AI for Marketers
PLAYBOOK

Learn how to use plug & play AI applications to drive e-commerce growth

Predictive Marketing Campaigns

Introduction | Where AI can make the biggest impact in marketing

The digital foundation most businesses are built on today is undergoing a massive transformation and everyone’s talking about it. As people involved in contributing to this shift from a technical perspective, we can honestly say AI is not about the hype you see in the news.

While this fundamental change opens up never before seen opportunities, there’s no denying it also comes with added pressure for everyone involved.

In their role as drivers for growth, marketers are the first to feel this new type of tension that’s been accelerating for the past couple of years. They’ve seen first-hand how digital transformation increased customers’ expectations and escalated the demands for growth in a highly competitive market. This leaves marketers stuck between a rock and a hard place, as they say.

But while everyone’s out chasing the shiny new trend, savvy marketers will know to focus on building a lasting competitive advantage by adjusting how they work. This goes beyond using new tools, just as AI goes beyond tech trends.

Experienced marketers know that formulaic marketing no longer works, that creativity and differentiation are more important than ever to stand out in a densely populated market. However, making the time for creative thinking and top-notch implementation is what constitutes a luxury for most marketing teams.

To thrive in a complex and unpredictable environment, marketers must make it all work together: the data flows, the tactics, the tools, and especially the people.

This is where AI can make the biggest impact, from our hands-on experience. Ownership, focus, less guesswork, more trust in data-driven insights - AI can make this possible and we’re going to show you exactly how.

We believe this because we’ve seen it work. We believe this because it’s just about WHAT you can achieve but also about improving HOW you achieve it.

Ciprian Borodescu

Ciprian Borodescu

Co-founder & CEO, MorphL

Alexandra Anghel

Alexandra Anghel

Co-founder & CTO, MorphL

About this playbook

About this playbook illustration

This playbook for marketers outlines our vision for AI-powered marketing solutions that proactively connect e-commerce companies to the specific needs of their individual customers.

Developed through hands-on projects with e-commerce companies in various verticals, this playbook helps marketers understand how AI plug and play applications works in real life. From reducing fragmentation to improving ownership over the data flow, and enhancing targeting, we’ll walk you through it step by step.

Our goal is to enable you to see how you can make AI work in your specific context to improve customer relationships across channels and devices with no overhead.

Marketers like you know this is the time

Marketers were and still are some of the most prolific innovators in the world. Their natural curiosity, their multidisciplinary backgrounds, and their diverse interests means they’re in the best position to experiment with AI.

To be at the forefront of this transformation that goes beyond tech to change how the world works is an incredible opportunity to do great work. But, as you already know, great results never come easy.

That’s why we’re dedicating this playbook to marketers like you, who welcome the challenge of adapting to new human behaviors and innovative ways to satisfy customers’ expectations.

You can also use this playbook as a chance to strengthen your understanding of key AI concepts and level up by then teaching your team and peers.

We’re going to show you exactly how other marketers in e-commerce companies use plug and play AI applications in their work to meet performance KPIs and have a bigger impact in their organisation.

Let’s get started!

Marketers like you struggle with challenges like these

Working with ecommerce companies from various verticals and agencies that handle marketing for them led us to identify the most common struggles marketers have nowadays.

  • Rising customer acquisition costs
  • A heavy marketing stack that eats up time and energy
  • Lack of integration between tools that does the same
  • Siloed data that still takes manual work to extract insights from
  • A certain amount of guesswork around user behavior with low or no ability to predict future actions
  • Evolving customer demands that add pressure on marketers to perform better and deliver faster (i.e. real-time presence across touchpoints)
  • Difficulty in identifying the most engaged and profitable customers
  • Moving from siloed messages to dynamic ones
  • Balancing personalization with protecting users' privacy while ensuring compliance
  • Wanting to use AI without requiring technical know-how but unable to do so because of the lack of info and transparency around how most AI-based tools work.

A marketer’s role is increasingly complicated and their effort often underestimated which is why we want to help.

We understand that, to make significant progress, marketers need a combination of:

Marketer Tools

We worked hard to include both in this playbook you can use as a field guide for making a bigger impact with the resources you have now.

How AI works in a marketing context

In marketing, artificial intelligence is a powerful way to leverage customer data on a scale and depth that was never possible before.

By using AI concepts, such as machine learning or deep learning, AI enables you not only to better understand your customers’ shopping behavior, but also anticipate their next action.

As a result, you gain the ability to target customers with more relevant offers, tailored to their individual needs and specific stages in the customer journey.

The thrilling part about using AI for marketing, no matter the sector or vertical, is that the technology constantly learns from changing customer behaviors, enabling you to keep up with these changes and create highly engaging experiences.

Engaging Experiences

Challenges and solutions to using AI for marketing

With so much on your plate at all times, it can be difficult to translate your eagerness to experiment with new tech into action. We empathize with your challenged and understand the constraints you have to work with in order to make an impact in your role.

That’s one of the reasons we created this playbook: to help marketers like you find a practical, low-effort way to start integrating AI solutions in a manner that doesn’t add overhead and pressure to the daily workflow.

The common barriers to adopting AI in marketing:

  • Lack of AI technical know-how in the company
  • Scarce development resources for the marketing department
  • Time constraints associated with the marketing strategy/roadmap
  • Pressure to balance short-term results with the long-term strategy
  • Little time for experimentation with new solutions

While building and continuing to develop MorphL, we keenly focus on all of these challenges to help you get better results with your available resources. Join us as we outline practical tactics to start using AI to boost your KPIs without requiring extra development time, so you can move fast and grow even faster!

Marketers like you start implementing AI like this

AI has the potential to make marketing tactics more agile, more effective, and a lot more personalized to individuals’ needs. From improving targeting to delivering messaging and offers that anticipate the customer’s next step, the opportunities abound.

Get in control of your marketing stack

On average, marketers use 14(!) tools to achieve their goals (source).

That’s a lot of time wasted on managing them, extracting data, exporting it, and combining it to get insights that take into account the entire customer journey.

You may be already using multiple tools that include some form of AI capabilities but the disconnect between them leads to wasted opportunities and imperfect implementation. AI is not a panacea when employed in contexts with limited use cases.

By using AI-as-a-platform, like MorphL customers do, you can automatically feed insights about individual customers’ behavior into all your other applications and save precious time

1

HOW IT WORKS

Select Your Predictive Model

Predictive Models

Eliminate data silos & get insights you can trust

Correlating data from various tools is time-consuming and leaves you depleted for other creative tasks. Just think of what it takes to create reports.

With AI-as-a-platform, MorphL integrates with all your data sources to surface the key marketing actions that have the biggest impact in terms of KPIs.

No matter the tools you use, you always have the full customer journey in view to make adjustments fast and deploy campaigns effectively.

2

HOW IT WORKS

Connect Your Data Source

Data Sources

Predict user behavior & eliminate guesswork

What if you could identify the most valuable customers who want to give you their money?

What if you could tell the difference between a user who’s just browsing for research and someone who has their credit card ready to go?

What if you could anticipate their next action and greet it with a personalized offer based on their individual needs?

With MorphL, you can achieve all this and more!

Instead of using a range of tools whose inner workings you don’t understand, you can integrate your data sources with MorphL and trigger their capabilities based on behavior specific to each individual customer who visits your website.

3

HOW IT WORKS

Machine Learning Predictions

Machine Learning Predictions

Anticipate and meet new customer demands

People outside the machine learning community rarely talk about this, but it’s important to know: introducing AI in a system changes the users’ behavior.

For example, the on-demand economy has changed customers’ expectations. They now count on their actions bringing them instant gratification 24/7. They’re also used to getting personalized offers and above average experiences which keep raising the bar for marketers.

With AI-as-a-platform, you can meet this new set of behaviors with content, offers, and experiences tailored to each individual user who visits your website, no matter the device.

MorphL triggers predictive actions that are automatically implemented by the marketing tools you use, leaving you more time to focus on strategy, creativity, and optimization.

4

HOW IT WORKS

Trigger Predictive Actions

Trigger Predictive Actions

Improve user recognition & engage your most profitable customers

Traditional targeting and segmentation methods completely miss outliers. These users are equally committed to making a purchase but don’t check the same boxes.

With MorphL, you can identify and engage these ghost users and turn them into a source of growth for the business.

By calculating their probability of converting individually, we help marketers identify users who are most likely to purchase before they move on to this step. This gives marketers a chance to greet them with an offer they can’t refuse.

Through well-timed campaigns, specialists can insert high-quality creative assets (notifications, emails, offers, tutorials, etc.) at the right time in the customer journey without becoming repetitive or irritating. At the same time, marketers get to optimize budgets and use them where it has the biggest ROI.

Predictive Marketing Campaigns

Predictive Marketing Campaigns

Ensure compliance with data protection regulations

Not only does MorphL strengthen data integrity but it also puts marketers back in control of it.

With full GDPR compliance as a standard, AI-as-a-platform provides marketing specialists with the opportunity to target individual customers without invading their privacy.

Predicting customer behavior is based on the individual user’s behavior history on the website, data collected with their consent. MorphL works for both subscription-based websites/product/services and for companies who collect nothing except website usage details.

Using AI-as-a-platform without in-house ML specialists

AI is a new way to engineer experiences but many marketers feel that this is a job for the IT department, as the tech behind AI is some of the most complex in the world.

At MorphL, we’ve made it our mission to lower the barrier for AI adoption by creating plug and play applications that integrate with existing workflows.

What’s more, we’re openly sharing why and how we’re building these models so you’ll always know how your data is handled and used to train the Machine Learning algorithms that power MorphL. Transparency and community contribution are built into our principles.

All predictions created by MorphL are available via an API that can be easily integrated into the marketing team’s reporting dashboard. Plus, we fully automate the model training and predictions in our infrastructure.

You won’t need any AI/ML specialists in-house to use MorphL, as setting it up and using it is just a matter of clicks.

How to use AI

An easier way to integrate AI for a sustainable competitive advantage

The best part about using AI is not the boost in status on the market or being at the forefront of a massive transformation (although these benefits count too). The biggest impact of using an AI platform like MorphL is that it improves a marketer’s job in 3 essential ways:

  1. Simplification and integration of your marketing stack
  2. Focus on customers who are ready to purchase
  3. Creating time for strategic thinking through automation.
Manage apps

Use MorphL to reap the benefits of the network economy to scale your impact and results.

We provide a collection of fully automated predictive models (from data-source to generating predictions) that are platform agnostic. This means MorphL works the same way, irrespective of the data source or app integrations you choose to connect.

The AI-based platform we built uses your analytics and marketing platforms as data sources. It then automatically feeds insights about users into the marketing tools you already use.

You can use these insights across the enterprise and the entire customer journey (with user granularity). As part of your workflow, MorphL enables you to personalize your users’ experience based on their behavior and engage them with calls-to-action that most resonate with them.

Our goal with MorphL is to give you the piece of missing information about your users, empowering you to create better calls-to-action and to spend your marketing budget where it really counts.

Make the rise of AI/ML economy a fundamental competitive advantage for your eCommerce business!

How Morphl ML models works

The 6 steps of planning & launching a predictive marketing campaign

1. Ideation

Not sure where to start to find ideas you can use AI to test and implement?

Here are some ways you can get started:

  • Identify the most common customer complaints and aim to reduce friction. Listen to call center recordings, pour over feedback forms and use anything handy to use existing customer feedback to improve your ecommerce platform.
  • Eat your own dog food. Switch perspectives and see what using your own product/service is like. Walk a mile in your customers’ shoes to better understand how they find, evaluate, and use your ecommerce platform.
  • Spot the most critical improvements you need. You can also start with the KPIs that are lagging and observe where customers drop off or where you have insufficient visibility, clarity, or effectiveness.

2. Strategy

Selecting an AI project involves figuring out what lies at the intersection between what AI can do and what is valuable for your business.

How to select an AI project for your company

For more practical insights into how this works, check out the full webinar with Alexandra Petrus, Google Developer Expert and Product Strategist.

3. Plan

Use these questions to make decisions for setting up an AI project:

What are the key pieces of information that you can’t manually extract from your data?

Which are the outliers or data trends that you cannot capture or identify using the tools you have now?

What drives business value in your organization?

What are the main pain points in your business?

Which tasks do you want to automate?

Mapping customers’ feedback gathered in ideation against your business priorities will reveal countless opportunities for improvement both in how marketing campaigns are implemented and how they play into the greater business context.

AI brainstorming framework

For more practical insights into how this works, check out the full webinar with Alexandra Petrus, Google Developer Expert and Product Strategist.

To start using MorphL, all you need is an open mind to trying a new way of doing marketing and the ability to connect your data sources and marketing stack to the platform.

Leave the rest to us and count on us to guide you through this new territory full of growth possibilities!

4. Integrate

Once MorphL is set up, the technical side of the project is done. The integration at this stage is focused on how you will use the AI-generated predictions in your daily work.

You can choose to embark the entire team on this learning curve, as you identify customer segments you’ve never targeted before (not with this level of accuracy anyway 😊).

Trigger Predictive Actions

For example, using MorphL may shift your priorities to address the most profitable or most loyal customers more frequently instead of investing the bigger part of your advertising budget on attracting new ones.

5. Launch 🚀

There is a lot of expectation and curiosity around launching an AI-enhanced marketing campaign. From our experience, we recommend approaching it with an innovator’s mindset that knows experimentation is the only way to (in)validate assumptions.

In the first stages of the launch, optimize for learning, not for scale. With this principle in mind, you can make faster progress and empower your team to improve not just their skill set but their mindset as well.

6. Optimize

When looking at your campaigns that leverage AI for growth, a couple of things may come up that you can pursue to optimize your efforts.

By using the insights from MorphL, you can:

  • Enhance customer segmentation to pinpoint the most receptive users or customers
  • Perfect personalization to ensure your messaging matches users’ expectations
  • Discover new customer segments (through granularity) you’ve never approached before
  • Refine your messaging and offers to reflect users’ needs and tone of voice
  • Improve customer experience across touchpoints, both on your website and in your ad-driven campaigns.

An integrative AI platform like MorphL helps you design custom experiences (offers, campaigns, ongoing loyalty programs, etc.) based on the intent, behavior, and needs that specific customers have.

With these steps in mind, here are the practical assets you need to get started.

Templates for Predictive Marketing Campaigns

Here’s how MorphL works in the real world for ecommerce companies that want to set a strong foundation for growth in the incoming AI-dominated era.

AI marketing tactics across the customer’s lifecycle

One of the most powerful things about MorphL is that it frees you from the constraints of using individual tools and their limited use cases. The predictions delivered through MorphL can be used across the customer journey, not just in certain touchpoints or specific moments.

Stages of Customer Lifestyle
Stage Tools AI predictions
Awareness Hubspot
Google Ads
Facebook Ads
Wordpress
Keyword Search Intent
Engagement Mailchimp
SendGrid
Remarketing campaigns
Unbounce
WIX
Recommendation Systems
Next Shopping Stage
Churning Users
Evaluation Shopify
Woocommerce
Magento
Next Shopping Stage
Keyword Search Intent
Recommendation Systems
Purchase Google Ads
Facebook Ads
Shopify
Woocommerce
Magento
Stripe
Paypal
Next Shopping Stage
Cart Abandonment
Product & Support Experience Shopify
Woocommerce
Magento
Google Ads
Remarketing campaigns
Next Shopping Stage
Churning Users
Customer Lifetime Value
Advocacy Hubspot
Mailchimp
SendGrid
Unbounce
WIX
Recommendation Systems
Customer Lifetime Value

1. Improve ROI for remarketing campaigns | Shopify + MorphL + Klaviyo

Predictive model: Next Shopping Stage prediction

Next Shopping Stage prediction

WHAT MORPHL DELIVERS

Know, for each specific website user, how probable it is that they will go on to do either of the following actions:

Shopping Scenarios

Using MorphL’s predictive capabilities, you can adjust your triggers (pop-ups, emails, remarketing ads, etc.) to meet your customer’s needs according to the next step in their shopping journey.

HOW YOU CAN USE NEXT SHOPPING STAGE PREDICTIONS TO GET RESULTS

Shopping Stage Predictions
Mobexpert Campaign

2. Boost CTR for PPC campaigns | Google Ads + MorphL

Predictive model: User Search Intent prediction

User Search Intent Prediction

WHAT MORPHL DELIVERS

When you deal with thousands or millions of keywords and want to truly reach the people genuinely interested in your product/services, it’s time to harness MorphL’s power!

Use this practical application to predict intent for millions of keywords with zero manual work and high accuracy.

Free up time to improve PPC campaigns on a strategic level and guide individual users to the most relevant landing pages for them.

Intent Segments

HOW YOU CAN USE USER SEARCH INTENT PREDICTIONS TO GET RESULTS

Intent Discovery

3. Reduce your website users churn | eCommerce platform + MorphL + Google Optimize

Predictive model: Churn prediction

Churn prediction

WHAT MORPHL DELIVERS

When you specifically know which of your customers is about to churn - before it happens - you have a fighting chance to win them back and keep them as customers.

With churn prediction, MorphL indicates which individual customers are about to stop using your product/service/website. With this information ready, you can engage customers at risk of churning in at least two ways:

  • You can offer those customers free shipping or a personalized discount to encourage them to go through with their purchase
  • You can offer them the option of delaying or pausing an order with an application like GetARPU which enables you to send pre-shipping email reminders and notify customers 3 days before their next billing cycle. This gives them the flexibility to pause or delay a shipment instead of cancelling and churning.
Loyalty Segments

HOW YOU CAN USE CHURN PREDICTION TO GET RESULTS

Churn Prediction Results

4. Engage your most profitable customers | Segment + MorphL + Mailchimp

Predictive model: Customer Lifetime Value (CLTV) prediction

Customer Lifetime Value (CLTV) prediction

WHAT MORPHL DELIVERS

Customer loyalty is scarce nowadays and nurturing that takes a deep understanding of customer behavior.

With the MorphL CLTV prediction application you can gain deep insight into the habits and irregularities in your customers’ purchasing patterns. What’s more, you can use MorphL to pinpoint loyal customers who took a longer time than usual to make their next purchase.

Predictive Analytics - Customer Lifetime Value (CLV)

HOW YOU CAN USE CLV PREDICTIONS TO GET RESULTS

CLV Predictions

How to set up | A proof of concept AI project

Most of the customers we work with need a bit of support to pitch their first AI projects to their managers and other stakeholders in the company.

To help you get started, here’s a business case template you can use to build your argument. Feel free to use the information on MorphL.io, our webinars, and our blog to fill in the details!

Project name

One-line project description


Prepared by


Executive summary


Business problem

Brief description


Analysis

Why does this problem exist?

What are the strategic objectives this problem has impact on?

What is the consequence of not solving the problem?

What data-driven arguments support solving the problem?

What is the timeframe for solving the problem?


Proposed solution

Describe the solution

Benefits and value

Risks

Strategic alignment

Goals

Deliverables


Requirements

Human resources

Procurement

Estimated costs


Feasibility


Supporting resources

How to use MorphL predictions | Across the entire customer journey

Although AI is often used as a point solution in the marketing industry, know you can achieve SO much more if you look at your efforts in a coordinated manner.

Here’s how you can use MorphL across the entire customer journey, from expressing intent while researching online to completing their purchases successfully and beyond.

AI predictions Action KPI
Recommendation Systems Display highly targeted product recommendations tailored to each individual website user. Sales
Next Shopping Stage Provide product recommendations targeted to individual user’s preferences. Average Order Size
Next Shopping Stage Increase the number of successful sales on your ecommerce website by delivering notifications, nudges, and recommendations adapted to the shopping stage your customer is about to move into (add to cart, checkout, transaction). Conversion rate
Next Shopping Stage Send highly personalized notifications (via email, mobile push notifications or otherwise) to nudge customers to complete their purchases. Shopping cart abandonment rate
Customer Lifetime Value Engage your most profitable customers through personalized upsells and loyalty campaigns. Customer lifetime value (CLV)
Keyword Search Intent Tailor your ad campaigns to individual user’s intent as revealed by their searches before landing on your website. Customer acquisition cost (CAC)
Churning Users Recover users at risk of churning through deeply personalized offers and reminders. Churn rate
Keyword Search Intent Bring more customers to your website with highly targeted ad campaigns that evoke the tone of voice and language used by individual users as revealed by their searches before landing on your website. Banner or display advertising CTRs

Intro to | AI in marketing

Key AI concepts

With so many new concepts crossing over from data and computer science into marketing, we’re doing our best to help marketers master them and leverage their far-reaching impact.

Here are some of the key AI concepts you will mostly likely come across increasingly frequently in your work.

What is Artificial Intelligence

This is a less-than-final but useful definition from Andreas Kaplan and Michael Haenlein from ESCP Europe Business School, who define AI as:

a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.

By no means is this a perfect definition. In fact, as Kaplan and Haenlein themselves admit:

AI is still a surprisingly fuzzy concept and a lot of questions surrounding it are still open.

For example, you’ll read articles where AI, machine learning (ML) and deep learning (DL) are used interchangeably. This is incorrect, as both ML and DL are subsets of artificial intelligence

all ML = AI BUT all AI ≠ ML
all DL = ML BUT all ML ≠ DL
Difference between AI, ML and DL

What is Machine Learning

Machine learning enables programs to learn through training, instead of being programmed with rules. By processing training data, machine learning systems provide results that improve with experience. (Source: The State of AI 2019: Divergence)

Real-life ML applications include predicting churn or forecasting fraud in credit card transactions.

What is Deep Learning

When it comes to deep learning, you should know it’s often used to work out specific issues. For example:

Deep learning is valuable because it transfers an additional burden – the process of feature extraction – from the programmer to their program. (Source: The State of AI 2019: Divergence)

In practice, deep learning aims to emulate the brain, whether animal or human. The objective is to train these networks of artificial neurons to extract features from data sets that they can later use to optimize processes and solve problems.

Whether we’re talking about AI subsets such as ML and DL (acronyms galore, we know), the objective is to develop technology that can learn through practice.

What is narrow AI

Narrow AI (or weak AI) only works in task-specific contexts. This is the type of AI we have today.

We’re slowly building a library of narrow AI talents that are becoming more impressive. Speech recognition and processing allows computers to convert sounds to text with greater accuracy.

Google is using AI to caption millions of videos on YouTube. Likewise, computer vision is improving so that programs like Vitamin D Video can recognize objects, classify them, and understand how they move. Narrow AI isn’t just getting better at processing its environment it’s also understanding the difference between what a human says and what a human wants
(Source: Aaron Saenz, SingularityHub)

What is Big Data

Big Data relates to the ability of aggregating, analyzing, and segmenting large volumes of data through a process that involves minimal manual input.

Working with big data allows marketers to identify patterns and deliver campaigns that are customized to specific users’ needs and expectations.

What is a Cluster

A cluster is a group of users who share a common set of traits. AI is capable of processing and interpreting large volumes of data (big data) to identify correlations humans would otherwise miss.

Clusters are extremely helpful for targeting specific audiences and even individual customers, generating marketing opportunities for growth.

What is Image recognition (or “computer vision”)

In the context of AI, image recognition is the capacity of artificial intelligence to analyze images and identify objects, places, people, written text, and actions within them. This enables the AI system to identify particularities the human eye might miss.

What is Natural Language Processing (NLP)

In the context of AI, NLP enables computers to determine what humans are saying, both through text and voice. AI is advancing to infer context and the more subtle nuances of human language.

What are Neural networks

Artificial neural networks are computing systems modeled after the human brain. They were designed to learn and overcome the limitations of task-specific rules.

What is Semantic analysis

This is the process of using AI to understand natural human language from the perspective of its meaning and in context (relationship, cultural, etc.).

What makes AI different from rule-based systems

Rule-based systems Learning systems (AI)
Use static if-then-that rules Can create, discard, and change rules based on what they learn
Knowledge is encoded as fixed rules Knowledge changes through learning (adaptive intelligence)
New situations that require new rules get the system stuck The system can adapt to new situations by creating new rules
The larger the data pool, the bigger the risk of introducing conflicting rules The larger the data pool, the better the system becomes by learning from specific situations
Top uses of AI in marketing, by economic sector

Source: The CMO Survey: Highlights and Insights Report, February 2019

Opportunities for growth you can unlock using AI for marketing

The concepts and technology in artificial intelligence bring never before seen opportunities for marketers across industries. Here are some of them to inspire your own journey to better serving your customers and reaching your KPIs:

Customers’ evolving needs Changes in customer behavior Growth opportunities driven by practical AI solutions for marketers
Individual expression Personalized service Improved accuracy in targeting through contextual analysis
Simplicity and ease of use Accessible and convenient Enhanced relevancy for creative assets (banners, ads, videos, articles, etc.)
Dialogue as an effective way to solve issues Immediate assistance Predictive customer service by identifying evolving patterns
Instant gratification Anywhere, in real-time Marketing automation across multiple touch-points through predictive insights
Connectedness and reliability Continual engagement & service Personalized suggestions and recommendations
Consumption as a matter of ethical concern Always-known - transparent and ethical Improved workflows - less manual work, more focus on strategy and non-scalable creative work

Marketing and sales is the industry that most started adopting AI most promptly. The reason for this openness is that AI-driven insights create significant value and ROI in a marketing context.

While there are still barriers to adoption, companies that started using AI are already reaping meaningful rewards both in terms of business results and productivity. A McKinsey & Company analysis reveals that 69% of surveyed professionals working in marketing and sales reported deriving significant or moderate value from adopting AI.

Business functions in witch AI has been dopted, by industry

Source: AI adoption advancement analysis by McKinsey & Company

The retail sector alone forecasted investments of up to $5.9 billion in 2019 in AI-based solutions to perform improvements such as automated customer service and enhanced product recommendations.

Marketers using AI are already seeing results from adoption solutions that help them have a more granular approach that involves less guesswork and more reliable targeting:

Percentage of Marketers

Source: Salesforce’s State of Marketing Study, 5th edition

From email marketing to campaign optimization, you can use AI-driven insights across all your marketing activities and assets, saving time and investing more energy where it matters the most: in strategy and creative assets that require critical thinking and the human touch.

We hope you’ll use this playbook to discover new ways to reach and engage customers in a way that’s meaningful and rewarding for both of you!

Key takeaways

How to start working with AI

  • AI impacts both results and workflows, and even the way a marketer's role is perceived in the company
  • You CAN reap meaningful rewards from using AI even without an in-house team of machine learning specialists
  • Using an AI-as-a-platform helps you integrate your marketing stack and automate triggers, saving you time and manual effort
  • Adopting AI and adding it to the marketing workflow can uncover opportunities for growth that have never been tapped into
  • Marketers have the chance to become AI pioneers in their companies, as they've always been innovation champions
  • Starting small, with a proof of concept project, gives marketers the data and arguments to build an internal business case for expanding the use of AI throughout the company

How to accelerate growth with AI

  • Gain a deeper, more granular, more accurate understanding of your consumers
  • Optimize your digital advertising campaigns for better quality and ROI
  • Reach individual customers with personalized offers tailored to their particular needs
  • Create dynamic, highly engaging experiences across touchpoints and customer journey stages
  • Predict customer behavior and adjust your creative assets based on your customers’ next action.

Curated resources to keep going

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