you can make in quality will come from improving data input.” – Vijay Chittoor, CEO, Blueshift

 


This is an excerpt from an article that originally appeared on CIO.com.

In a recent article on CIO.com, our CEO, Vijay Chittoor, provided insights into how today’s CIOs will empower CMOs through rich data to power new AI designed for marketing. Today’s CMOs and marketing leaders are being pushed further and further into a “technologist” role, often sacrificing the time and resources needed to create powerful messaging and overall strategy.

As the article illustrates, marketers are bogged down, there’s a mountain of data, and a need to efficiently analyze and take action on the data. AI poses the solution for marketers to get out of “tinkering” and get into actually producing more from their data. It’s not a matter of not having access to data, it’s knowing how to structure and USE the data.

“The data required for AI to do its magic already exists. Our online behavior is constantly being monitored. The data traces we leave behind are compiled and analyzed by machine learning programs to find patterns. For example, it may find that people who search for orange sweaters in October are also highly likely to want to buy a pumpkin flavored coffee drink, and are most likely to make that purchase if they are served with a mobile ad at 8:00am, before they head to work.

The key, of course, is data. The more comprehensive the data, the more precise and effective a campaign can become.”

Read the full article here.

Friday Five

Friday Five – #AI struggles, @Amazon fumbles, #CustomerExperience mumbles, and a ray of AI light

Welcome to our inaugural Friday Five. Each week, our goal is to give you a run-down on 5 of the top stories and themes circulating on the topic of AI in Marketing. Think of this as that TL;DR of those stories you meant to read or might have missed.

Sit back, enjoy that cup of coffee (or tea, I’ve just discovered the wonder of Pu-erh tea), and feel free to reach out to me on LinkedIn, or via email if you’d like to chat about marketing, AI, CX, or with a hot topic you found.

Without further ado…


[TOPIC] A bunch of Amazon customers were told about a purchase on their non-existent baby registries


Yep, I got this email too: “A gift is on it’s way”
(No, I don’t have a baby, nor am I expecting… I do love Lego though…)

Normally, getting a notification that people are celebrating your new arrival and buying from your baby registry is a great thing! But not if you (1) don’t have a baby registry or (2) you don’t even have a baby.

Take this as a cautionary tale to make sure you have a strong handle on the integrity of your data and have a solid QA policy in place for your marketing sends. This “technical glitch”, as Amazon called it, shows that even large, well-run operations can still have a bump in the road.

The best Tweet I found on Amazon’s little “snafu”:

 



[ARTICLE] How AI Is Transforming the Retail Experience


(read the story)

“Awash in shopper data, retailers can also use artificial intelligence to sift through that data to provide actionable insights that allow them to better personalize the shopping experience.”

Can I get a Hallelujah!

In the article, Becky Lawlor (Twitter: @lawlor_becky) wrote about 3 key areas where smart retailers have begun transforming their approach to customer engagement with AI. In a nutshell, it all comes down to helping customers find what they want (think virtual shopping assistant/concierge), personalizing the shopping experience (from online to in-store and everywhere in between), and keeping the retail brand cutting-edge (think apps and new in-store experiences).

In my opinion, the SMARTEST retailers are focusing on building better customer experiences by creating a truly holistic view of their customer (both online and off).

Little Tip: Data alone will not be a differentiator (as so many articles are proclaiming), it’s what you DO with that data to engage with each customer that will differentiate you.

 



[ARTICLE] Extreme personalization is the new personalization


(read the story)

On the same theme as retail: Modern commerce brands are changing the game and marketers need artificial intelligence to compete. This article, by Brian Solis (Twitter: @briansolis), dives into some overwhelming stats that reveal what many of us in marketing already know.

Read this excerpt and be scared… brands are STILL struggling with personalization and a true single view of their customers:

“…only 14% of companies rank themselves as “strong” in achieving a single view of the customer, and less than 10% of top tier retail brands say they’re highly effective at personalization.”

A few key points from the article:

— We have too much data (or more importantly, data without a clear understanding of just what data we truly have)

— Lack of a single view of the customer (caused by too much data on too many systems because we have built “frankenstacks” of technology that silos the data [I feel like data silos were something that we were supposed to have solved years ago!!]) It’s not easy, trust us, it’s what we do here at Blueshift!

It’s not about removing the gut/guesswork, in-so-much as it’s about systematizing the way we test and measure our hypothesis with diligent A/B testing and powerful analysis performed with machine learning and AI.

Whatever you call it (Extreme Personalization sounds like a new Mountain Dew flavor), marketers brands must transform the way they engage with their customers. It takes an organizational shift, not just a goal for the marketing department.



[ARTICLE] The Impact of AI on Modern Marketing: 50 Categories Ranked, 70 Experts Sound Off


(read the story)

If you love stats, lots of supporting articles, and executives giving real opinions, then this is a great read for you. The article starts with this: (don’t dismiss the article on this over-used statement…)

“The modern marketer has a single-most, overarching and critical objective: to deliver the right message at the right time to the right audience, efficiently.”

I’m sure we have all heard the “right person, right content, right time” mantra… again and again and again. Yet, so many marketers struggle with it… and the answer, simply, is using AI to make a more frictionless customer experience. (period)

“the future of AI promises marketers an opportunity to connect with customers, in a personal way, with speed and precision.”

In the end, the results are about converting visitors to loyal customers and generate lots of revenue. (it’s not rocket science… but it does help to have a smart data scientist and a solid AI engagement platform.)

It’s a long read, but SOOOoo worth it. Thank you for organizing it into one place, Lana Moore (Twitter: @MarTechExec) Think of it as a TL;DR of hundreds of articles into one article. If you’re a stat and graph junkie like me, here’s one that should whet your appetite.

(check out the rest of the article!)

 



[ARTICLE] AI-Powered Live Personalization on Websites, Email, & Mobile Apps


(read the story)

I wanted to draw your attention to a big announcement we at Blueshift just dropped in the media this week:

Blueshift’s AI is Now Available for Live Personalization on Websites & Mobile Apps

Along with previously announced capabilities for marketing applications like Email, Mobile Push notifications and SMS, the new release enables multiple marketing & product teams to operate on a unified customer view, driving AI Powered customer journeys across every channel.

The new offering extends Blueshift’s core capabilities around segmentation, recommendations & customer journey orchestration to Live Personalization in the following ways:

— Segment customers using AI

— Recommend 1:1 Content powered by AI

— Deploy, measure & A-B test rapidly

 

Read all about it here!

Blueshift Launches First AI-Powered Cross-Channel Visual Journey Builder

Blueshift Launches First of It’s Kind AI-Powered Cross-Channel Visual Journey Builder

“One of the biggest challenges for marketers in 2017 will be understanding the connected customer journey across all touch points and how best to interact on a more personal, content-rich level.”
– CMO Council

Introducing The AI-Powered Cross-Channel Visual Journey Builder

Today, we announce the public launch of our AI-Powered Cross-Channel Visual Journey Builder. Blueshift solves the problem of building personalized, content-rich campaigns and customer journeys with a first-of-its-kind approach to customer engagement that brings Data, Artificial Intelligence, and Cross-Channel Automation together into a unified, quick to implement product.

Today’s marketers must build unique, 1:1 user experiences at scale to meet the increasing demands of their perpetually connected customers across all devices and touch points. Only by combining behavioral data, artificial intelligence, and automation does this becomes a reality.

What Makes Blueshift’s Visual Journey Builder Different?

Unlike legacy systems, Blueshift’s AI-Powered Visual Journey Builder enables marketers to trigger cross-channel customer journeys and campaigns based on AI-Computed Predictive Scores, as well as to include AI-Powered content and product recommendations at every step…all through a highly visual and intuitive interface.

This unique approach of combining behavioral data, AI, and automation in a unified product gives marketers the full control they need to respond to every customer behavior with a 1:1 customer experience on every channel. Beyond merely building a simple workflow tool, Blueshift built a unified platform that provides a powerful segmentation engine, multichannel campaign orchestration, predictive scoring (powered by AI), and A/B testing.


Contact us today to schedule a demo to see how AI will make every user experience more personal and relevant.


Unlike legacy marketing cloud solutions and overly simplistic “point-and-click” tools that do not have AI at the core, this unified approach provides the following advantages:

Enter Customers into Journeys at Exactly the Right Time & Right Channel, Based on AI.
In the past, marketers struggled to define rules that should determine when customers enter a journey. With Blueshift, marketers can use AI-Powered Predictive Scores to launch journeys at the perfect time for each customer.

Insert AI-Powered Content Recommendations at Each Step.
With legacy systems, it is often hard to combine content-rich personal experience with automated campaigns. With Blueshift, the visual campaign builder is fully integrated with an AI-Powered Recommendation Studio for content & product recommendations, ensuring a content-rich 1:1 experience across channels. Marketers can even a/b test different types of recommendations.

Track & Measure Campaigns in an Intuitive, Visual Interface.
Legacy systems are unable to tie back attribution data and visualize the data at each step of the customer journey. With Blueshift’s unique integrated approach, marketers select their own conversion metrics from any part of their funnel, customize their attribution models, and visualize campaign performance at each step.

 

But Don’t Take Our Word For It…


Udacity finds success with Blueshift's AI-Powered Visual Journey Builder.Early adopters of the solution include online learning leader, Udacity, who needed a solution that would provide their online students a more personalized experience at every step in the education journey.

 

“Blueshift’s new approach of combining behavioral data, AI and cross-channel automation in a unified product finally enables us to launch more direct customer engagement at scale.”
– Kristy Ng, Sr. Manager, Digital Marketing, Udacity

 

A New Approach that Drives Results


Vouchercloud finds success with Blueshift's AI=Powered Visual Journeys with 81% increase in revenue
Another early adopter, UK’s biggest money saving app, Vouchercloud, has used Blueshift’s Visual Journey Builder to deliver more than 1 billion emails & mobile push notifications, with a small team of marketers.

“Using Blueshift’s AI-Powered customer journeys, our small team has been able to deliver over 1 billion emails and push notifications across 12 countries. The messages are highly personalized with behavior-based, localized recommendations. In just 6 months with Blueshift, we’ve seen engagement rates climb to 40% and year over year direct email revenue has increased by 81%, far exceeding our expectations.”
– Becky Spurr, Head of Communications, Vouchercloud/em>

Read the the full case study here >


Contact us today to schedule a demo to see how AI will make every user experience more personal and relevant.


Blueshift and Redmart Win MARKies Award for Best Use of Programmatic

Blueshift Disrupts Programmatic Technology with MARKies Award Win

Last night, Blueshift disrupted the programmatic technology space by winning a coveted MARKies Award for “Best Use of Programmatic” with their client RedMart, Singapore’s leading online grocer. The 11th Annual MARKies Awards were held in Singapore to honor work by top marketers, agencies, and brands across over two dozen categories. Winners of the MARKies set the benchmark for the industry and are recognized as top performers in their field.

“This is a win for the whole team at RedMart and Blueshift. In the last few years, the word “programmatic” has come to be associated solely with Advertising. Blueshift is disrupting that thought process in the industry, by demonstrating that programmatic techniques can be applied to CRM as well.” ~ Dhruv Shanker, VP – APAC | Blueshift

From Left to Right: Dhruv Shanker (APAC VP of Sales, Blueshift), Bi Ying Wong (Customer Engagement Marketing Manager, RedMart), and Penny Cox (VP of Commercial & Marketing, RedMart)

From Left to Right: Dhruv Shanker (VP – APAC, Blueshift), Bi Ying Wong (Customer Engagement Marketing Manager, RedMart), and Penny Cox (VP of Commercial & Marketing, RedMart)

The category “Best Use of Programmatic” is a new category for the awards. Programmatic is a term typically used to refer to advertising technology that strips out the manual placing of bids and targeting and makes it more automated through sophisticated software/platforms. Blueshift disrupts the marketing industry itself with the introduction of their Programmatic CRM built for forward-thinking brands, like RedMart, ready to harness behavior-based marketing coupled with powerful AI. With the recognition that Blueshift has received by winning a MARKies Award in Programmatic, it is evident that marketers are ready to take the next step with their CRM to overcome the current limitations of scaling behavior-based cross-channel personalization.

“Blueshift’s Programmatic CRM has helped us drive targeted lifecycle marketing, and dramatically improve our re-engagement rates. With Blueshift, we are now able to launch personalized campaigns on email & mobile app push notifications, and drive a consistent message across different marketing channels.”
~ Penny Cox, VP Marketing | RedMart

RedMart’s lean, forward-thinking marketing team used Blueshift’s Programmatic CRM platform to gain a 3x lift in purchases with personalized multi-channel lifecycle marketing.

Read the case study here>>


Blueshift-and-Redmart-win-Best-Use-of-Programmatic-at-MARKies-Awards

Thousands of entries were submitted to the judges, but only a handful were actually recognized for excellence by winning. Within the “Best Use of Programmatic” category, dozens of advertising, technology, and automation companies entered. Blueshift and RedMart competed against Amnet (Microsoft), Publicis (Scoot Airlines), and Vizeum (IKEA) as finalists.