Are you among 51% of companies currently using marketing automation? Well, if not, you better be, as according to Epsilon research, 80% of consumers are more likely to purchase from brands that offer personalized experiences.
First, don’t be afraid that marketing automation means replacing your marketing team. On the contrary, it’s supposed to complement their work and eliminate repetitive tasks, allowing them to focus on strategic tasks no AI can complete. Keep reading our guide to learn more about how marketing automation can be applied to your business.
What is marketing automation with data?
Marketing automation refers to integrating AI-driven marketing, customer data analytics, and automation tools to enhance the efficiency and personalization of digital marketing strategies. It involves using marketing automation software, predictive analytics, and real-time marketing analytics to automate repetitive tasks like customer service and support, email marketing, website conversion rate optimization, and audit while optimizing customer engagement.
A marketing automation system is based on collecting and analyzing data about customers, their behavior and interaction with the company’s content. It allows you to configure the sending of personalized messages, launch advertising campaigns, track results, and create reports.
Why is marketing automation essential for technology companies?
Technology companies, particularly SaaS platforms, marketplaces, and financial platforms, rely on vast data. Without an efficient marketing automation platform, managing data for lead nurturing and scoring, customer journey mapping, and retargeting can be overwhelming.
With the rise of cookieless tracking, businesses can leverage AI marketing automation, business intelligence, and big data to predict customer behavior and deliver personalized content marketing.
Key benefits of marketing automation
Companies that implement data-driven automation outline four key benefits, such as:
Efficiency: reduces manual effort by automating email marketing, PPC campaigns, SEO automation, and CRM marketing automation.
Personalization: uses dynamic content generation and omnichannel marketing to tailor campaigns based on customer lifecycle data.
Scalability: enables businesses to expand marketing efforts without increasing operational costs.
Higher ROI: AI-driven marketing automation increases customer retention and conversion rates.
Who Benefits from Marketing Automation with Data?
According to the Ascend2 trend report, 29% of the surveyed marketers plan to add automation to their social media management initiatives and paid advertising. Another 28% say they will be automating email marketing efforts.
Let’s review a few examples of tech companies and how they can benefit from data-driven marketing automation.
SAAS platforms
SaaS businesses use marketing automation tools to enhance lead scoring, manage customer data, and improve email marketing automation. They can build CDPs (customer data platforms) that combine data from multiple tools to create a single centralized customer database containing data on all touch points and interactions with your product or service. It allows them to personalize customer interactions, improving user acquisition and retention.
Marketplaces
Marketplaces rely on marketing automation software to streamline programmatic advertising and dynamic content generation. For example, programmatic advertising gives buyers relevant ad impressions in less than a second to ensure that users see relevant product recommendations and boost sales. Dynamic retargeting is another digital marketing automation tool that can be used to drive customer engagement and sales.
Digital products
Companies that offer digital products can implement AI-powered solutions to optimize conversion rates through predictive analytics. One of the marketing automation benefits for digital products is that it takes the guesswork out of CRO by identifying patterns and trends, making predictions, and generating insights.
Online retail
For retailers, tools for personalized recommendations, push notifications, and email automation play a key role in driving sales and engagement. By sending a personalized welcome, birthday, or follow-up email, customers feel special and differentiate you from other retailers. Marketing automation systems also integrate with API-driven analytics to track sales trends.
Financial platforms
Financial platforms use AI-driven customer scoring, predictive analytics, and sales funnel automation to refine their marketing automation strategy and enhance customer retention.
For additional context, you can review our Marketing Automation success stories and contact our team if you face any challenges that can be solved using data-driven automation solutions.
Examples of solutions and their business impact
AI-powered menu generation for restaurants
Restaurants often struggle to create dynamic and personalized menus that accommodate changing consumer preferences, dietary restrictions, and seasonal ingredient availability.
Content marketing automation can be used to address this issue by leveraging customer data analytics and machine learning algorithms to generate menus tailored to customer preferences and purchasing history.
Using AI, restaurants can adjust digital menus in real-time based on customer data, highlighting popular items or promoting new dishes.
How it works:
- Data Collection and Analysis: AI-powered systems analyze customer orders, feedback, and preferences from CRM systems, loyalty programs, and social media interactions.
- Personalized Menu Suggestions: Machine learning models generate menu recommendations based on past orders, seasonal trends, and regional preferences.
- Automated Content Generation: AI automates the process of updating digital menus, ensuring real-time personalization and targeted promotions.
- Integration with digital marketing automation tools: AI-generated menus can be automatically used in email marketing automation, push notifications, and PPC (pay-per-click) advertising to attract more customers.
As a result, restaurants will achieve higher customer engagement due to better personalization, boost average order value, and streamline workflow efficiency by reducing the time spent on manual menu updates.
Chargeback analysis service
Chargebacks are a significant challenge for businesses, especially in eCommerce, finance, and subscription-based services. High chargeback rates can lead to revenue losses and damage a company’s reputation with payment processors. AI-driven chargeback analysis services have the potential to revolutionize the chargeback process by providing real-time risk assessment and predicting the likelihood of chargeback disputes arising.
How it works:
- Transaction Monitoring and Risk Scoring: AI models analyze customer transaction patterns to identify any potential risks.
- Predictive Analytics: ML algorithms predict which transactions are likely to result in chargebacks, allowing businesses to take preemptive actions.
- Automated Alerts and Dispute Resolution: AI systems send real-time alerts when high-risk transactions are detected, enabling immediate intervention.
Implementing a chargeback analysis service will help companies reduce chargeback rates, speed up dispute resolution, and strengthen customer trust by improving customer service and satisfaction.
Microservices for specific business tasks
Many companies require custom automation solutions to handle specific marketing processes, such as email marketing, social media management, paid ads, content management, and campaign tracking. AI-powered microservices can be used to provide flexible and scalable automation of those processes for businesses across various industries.
Based on the Ascend2 trend report, most marketers used automation in their email marketing and social media efforts in 2023. Compared to 2022 data, there is also a notable increase in the use of automation for paid ads, content management, and landing pages.
How it works:
- API-Based Integration: businesses integrate AI-driven microservices into their existing marketing automation platforms to enhance functionality.
- Custom AI Solutions: companies can deploy no-code/low-code automation tools to handle lead scoring, predictive analytics, and CRM marketing automation.
- Data Processing and Personalization: AI-driven microservices analyze customer data to help create hyper-personalized marketing campaigns.
By automating manual tasks and using AI-powered microservices, businesses can enhance scalability and cost efficiency while creating highly personalized campaigns to boost conversion rates.
Data engineering for companies without in-house data engineers
Some companies without in-house data engineers lack the technical expertise to manage data pipelines, customer data platforms, and big data analytics. Data engineering services provide businesses with automated solutions for data optimization, storage, and real-time processing.
How it works:
- Data Pipeline Automation: AI-driven data pipelines ensure real-time data integration and processing across marketing automation systems.
- Big Data Processing and Analytics: AI models analyze large datasets to provide actionable insights for marketing strategies.
- CRM and CDP Integration: Businesses integrate AI-driven customer data platforms with CRM marketing automation software for better audience segmentation.
- Cloud-Based Data Management: AI-powered cloud computing solutions manage customer lifecycle data and predictive analytics.
Outsourcing data engineering tasks means companies without in-house data engineers can cut operational expenses and improve data accuracy for better customer segmentation.
Who needs marketing automation implementation?
Not every company realizes they need marketing automation solutions until they hit roadblocks - whether it’s data bottlenecks, inefficient lead generation, or scaling challenges. But when these issues arise, automation becomes a game-changer. Here’s who benefits the most:
If your business is dealing with unstructured data, it’s like making decisions without a clear view of what’s ahead. From database configuration issues and pipeline restoration to data management consulting needs, integrating marketing automation solutions can help. For example, data-driven marketing automation platforms centralize customer insights to make personalization easier, while AI-powered data engineering optimizes workflows, ensuring that CRM marketing automation tools get accurate, real-time data. Marketing teams can also leverage predictive analytics to forecast trends and create marketing campaigns to stand out among their competitors.
For startups, though, it’s slightly different. They grow fast, but without scalable marketing automation software for small businesses, they have limited resources and, as a consequence, limited results.
With limited resources and small teams, they can’t afford to waste time on manual lead generation, audience segmentation, and customer nurturing. That’s where marketing automation steps in:
- AI-driven audience segmentation ensures they reach the right people with personalized messaging.
- Email marketing automation nurtures leads automatically, helping turn prospects into loyal customers.
- Omnichannel marketing automation for small businesses connects social media, PPC, and content marketing efforts, making campaigns more effective.
- No-code/low-code automation tools allow startups to integrate marketing automation platforms without needing a full development team.
You can schedule a call with our marketing automation consultant to discuss how your business can implement marketing automation.
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How is marketing automation with data implemented?
Marketing automation integration isn’t a one-size-fits-all process. Some companies already have digital marketing automation in place but need AI-powered optimization, while others require a full-scale automated system from scratch. Choosing the right approach depends on your existing infrastructure, growth stage, and business goals.
Creating a new product from an existing business
For companies that already have a marketing system in place, adding ai-powered marketing automation can take things to the next level and significantly simplify workload for their teams.
Many companies start with basic digital marketing automation, using email marketing automation, CRM marketing automation, and PPC campaign optimization. But as they grow, they realize manual adjustments and limited automation capabilities are slowing them down.
Instead of replacing their entire system, they enhance it with AI-driven automation tools that:
- Use machine learning to personalize customer interactions: AI analyzes user behavior to create hyper-targeted marketing campaigns.
- Optimize marketing funnels with real-time data: marketing automation tools adjust strategies dynamically based on customer engagement patterns.
- Integrate with existing CRM marketing automation platforms.
Hypothetical situation: a SaaS company struggles with low engagement rates in email campaigns. To boost email open rates and click-through, they can implement AI-driven content personalization without changing their email marketing software.
Full development of automated solutions
For businesses that haven’t yet implemented marketing automation software, the process involves more than just choosing the right tool. It requires a strategic, data-driven approach from scratch.
A fully automated marketing system includes data pipeline integration, AI-powered predictive models, end-to-end workflow automation, and scalable infrastructure. Together, it ensures that every process is optimized, from lead generation to conversion tracking.
Hypothetical situation: a real estate marketplace needs a marketing automation system that can automatically qualify leads, trigger personalized email sequences, and provide real-time analytics. By developing a full-scale automation platform, they can reduce manual work and boost conversions without involving extra marketing staff.
Real-life project examples
At DATAFOREST, we specialize in helping businesses across different industries adopt marketing automation solutions. Let’s delve deeper into a few case studies:
Lead Generation for Real Estate
Our client requested a lead generation web application to provide the possibility to search through the U.S. real estate market and send emails to the house owners.
Real Estate Lead Generation
Stantem enables lead generation automation in the US real estate market.
DATAFOREST built the web application that features user authentication, registration, and Stripe integration. As the client needed a Fast and easy search through the high-volume database of 150 million records, we selected The ElasticSearch database as the most effective solution. As a result, users can run a 2-second search function for over 156 million objects in both lists and maps search format, including building photos via GoogleMaps integration.
Also, DATAFOREST implemented email campaign functionality with the Tiny text editor, simplifying email composition and formatting.
Beauty-matching app with Gen AI
DATAFOREST developed a Gen AI solution for an online resource client providing women with the latest hairstyles and haircuts. The client was looking to boost retention and add extra value to his project by providing an online Hairstyle try-on service and a complimentary try-on tool for his website visitors.
Gen AI Hairstyle Try-On Solution
Gen AI Hairstyle Try-On Solution
Given our experience in Gen AI and Data science, we designed a solution that resulted in 94% model accuracy, leading to high user satisfaction and making it #1 app on the market.
At the same time, DATAFOREST developed a solution that works as a marketing tool. It is a widget that offers a free trial, raising interest in trying the main product. The widget on the website offers a free try-on of 21 standard hairstyles. It also collects lead information, as users must register with their email to try the widget.
The user journey is seamlessly monitored and managed through our user-friendly admin panel, making it easy to handle support tickets. The client noted that the solution delivers the best quality results on the market.
Marketing Automation for Enterprises
As companies grow, so does the complexity of their marketing operations. Marketing automation is crucial for enterprises looking to streamline processes, improve efficiency, and drive better results. It includes using software or technology to automate, arrange, and enhance various marketing operations, tasks, or activities at the enterprise level.
When it comes to mid-sized companies with 100 to 200 employees, marketing teams often struggle with scalability and personalization. Without automation, campaigns become time-consuming, and customer engagement drops due to a lack of tailored messaging. That’s where AI-driven marketing automation solutions step in to optimize workflows, enhance segmentation, and maximize conversions. Mid-sized businesses have outgrown manual marketing processes but may not yet have a fully automated infrastructure in place. Implementing a marketing automation system enables businesses to manage complex marketing campaigns and customer interactions and lead nurturing automation activities on a larger scale.
What about Small Corporations and Physical Businesses?
While digital-first companies have been early adopters of AI-driven marketing automation, brick-and-mortar businesses, and small corporations are also recognizing the need to modernize their marketing efforts. Even businesses with a physical presence can benefit from automation tools that help them better engage customers, increase foot traffic, and boost online visibility.
Here’s how physical businesses and small companies can integrate and benefit from marketing automation services:
- Social Media Marketing Automation: AI-driven tools schedule posts, analyze engagement, and recommend optimal content for customer interaction.
- CRM-Integrated Email Automation: Automated follow-ups, customer reminders, and promotional campaigns keep businesses top-of-mind.
- Omnichannel Customer Engagement: personalized push notifications, SMS marketing, and chatbot interactions to improve customer retention.
Let’s also review marketing automation examples in specific industries like fintech, utility companies, and service companies.
Fintech: AI solutions for product personalization
In order to meet the demands of today’s consumers, fintech companies integrate AI-powered marketing automation to revolutionize customer engagement by delivering hyper-personalized financial services. It includes using predictive analytics and machine learning to analyze customer behavior, preferences, and needs, as well as their spending habits, investment preferences, and risk tolerance.
Based on these insights, companies can offer personalized financial recommendations based on transaction history, AI-driven fraud detection to prevent chargebacks and unauthorized transactions, and automated customer scoring to optimize loan approvals and interest rates.
Utility companies: Power generation and distribution optimization
For utility providers, AI-driven marketing automation can help optimize power distribution, reduce waste, and enhance customer engagement. Some of these solutions include:
- Smart grid automation that adjusts energy flow based on real-time demand
- Dynamic pricing models that personalize energy rates for different user segments
- Automated customer alerts for billing, energy-saving tips, and outage notifications
Service companies: Customer service automation
Service-based businesses are always looking to streamline the process of handling customer inquiries and automate manual tasks. Most companies integrate AI chatbots, automated workflows, and omnichannel marketing automation to streamline customer interactions and support. For example, with AI-powered chatbots they can ensure that customer service is available 24/7 for query resolution. Integrating automated appointment scheduling reduces manual booking errors and frees up agents from routine work. Also, they can use personalized email marketing automation to retain customers and drive engagement. These tools allow service companies to handle most customer interactions without direct human involvement, reducing costs and enhancing agent performance.
Specifics of marketing automation for the U.S.
According to a recent IMARC Group report, the United States marketing automation market reached $19.1 Billion in 2024. Looking forward, IMARC Group expects the market to reach $53.8 Billion by 2033. This growth results from the rising focus on strategic initiatives, creative personalized campaigns, and more robust customer relationship management.
To put it simply, more and more companies in the U.S. are implementing both B2C and B2B marketing automation. Marketing automation solutions are in high demand in the U.S. since businesses need to efficiently manage and optimize their marketing activity to keep up with competitors. These solutions automate a wide range of functions, including email marketing, social network posting, lead nurturing, campaign management, and customer segmentation. Aside from that, the U.S. marketing automation industry is distinguished by its ability to deliver tailored and targeted customer communication, considerably enhancing engagement and conversion rates. In addition to productivity savings, marketing automation agencies enable companies to optimize their marketing plans by leveraging data-driven insights and analytics. Businesses in the U.S. use these systems to track and manage leads throughout the full customer experience, making marketing automation a key aspect of the country's tech-driven marketing environment. This, in turn, is expected to influence the growth of the regional market over the forecasted period.
Leveraging AI microservices without replacing existing developers
One of the biggest concerns developers have when adopting any automation solutions is that AI will replace them. The good news? It won’t.
First of all, AI microservices are designed to support development teams and enhance their efficiency rather than eliminating the need for human expertise. It simply can’t replace software engineers as they are the ones to maintain the code and AI as well.
AI microservices handle specific tasks, such as customer segmentation, predictive analytics, or real-time personalization. Instead of requiring developers to build these capabilities from scratch, AI microservices integrate seamlessly into existing systems, allowing teams to focus on higher-priority tasks like product innovation, custom development, and system optimization.
These microservices act as tools that extend developers’ capabilities. Engineers still play a critical role in customizing, maintaining, and optimizing these solutions, ensuring they align with the company’s specific needs. With AI microservices, teams work smarter, automate repetitive tasks, and implement advanced data-driven strategies.
4 future trends in marketing automation
In 2025, AI-powered insights are replacing guesswork to help marketers predict trends and develop hyper-personalized campaigns.
1. Voice Search Optimisation to reach clients who rely on voice search for information and assistance.
2. AI-Powered Hyper-Personalization to tailor content to individual user preferences based on real-time behavioral analysis.
3. Chatbot Integration for 24/7 customer service, automating product demos and answering FAQs in real-time, enhancing sales conversions.
4. Demand forecasting and predictive analytics with artificial intelligence to identify high-value leads, forecast campaign performance, and make data-driven decisions to optimize marketing strategies and maximize ROI.
How to implement marketing automation with data in your business?
Whether you’re enhancing an existing system or building it from scratch, the right marketing automation strategy depends on your business’s needs. Regardless of where your business stands, data-driven marketing automation is no longer optional, it’s essential. Want to explore how AI-powered automation can transform your marketing efforts? Connect with DATAFOREST and our marketing automation specialist will help you find the right solution for your business.
FAQ
How can AI-driven marketing automation improve customer acquisition for SaaS platforms and digital products?
AI-driven marketing processes automation can enhance customer acquisition for these types of companies with predictive leads scoring to boost conversion rates, dynamic content recommendations, and personalized follow-ups such as emails, in-app tutorials and chatbots.
What data sources should online retailers integrate to enhance personalized marketing automation?
Our marketing automation specialist recommends online retailers integrate data sources like customer purchase history, user behavior on your website, CRM data, social media insights, and real-time inventory data to deliver hyper-personalized experiences.
How can microservices help optimize marketing automation without replacing existing developers?
AI microservices integrate seamlessly with existing systems to automate manual tasks and free up time for developers to focus on important tasks that can be automated with AI.
What are the best practices for implementing AI-based chargeback analysis in financial platforms?
To reduce chargebacks and fraud, financial platforms should use machine learning models, automate chargeback response workflows, and enhance customer verification. This approach will help identify suspicious patterns before disputes occur.
How can marketing automation improve lead generation and conversion for enterprise-level companies with physical operations?
Enterprises with physical locations can enhance lead generation by automating follow-ups based on customer visits, inquiries, or call center interactions and targeting users with location-specific offers via SMS or push notifications. Also, they can connect in-store, online, and call center data for omnichannel customer engagement.
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