As we navigate the ever-evolving landscape of digital marketing, one thing is clear: personalization is key to driving customer engagement and loyalty. With the average consumer interacting with a brand across multiple touchpoints, from social media to email and beyond, the need for a seamless, omnichannel experience has never been more pressing. According to recent research, companies that adopt an omnichannel strategy see a 91% higher customer retention rate compared to those that don’t. In this blog post, we’ll explore the 5-step roadmap to deploying AI-powered omnichannel marketing, a strategic guide designed specifically for business leaders and marketers looking to stay ahead of the curve. By leveraging the latest advancements in AI and machine learning, you’ll learn how to create a cohesive, data-driven marketing strategy that meets your customers where they are, driving meaningful connections and conversions. In the following sections, we’ll dive into the key steps and best practices for implementing an effective AI-powered omnichannel marketing strategy, providing you with the insights and expertise you need to succeed in today’s fast-paced digital landscape.

Welcome to the world of AI-powered omnichannel marketing, where the lines between online and offline channels are blurring, and customer expectations are soaring. In today’s digital age, customers interact with brands across multiple touchpoints, expecting seamless, personalized experiences. As we here at SuperAGI have seen, businesses that fail to deliver omnichannel marketing strategies risk losing customers and revenue. In this introduction, we’ll explore the evolution of marketing from single-channel to omnichannel and why AI is the game-changer for success. We’ll delve into the importance of adopting AI-powered omnichannel marketing and set the stage for the 5-step roadmap that will guide business leaders and marketers in deploying effective AI-powered omnichannel marketing strategies.

The Evolution of Marketing: From Single-Channel to Omnichannel

Marketing has come a long way from its traditional single-channel roots, where businesses relied on a sole medium, such as print or television, to reach their audience. The advent of new channels and technologies led to the emergence of multichannel marketing, where companies used multiple channels, like email, social media, and websites, to interact with customers. However, this approach had its limitations, as it often resulted in disconnected experiences across channels.

Today, we’re in the era of omnichannel marketing, which represents a significant shift towards integrated, seamless, and customer-centric experiences. The key difference between multichannel and omnichannel lies in their approach: multichannel marketing focuses on using multiple channels, whereas omnichannel marketing emphasizes the integration of these channels to provide a unified experience. According to a Harvard Business Review study, companies that adopt an omnichannel approach see a 10% year-over-year increase in revenue, compared to a 3.4% decline for those using a multichannel strategy.

Recent statistics highlight the importance of omnichannel marketing in meeting consumer expectations. A study by Salesforce found that 80% of customers consider the experience a company provides to be as important as its products or services. Moreover, Google reports that 60% of consumers use multiple devices to make a single purchase, demonstrating the need for seamless experiences across channels.

  • 75% of consumers expect a consistent experience across all channels (source: SAP)
  • 85% of customers use more than one channel to interact with a company (source: Forrester)
  • Companies that prioritize customer experience see a 20-30% increase in loyalty and retention (source: Bain & Company)

As we can see, the evolution of marketing has been driven by changing consumer behaviors and the need for integrated experiences. By adopting an omnichannel approach, businesses can provide seamless interactions across channels, ultimately leading to increased customer satisfaction, loyalty, and revenue growth. With the help of AI-powered tools, such as those offered by SuperAGI, companies can now streamline their marketing efforts, personalize customer experiences, and drive business success.

Why AI is the Game-Changer for Omnichannel Success

The advent of Artificial Intelligence (AI) has revolutionized the marketing landscape, and its impact on omnichannel marketing is particularly profound. AI enables brands to deliver personalized experiences at scale, make data-driven decisions in real-time, and predict customer behavior with uncanny accuracy. This is achieved through predictive analytics, which allows marketers to forecast customer interactions and tailor their strategies accordingly. For instance, Sailthru, a leading AI-powered marketing platform, helps brands like Sephora and The New York Times personalize their customer journeys, resulting in significant increases in engagement and conversion rates.

One of the key advantages of AI in omnichannel marketing is its ability to automate routine tasks, freeing up marketers to focus on high-level strategy and creative work. Companies like Domino’s Pizza and Uber are leveraging AI-powered chatbots to handle customer inquiries, provide personalized recommendations, and even facilitate transactions. According to a study by Gartner, AI-powered chatbots can reduce customer support costs by up to 30%.

Real-time decisioning is another area where AI excels, enabling marketers to respond to changing customer behaviors and preferences in the moment. For example, Netflix uses AI to analyze viewer behavior and adjust its content recommendations in real-time, resulting in a more personalized and engaging experience for its users. Similarly, Amazon uses AI to optimize its pricing, inventory, and supply chain management, ensuring that customers receive the best possible experience.

The measurable impact of AI on omnichannel marketing key performance indicators (KPIs) is substantial. According to a study by Marketo, companies that use AI in their marketing strategies see an average increase of 25% in customer engagement, 15% in conversion rates, and 10% in revenue growth. Furthermore, a survey by Salesforce found that 62% of marketers believe that AI has improved their ability to deliver personalized customer experiences, while 57% say it has enhanced their ability to make data-driven decisions.

Some of the most successful AI-powered omnichannel marketing strategies include:

  • Personalized email marketing: Using AI to analyze customer behavior and tailor email content, subject lines, and send times for maximum engagement.
  • Chatbot-powered customer support: Leveraging AI-powered chatbots to provide 24/7 customer support, answer frequently asked questions, and even facilitate transactions.
  • Predictive analytics: Using AI to analyze customer data and predict future behavior, allowing marketers to proactively tailor their strategies and improve customer experiences.

As AI continues to evolve and improve, its potential to transform omnichannel marketing will only continue to grow. By embracing AI and leveraging its capabilities, marketers can deliver more personalized, engaging, and effective customer experiences, driving revenue growth, customer loyalty, and long-term success.

As we dive into the 5-step roadmap for deploying AI-powered omnichannel marketing, it’s essential to start with a solid foundation. Before you can harness the power of AI to elevate your marketing efforts, you need to understand your current state of affairs. In this section, we’ll explore the critical first step: assessing your current marketing infrastructure and data readiness. You’ll learn how to conduct a thorough channel and customer journey audit, evaluate your data quality, integration, and governance, and identify areas for improvement. By doing so, you’ll set yourself up for success in implementing an effective AI-powered omnichannel marketing strategy that drives real results. According to industry insights, a well-planned infrastructure and data strategy are crucial for successful AI adoption, with many marketers citing data quality and integration as major challenges. Let’s get started on laying the groundwork for a seamless and efficient AI-powered omnichannel marketing approach.

Conducting a Channel and Customer Journey Audit

To conduct a thorough channel and customer journey audit, it’s essential to map existing customer journeys across all channels, identify friction points, and evaluate the effectiveness of each touchpoint. This process involves creating a visual representation of the customer’s experience, from initial awareness to post-purchase support. For instance, a company like Stitch Fix can use journey mapping to understand how their customers interact with their service, from receiving personalized clothing recommendations to providing feedback on their purchases.

A framework for documenting customer interactions and measuring engagement across channels can be broken down into the following steps:

  • Identify all touchpoints: List every possible interaction a customer can have with your brand, including social media, email, website, customer support, and in-store experiences.
  • Map the customer journey: Use tools like SmartDraw or Lucidchart to create a visual map of the customer’s journey, highlighting pain points and areas of friction.
  • Evaluate touchpoint effectiveness: Assess the impact of each touchpoint on the customer’s experience, using metrics such as engagement rates, conversion rates, and customer satisfaction scores.
  • Analyze customer feedback: Collect and analyze customer feedback from various sources, including surveys, reviews, and social media, to gain insight into the customer’s perspective and identify areas for improvement.

Practical tools and methodologies for journey mapping include:

  1. Customer journey mapping workshops: Bring together cross-functional teams to map the customer journey and identify areas for improvement.
  2. Service blueprinting: Create a detailed diagram of the customer’s experience, highlighting front-stage and back-stage processes.
  3. Empathy mapping: Use tools like Mural to create a visual representation of the customer’s thoughts, feelings, and pain points throughout their journey.

By following this framework and using the right tools and methodologies, businesses can gain a deeper understanding of their customers’ experiences and identify opportunities to improve engagement, reduce friction, and increase customer satisfaction. According to a study by Gartner, companies that use customer journey mapping are more likely to see an increase in customer satisfaction and loyalty, with 75% of organizations reporting a significant improvement in customer experience.

Evaluating Data Quality, Integration, and Governance

Data quality is the foundation upon which successful AI-powered omnichannel marketing is built. High-quality data enables accurate predictions, informed decision-making, and personalized customer experiences. However, research suggests that many organizations struggle with data quality issues, with 60% of companies reporting that their data is not yet ready for AI implementation. To address this challenge, it’s essential to assess current data silos and establish proper governance frameworks.

When evaluating data quality, integration, and governance, consider the following key factors:

  • Data accuracy and completeness
  • Data standardization and consistency
  • Data security and compliance
  • Data accessibility and sharing

Common data challenges that organizations face include:

  1. Fragmented data sources and silos
  2. Inconsistent data formats and standards
  3. Insufficient data governance and quality control
  4. Limited data accessibility and sharing

To overcome these challenges, organizations can establish a robust data governance framework that includes:

  • Clear data policies and procedures
  • Defined data roles and responsibilities
  • Regular data quality checks and audits
  • Ongoing data training and education

A case study of SuperAGI helping a company unify their fragmented data sources is a great example of how to address data challenges. By implementing SuperAGI’s AI-powered data integration platform, the company was able to consolidate their customer data from multiple sources, including CRM, social media, and website analytics. This enabled them to create a single, unified customer view and deliver personalized marketing campaigns that resulted in a 25% increase in sales. As we here at SuperAGI often see, the key to successful AI implementation is not just about the technology, but about the data that drives it.

By prioritizing data quality, integration, and governance, organizations can lay the foundation for successful AI-powered omnichannel marketing and drive business growth. As Forrester notes, “Data quality is the most critical factor in ensuring the success of AI and machine learning initiatives.” By addressing data challenges and establishing a robust data governance framework, organizations can unlock the full potential of AI and deliver exceptional customer experiences.

Now that you’ve assessed your current marketing infrastructure and data readiness, it’s time to define your omnichannel strategy and AI implementation roadmap. This critical step will lay the foundation for a tailored approach that aligns with your business goals and leverages the power of AI to drive customer engagement. In this section, you’ll learn how to identify the most effective AI-powered use cases for your organization, select the right technology partners and solutions, and create a clear roadmap for implementation. By doing so, you’ll be able to harness the full potential of AI to deliver personalized, seamless customer experiences across all touchpoints, ultimately driving revenue growth and competitive advantage. With the right strategy in place, you’ll be well on your way to unlocking the benefits of AI-powered omnichannel marketing and staying ahead of the curve in today’s rapidly evolving marketing landscape.

Aligning Business Goals with AI-Powered Use Cases

To create an effective AI-powered omnichannel marketing strategy, it’s essential to identify high-value use cases that support your business objectives. This involves analyzing your organization’s goals and determining how AI can help achieve them. For instance, if your goal is to improve customer satisfaction, you might consider using AI-powered chatbots to provide personalized support and improve response times. According to a study by Gartner, companies that use AI-powered chatbots see a 25% increase in customer satisfaction ratings.

Some examples of AI applications in marketing include:

  • Personalization: Using AI to analyze customer data and create personalized recommendations, such as Amazon’s product suggestions or Netflix’s content recommendations.
  • Predictive analytics: Using AI to analyze customer behavior and predict future actions, such as Salesforce’s Einstein analytics platform.
  • Content generation: Using AI to generate high-quality content, such as WordLift’s AI-powered content creation platform.

These AI applications can have a significant impact on revenue, customer satisfaction, and operational efficiency. For example, a study by McKinsey found that companies that use AI-powered personalization see a 10-15% increase in revenue. Additionally, a study by Forrester found that companies that use AI-powered predictive analytics see a 20-30% increase in customer retention rates.

To identify high-value AI use cases, consider the following steps:

  1. Align AI use cases with business objectives: Determine how AI can help achieve your business goals, such as increasing revenue or improving customer satisfaction.
  2. Assess data quality and availability: Determine if you have the necessary data to support AI-powered use cases, such as customer behavior data or sales data.
  3. Evaluate technology and resource requirements: Determine the technology and resource requirements for implementing AI-powered use cases, such as data scientists or machine learning engineers.

By following these steps and considering examples of AI applications in marketing, you can identify high-value AI use cases that support your business objectives and drive revenue, customer satisfaction, and operational efficiency growth. We here at SuperAGI have seen firsthand how our AI-powered sales platform can help businesses achieve their goals, and we’re excited to help you do the same.

Selecting the Right Technology Partners and Solutions

When it comes to selecting the right technology partners and solutions for your AI-powered omnichannel marketing strategy, there are several key criteria to consider. At we here at SuperAGI, we believe that a thorough evaluation of potential partners is crucial to ensuring the success of your omnichannel efforts. First and foremost, integration capabilities should be a top priority. Look for platforms that can seamlessly integrate with your existing marketing stack, including CRM, ERP, and other core systems. For example, Marketo offers a range of pre-built integrations with popular marketing and sales tools, making it easy to incorporate into your existing ecosystem.

In addition to integration capabilities, scalability is also essential. As your business grows, your technology partners should be able to scale with you, providing the necessary support and resources to meet increasing demand. Consider platforms like Salesforce, which offers a range of scalable solutions for businesses of all sizes. We here at SuperAGI also prioritize scalability, ensuring that our platform can adapt to the evolving needs of our customers.

Expertise is another critical factor to consider when evaluating AI marketing platforms and technology partners. Look for partners with a deep understanding of AI and machine learning, as well as experience in implementing omnichannel marketing strategies. For instance, SAS offers a range of AI-powered marketing solutions, backed by a team of expert data scientists and marketing professionals. Our team at SuperAGI also comprises experienced professionals who can provide guidance and support throughout the implementation process.

When it comes to building vs. buying, there are pros and cons to consider. Building a custom solution can provide a high degree of flexibility and control, but it can also be time-consuming and resource-intensive. On the other hand, buying an off-the-shelf solution can be faster and more cost-effective, but may not provide the same level of customization. Ultimately, the decision to build or buy will depend on your specific needs and goals. At we here at SuperAGI, we offer a range of solutions that can be tailored to meet the unique needs of our customers.

To create a technology ecosystem that supports your omnichannel vision, consider the following best practices:

  • Develop a clear understanding of your business goals and objectives
  • Assess your current technology stack and identify areas for integration and optimization
  • Evaluate potential technology partners based on their expertise, scalability, and integration capabilities
  • Consider a phased implementation approach, starting with a pilot project or proof-of-concept
  • Establish a cross-functional team to oversee the implementation and ensure alignment with business goals

By following these guidelines and carefully evaluating potential technology partners, you can create a robust and effective technology ecosystem that supports your AI-powered omnichannel marketing strategy and drives business success. As we here at SuperAGI continue to innovate and improve our platform, we remain committed to helping our customers achieve their marketing goals.

Now that we’ve laid the groundwork for our AI-powered omnichannel marketing strategy, it’s time to bring it all together. In this section, we’ll dive into the implementation of cross-channel orchestration and personalization, a critical step in creating a seamless customer experience. Research has shown that companies with a strong omnichannel strategy retain an average of 89% of their customers, compared to 33% for those without one. To achieve this level of customer engagement, we’ll explore the process of creating unified customer profiles and segments, as well as designing automated, trigger-based customer journeys. By the end of this section, you’ll have a clear understanding of how to implement a personalized, cross-channel approach that drives real results for your business.

Creating Unified Customer Profiles and Segments

To create unified customer profiles, you need to integrate data from multiple sources, including customer relationship management (CRM) systems, marketing automation tools, and social media platforms. For example, Salesforce provides a comprehensive platform for integrating customer data from various sources, allowing businesses to build a single, unified view of their customers. By integrating data from multiple sources, you can create a “golden record” – a single, authoritative record of each customer that includes all relevant information about their interactions, preferences, and behaviors.

The golden record is the foundation of a successful omnichannel marketing strategy, as it powers consistent experiences across channels. With a unified customer profile, you can ensure that every interaction with your customer is personalized, relevant, and timely. For instance, Starbucks uses customer data to offer personalized promotions and recommendations to its customers, resulting in a 26% increase in customer spending.

AI can help identify meaningful segments and personalization opportunities by analyzing customer data and behavior. For example, Adobe Analytics uses machine learning algorithms to identify high-value customer segments and predict their behavior. By analyzing customer data, you can identify patterns and trends that can inform your marketing strategy and improve customer engagement. Some key benefits of using AI for customer segmentation include:

  • Improved accuracy and precision in segment identification
  • Increased efficiency in targeting and personalization
  • Enhanced customer experiences and loyalty

To get started with building comprehensive customer profiles and identifying meaningful segments, follow these steps:

  1. Integrate data from multiple sources, including CRM, marketing automation, and social media platforms
  2. Use AI and machine learning algorithms to analyze customer data and behavior
  3. Identify high-value customer segments and predict their behavior
  4. Use the golden record to power consistent experiences across channels
  5. Continuously monitor and update customer profiles to ensure accuracy and relevance

By following these steps and leveraging the power of AI, you can create unified customer profiles that drive personalized, relevant, and timely interactions with your customers, resulting in increased loyalty, engagement, and revenue. According to a study by Forrester, companies that use AI for customer segmentation and personalization see an average increase of 20% in customer satisfaction and a 15% increase in revenue.

Designing Automated, Trigger-Based Customer Journeys

Designing automated, trigger-based customer journeys is a crucial step in implementing cross-channel orchestration and personalization. This approach allows businesses to respond to customer behaviors and preferences in real-time, creating a more personalized and engaging experience. For instance, Starbucks uses automated workflows to send personalized offers to customers based on their purchase history and loyalty program status. When a customer makes a purchase, it triggers a workflow that sends a personalized offer to their email or mobile device, encouraging them to make another purchase.

Trigger-based workflows typically include decision points that determine the next step in the customer journey. These decision points can be based on customer data, such as demographics, behavior, or preferences. For example, Amazon uses decision points to determine whether a customer is likely to abandon their shopping cart. If a customer has items in their cart but hasn’t checked out, Amazon sends a reminder email with a personalized offer to encourage them to complete the purchase. According to Salesforce, companies that use automated workflows to respond to customer behaviors see a 15% increase in sales.

AI plays a significant role in continuously optimizing these journeys based on performance data. By analyzing customer interactions and responses, AI can identify areas for improvement and make recommendations for optimization. For example, HubSpot uses AI-powered analytics to optimize email workflows, determining the best subject lines, email copy, and calls-to-action to use based on customer engagement data. This approach has been shown to increase email open rates by up to 25%, according to HubSpot.

  • Define trigger points: Identify the events or behaviors that will trigger the automated workflow, such as a customer making a purchase or abandoning their shopping cart.
  • Set decision points: Determine the criteria for making decisions about the next step in the customer journey, such as customer demographics or behavior.
  • Use AI for optimization: Leverage AI-powered analytics to continuously optimize the automated workflows based on performance data, such as customer engagement and conversion rates.

By following these steps and using real-time data and analytics to inform decision-making, businesses can create automated, trigger-based customer journeys that drive engagement, conversion, and revenue growth. According to Gartner, companies that use AI-powered automation see a 20% increase in revenue growth, making it a key strategy for businesses looking to stay ahead of the competition.

As you’ve made your way through this 5-step roadmap, you’ve laid the foundation for a robust AI-powered omnichannel marketing strategy. Now, it’s time to talk about the final piece of the puzzle: measuring, optimizing, and scaling your approach. This is where the rubber meets the road, and you start to see real ROI from your efforts. In this section, we’ll dive into the importance of defining cross-channel attribution and ROI metrics, as well as how to leverage AI for continuous optimization and innovation. With the right metrics and mindset, you’ll be able to refine your strategy, identify areas for improvement, and ultimately drive more revenue and growth for your business. By the end of this section, you’ll have a clear understanding of how to take your AI-powered omnichannel marketing to the next level and stay ahead of the competition.

Defining Cross-Channel Attribution and ROI Metrics

To measure the impact of omnichannel initiatives, businesses can leverage multi-touch attribution models, which assign credit to each touchpoint in a customer’s journey. For instance, Google Analytics 4 provides a range of attribution models, including data-driven attribution, which uses machine learning to assign credit based on the unique characteristics of each customer’s journey. According to a study by Google, businesses that use data-driven attribution see an average increase of 10% in ROI compared to those using traditional attribution models.

Another approach is incrementality testing, which measures the incremental impact of a specific marketing channel or campaign on customer behavior. Facebook Attribution is a tool that allows businesses to measure the incremental impact of their Facebook and Instagram ads on customer conversions. For example, Coca-Cola used Facebook Attribution to measure the incremental impact of their Facebook ads on sales and found that for every dollar spent on Facebook ads, they saw a return of $1.34 in incremental sales.

To quantify the ROI of AI investments in marketing, businesses can use metrics such as customer lifetime value (CLV) and return on ad spend (ROAS). CLV measures the total value a customer is expected to bring to a business over their lifetime, while ROAS measures the revenue generated by a specific ad campaign compared to its cost. According to a study by Salesforce, businesses that use AI-powered marketing automation see an average increase of 25% in CLV and 15% in ROAS.

Some key considerations when measuring the ROI of AI investments in marketing include:

  • Define clear goals and objectives for AI-powered marketing initiatives
  • Establish a baseline for measuring ROI and track progress over time
  • Use data and analytics to inform decision-making and optimize marketing strategies
  • Continuously monitor and evaluate the performance of AI-powered marketing initiatives

By taking a data-driven approach to measuring the impact of omnichannel initiatives and AI investments in marketing, businesses can demonstrate value to stakeholders and make informed decisions to drive growth and revenue.

Leveraging AI for Continuous Optimization and Innovation

As we dive into the world of continuous optimization and innovation in AI-powered omnichannel marketing, it’s clear that AI plays a vital role in identifying areas for improvement and driving marketing performance forward. With the help of machine learning models, marketers can analyze vast amounts of customer data to pinpoint optimization opportunities that may have gone unnoticed by human eyes. For instance, Netflix uses AI-powered algorithms to personalize content recommendations, resulting in a significant increase in user engagement and a reported 75% of viewer activity being driven by these recommendations.

One of the key benefits of AI in marketing optimization is the ability to test variations at scale. By leveraging techniques like A/B testing and multivariate testing, marketers can quickly and efficiently determine which marketing strategies are driving the best results. Companies like HubSpot and Marketo offer AI-powered testing tools that enable marketers to automate the testing process, reducing the time and resources required to achieve optimal results. For example, Expedia used AI-powered testing to optimize its website and mobile app, resulting in a 10% increase in bookings and a 25% increase in revenue.

To illustrate the power of AI-driven optimization, consider the following examples:

  • Amazon uses machine learning models to optimize product recommendations, resulting in a significant increase in sales and customer satisfaction. As the models process more data, they become increasingly accurate, driving better results over time.
  • Google leverages AI to optimize ad targeting and delivery, resulting in higher ROI and more effective campaigns. By analyzing vast amounts of data, Google’s AI algorithms can identify the most effective ad creatives, targeting strategies, and bidding approaches.
  • Salesforce uses AI-powered analytics to optimize customer journeys, resulting in improved customer engagement and loyalty. By analyzing customer behavior and preferences, Salesforce’s AI algorithms can identify areas for improvement and provide personalized recommendations to customers.

As machine learning models process more data, they become increasingly effective at driving marketing performance. According to a report by McKinsey, companies that leverage AI in their marketing efforts can expect to see a 20-30% increase in ROI compared to those that do not. By embracing AI-powered optimization and innovation, marketers can unlock new levels of performance and drive business growth in today’s fast-paced, data-driven landscape.

In conclusion, deploying AI-powered omnichannel marketing is no longer a choice, but a necessity for businesses to stay competitive in today’s digital landscape. As we’ve discussed in this 5-step roadmap, assessing your current marketing infrastructure, defining your omnichannel strategy, implementing cross-channel orchestration, measuring and optimizing, and scaling your approach are crucial steps to success. By following these steps, businesses can unlock the full potential of AI-powered omnichannel marketing, driving increased customer engagement, improved customer experience, and ultimately, revenue growth.

According to recent research, companies that adopt omnichannel marketing strategies see a 24% increase in customer retention rates and a 10% increase in revenue. With the help of AI, businesses can take their marketing efforts to the next level, providing personalized experiences that meet the evolving needs of their customers. To learn more about how to implement AI-powered omnichannel marketing, visit Superagi and discover the latest trends and insights in the industry.

As you embark on this journey, remember that the key to success lies in continuous measurement, optimization, and scaling. Stay ahead of the curve by leveraging the latest technologies and trends, such as AI-powered chatbots, voice marketing, and augmented reality. By doing so, you’ll be well-positioned to drive business growth, improve customer satisfaction, and stay competitive in an ever-evolving market. So, take the first step today and start transforming your marketing strategy with AI-powered omnichannel marketing. The future of marketing is here, and it’s time to get on board.