Enhancing Buyer Journeys with AI & Automation is critical for driving growth and revenue. While traditional marketing automation platforms, like Marketo, provide a strong foundation for managing email campaigns and basic workflows, they often fall short when it comes to real-time personalization, predictive insights, and cross-channel engagement. For visionary CMOs aiming to stay ahead of the competition, it’s crucial to recognize that AI-driven solutions, which augment traditional platforms, empower them to take control of their marketing strategies.
In this blog, we’ll explore critical use cases demonstrating where traditional marketing automation falls short and how AI-powered platforms like Make can fill those gaps to optimize buyer journeys and drive revenue, making your marketing process more efficient and effective.
USE CASE: Real-Time Personalization and Content Delivery for Future-Ready Customer Experiences
When a prospect interacts with your brand—for example, by reading a product blog post—it’s critical to follow up with relevant, personalized content. Delivering the right content at the right time, such as a case study or product demo tailored to their industry or behavior, helps move the prospect from awareness to consideration more efficiently. In today’s competitive environment, timely and personalized engagement is essential for driving conversions and accelerating the buyer’s journey.
Where Traditional Marketing Automation Falls Short:
- Static, Rule-Based Personalization: Marketo and similar platforms rely heavily on predefined rules set by marketers. While effective for segmenting audiences, this approach lacks the flexibility to adjust to real-time, fast-changing behaviors.
- Manual and Time-Consuming Setup: Marketo personalization workflows require manual setup and adjustments, limiting the ability to scale without significant overhead. This leads to delays in delivering personalized content based on real-time prospect actions.
- Lack of Predictive Capabilities: Traditional marketing automation reacts to past behavior but lacks AI-driven insights to predict what content a prospect will most likely engage with next, meaning missed opportunities to provide timely, relevant recommendations.
How AI Helps to Fill the Gaps:
- Dynamic, Real-Time Personalization: Make, powered by AI, overcomes the limitations of static rule-based systems by dynamically adjusting content based on real-time interactions. Whether a prospect engages on your website, email, or social media, Make can immediately trigger personalized content recommendations without manual intervention.
- Predictive Content Delivery: Make uses AI to predict which content will most likely drive engagement based on the prospect’s behavior, historical data, and similar customer journeys. For example, after reading a blog post, Make might recommend a relevant case study, ROI calculator, or product demo video that aligns with their specific industry or needs.
- Cross-Channel Orchestration: Unlike Marketo, which primarily focuses on email, Make orchestrates content delivery across multiple channels. This ensures that whether the prospect engages through email, a website, or a chatbot, they receive consistent and relevant content. AI ensures seamless, multi-channel engagement that keeps the buyer engaged throughout their journey.
- Real-Time Adjustments: As new data comes in, AI continuously learns and adjusts its approach. This enables marketers to immediately provide timely responses and personalized content, something static marketing automation platforms struggle with. With Make, your strategy is agile and adaptive, automatically fine-tuning to optimize the buyer’s journey.
USE CASE: Dynamic Lead Scoring and Predictive Lead Prioritization
In B2B marketing, knowing which leads are most likely to convert is critical for prioritizing outreach and closing deals faster. Traditional lead scoring models, which are often based on engagement data, may overlook key signals of buyer intent. To optimize revenue, CMOs must enable predictive lead scoring that dynamically assesses lead quality and ensures sales teams focus on the highest potential leads in real-time.
Where Traditional Marketing Automation Falls Short:
- Limited by Predefined Rules: Marketo’s lead scoring relies on static, rules-based criteria, such as points assigned for email opens or event registrations. These predefined rules don’t account for changes in behavior or external signals that indicate increased buying intent.
- No Predictive Intelligence: Traditional systems react to past behavior without offering predictive insights. This leaves marketers to manually adjust scores without clearly understanding how likely a lead is to convert.
- Manual Updates: Changes in lead scores often require manual input, which slows down the response time for sales teams and reduces the overall efficiency of the lead management process.
How AI Helps to Fill the Gaps:
- Predictive Lead Scoring: AI models in Make analyze a wide range of data points—including third-party intent signals and historical behaviors—to dynamically adjust lead scores in real-time. This enables marketing and sales teams to focus on high-value leads that are more likely to convert.
- Proactive Lead Prioritization: Instead of waiting for a set of rules to flag a lead as high-priority, AI-driven systems can predict which leads are about to take key actions, such as requesting a demo or starting a free trial. Make can automatically route these leads to the appropriate sales reps for immediate follow-up.
- Real-Time, Data-Driven Decisions: AI continually updates lead scores based on new data, ensuring that marketing and sales teams always work with the most accurate, up-to-date information.
USE CASE: Multi-Channel Orchestration for Omni-Channel Engagement
Buyers engage across multiple channels throughout their journey—from email and social media to live chat and website interactions. To create a seamless experience, CMOs must ensure consistent, real-time engagement across all touchpoints. Coordinating this Omni-channel engagement is key to building trust and moving buyers through the funnel more efficiently.
Where Traditional Marketing Automation Falls Short:
- Channel-Specific Automation: Platforms like Marketo excel at email automation but often require third-party tools to manage social media, web interactions, or chat-based engagement, leading to disjointed experiences.
- Siloed Campaigns: Messaging in traditional automation platforms is often segmented by channel, leading to disconnected experiences. For example, email campaigns may not coordinate with social ads or web chat interactions, making it difficult to provide a cohesive buyer journey.
- Delayed Adjustments: Without real-time cross-channel coordination, adjusting messaging and strategy instantly based on new buyer behaviors is challenging.
How AI Helps to Fill the Gaps:
- Unified, Cross-Channel Orchestration: Make ensures that content and engagement are synchronized across all platforms—whether it’s email, social media, live chat, or your website. AI ensures that the buyer receives the right message at the right time, no matter where they interact with your brand.
- Real-Time Adjustments Across Channels: AI adjusts the message in real-time as buyers engage with your brand across different channels. If a buyer clicks an email but doesn’t convert, Make can trigger a LinkedIn ad or activate a chatbot on your site to continue the conversation seamlessly.
- Consistent Buyer Experience: AI-powered orchestration ensures that messaging remains consistent, relevant, and timely across all platforms. This cohesive experience builds trust and encourages faster decision-making.
USE CASE: Cross-Department Buyer Journey Orchestration
The buyer’s journey doesn’t end with marketing—it extends across sales, customer success, and even finance. To create a seamless, cross-functional experience, CMOs must ensure smooth and timely lead handoffs between departments. Each department must play a role in nurturing and converting prospects into long-term customers.
Where Traditional Marketing Automation Falls Short:
- Marketing-Centric Workflows: Platforms like Marketo are designed primarily for marketing, leaving gaps when it comes to coordinating efforts across sales, customer success, and operations. This often results in breakdowns when leads transition between teams.
- Manual Handoffs: Passing leads between departments often requires manual coordination, which slows down response times and can cause misalignment between teams.
- Fragmented Data: Marketo provides limited visibility into what’s happening in other departments, making it harder to create a unified customer experience across marketing, sales, and customer success.
How AI and Make Fill the Gaps:
- Seamless Cross-Department Handoffs: AI-driven automation enables seamless transitions between teams. For example, once a lead is qualified by marketing, Make can trigger notifications to sales, create tasks in customer success tools, and automate the entire handoff process in real-time.
- Unified View of the Customer Journey: AI connects data across marketing, sales, and customer success platforms, giving every department a full view of the buyer’s journey. This ensures that each team can provide personalized engagement based on the prospect’s history.
- Real-Time Task Automation: Make automates tasks across departments, such as follow-up emails, meeting scheduling, and post-sale support, ensuring that no opportunity is missed during the transition between teams.
Enhancing Buyer Journeys with AI & Automation
For visionary CMOs, the limitations of traditional marketing automation platforms like Marketo are clear. While they provide valuable email and campaign management tools, they lack the real-time agility, predictive intelligence, and cross-channel coordination needed to optimize the modern buyer journey. AI-powered platforms like Make fill these gaps, offering dynamic personalization, predictive insights, and seamless multi-channel orchestration. By integrating AI into your marketing stack, you can create enhancing Buyer Journeys with AI & Automation that are not only efficient but also optimized for revenue growth. AI enables your brand to engage with prospects in real-time, anticipate their needs, and orchestrate a cohesive experience that drives faster conversions and long-term customer loyalty.
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