Reading Time: 3 minutes In a recent webinar hosted by MoEngage, QSR marketing experts from Radar and Bottle Rocket came together to unpack the findings of the 2025 State of Cross-Channel Marketing for QSRs report.  With more than 800 total survey responses, including 70 from QSR marketers, this report revealed where quick-service restaurants are focusing their energy, what is holding them back, and the emerging strategies reshaping the guest experience. Here is a recap of the key takeaways, expert insights, and actionable advice shared by our panelists.   Where QSRs Are Focused in 2025: Loyalty, Personalization & Speed The webinar kicked off with a deep dive into shifting priorities. Customer engagement and loyalty emerged as the top focus for QSR marketers in 2025, with 80% of respondents increasing investment in customer experience technology. Mobile-first experiences and real-time personalization are no longer optional; they are essential for effective QSR marketing. Nick Patrick, CEO of Radar, put it simply: “Mobile has become the primary interface between QSRs and their customers. Real-time context is what makes that interface intelligent.” Challenges: Disconnected Data, Tech Silos, and Execution Speed While QSRs have the vision, many struggle with execution.  The report found that 60% of QSR leaders still struggle with personalization, and more than a quarter cited siloed data as a top challenge. The panelists echoed these findings, pointing to fragmented systems and misaligned teams as major hurdles. Brendan shared: “The POS system was designed for speed and accuracy, not personalization. But when you can use even a basic signal, like a loyalty status, to prompt a more human, high-touch experience, it makes a real difference.” Strategies That Work: Start Small, Focus Deep, Earn Trust Panelists emphasized the value of starting small with high-impact initiatives like curbside pickup or loyalty nudges. Cross-functional alignment and choosing scalable tech partners were key themes. “Don’t boil the ocean,” Brendan advised. “Start with one moment in the journey that can be improved and work cross-functionally to get it right.” Earning Location Opt-ins the Right Way Location data is a powerful lever for marketing and operations, but only if opt-ins are earned with care. Nick shared a practical framework: “It comes down to three things: transparency, value, and timing. You can’t just ask up front with no context and expect users to say yes.” He pointed to Outback Steakhouse as a standout example: “They clearly explain the value, guide users through branded screens, and then request OS-level permissions. It’s thoughtful, and it works.” AI in Action: Real Business Impact Artificial intelligence was another hot topic. Brendan shared two areas where AI is delivering real value: smarter cross-sell/upsell and feedback intelligence. “Even simple segmentation by daypart or region can lift basket size. Some tools report a 10% increase just by turning it on,” he said. “It doesn’t need to be complex to be effective.” QSR Webinar Recap: Closing Thoughts Whether optimizing app experiences, trying to unify your tech stack, automating manual processes, or building stronger loyalty loops, the advice was clear: start small, stay focused, and partner with tools and teams that can scale with you. Watch the full webinar on demand to explore these examples further and learn how MoEngage, Radar, and Bottle Rocket can help your team accelerate QSR engagement.   The post Digital Meets Dine-In: 5 Expert QSR Engagement Strategies appeared first on MoEngage.

In this Q&A, get a glimpse into the future of artificial intelligence (AI) and computer vision through the lens of longtime Unity user Gerard Espona, whose robot digital twin project was featured in the Made with Unity: AI series. Working as simulation lead at Luxonis, whose core technology makes it possible to embed human-level perception into robotics, Espona uses his years of experience in the industry to weigh in on the current state and anticipated progression of computer vision.During recent years, computer vision (CV) and AI have become the fastest-growing fields both in market size and industry adoption rate. Spatial CV and edge AI have been used to improve and automate repetitive tasks as well as complex processes.This new reality is thanks to the democratization of CV/AI. Increasingly affordable hardware access, including depth perception capability as well as improvements in machine learning (ML), has enabled the deployment of real solutions on edge CV/AI systems.Spatial CV using edge AI enables depth-based applications to be deployed without the need of a data center service, and also allows the user to preserve privacy by processing images on the device itself.Along with more accessible hardware, software and machine learning workflows are undergoing important improvements. Although they are still very specialized and full of technical challenges, they have become much more accessible, offering tools that allow users to train their own models.Within the standard ML pipeline/workflow, large-scale edge computing and deployment can still pose issues. One of the biggest general challenges is to reduce the costs and timelines currently required to create and/or improve machine learning models on real-world applications. In other words, the challenge is how to manage all these devices to enable a smooth pipeline for continuous improvement.Also, the implicit limitations in terms of compute processing need extra effort on the final model deployed on the device (that is, apps need to be lightweight, performant, etc.). That said, embedded technology evolves really fast, and each iteration is a big leap in processing capabilities.Spatial CV/AI is a field that still requires a lot of specialization and systems. Workflows are often complicated and tedious due to numerous technical challenges, so a lot of time is devoted to smoothing out the workflow instead of focusing on value-added tasks.Creating datasets (collecting and filtering images and videos), annotating the images, preprocessing/augmentation process, training, deploying and closing the feedback loop for continuous improvement is a complex process. Each step of the workflow is technically difficult and usually involves time and financial cost, and more so for systems working in remote areas with limited connectivity.At Luxonis, we help our customers build and deploy solutions to solve and automate complex tasks at scale, so we’re facing all these issues directly. Our mission, “Robotic vision made simple,” provides not only great and affordable depth-capable hardware, but also a solid and smooth ML pipeline with synthetic datasets and simulation.Another important challenge is the work that needs to be done on the interpretability of models and the creation of datasets from an ethical, privacy and bias point of view.Last but not least, global chip supply issues are making it difficult to get the hardware into everybody’s hands.Data-centric AI is potentially useful when a working model is underperforming. Investing a large amount of time to optimize the model often leads to almost zero real improvement. Instead, with data-centric AI the investment is in analysis, cleaning and improving of the dataset.Usually when a model is underperforming, the issue is within the dataset itself, as there is not enough data for the model to outperform. This could be the result of two possible reasons: 1) the model needs a much larger amount of data, which is difficult to collect in the real world, or 2) the model doesn’t have enough examples of rare cases, which take a lot of time to happen in the real world.In both situations, synthetic datasets could help.Thanks to Unity’s computer vision tools, it is very easy to create photorealistic scenes and randomize elements like materials, light conditions and object placement. The tools come with common labels like 2D bounding boxes, 3D bounding boxes, semantic and instance segmentation, and even human body key points. Additionally, these can be easily extended with custom randomizers, labelers and annotations.Almost any task you want to automate or improve using edge CV/AI very likely involves detecting people for obvious safety and security reasons. It’s critical to guarantee user safety around autonomous systems or robots when they’re working, requiring models to be trained on data about humans.That means we need to capture a large amount of images, including information like poses and physical appearance, that are representative of the entire human population. This task raises some concerns about privacy, ethics and bias when starting to capture real human data to train the model.Fortunately, we can use synthetic datasets to mitigate some of these concerns using human 3D models and poses. A very good example is the work done by the Unity team with PeopleSansPeople.PeopleSansPeople is a human-centric synthetic dataset creator using 3D models and standard animations to randomize human body poses. Also, we can use a Unity project template, to which we add our own 3D models and poses to create our own human synthetic dataset.At Luxonis, we’re using this project as the basis for creating our own human synthetic dataset and training models. In general, we use Unity’s computer vision tools to create large and complex datasets with a high level of customization on labelers, annotations and randomizations. This allows our ML team to iterate faster with our customers, without needing to wait for real-world data collection and manual annotation.Since the introduction of transformer architecture, CV tasks are more accessible. Generative models like DALL-E 2 could also be used to create synthetic datasets, and NeRF as a neural approach to generate novel point of views of known objects and scenes. It’s clear all these innovations are catching the attention of audiences.On the other hand, having access to better annotation tools and model zoos and libraries with pre-trained, ready-to-use models are helping drive wide adoption.One key element contributing to the uptick in computer vision use is the fast evolution of vision processing units (VPUs) that currently allow users to perform model inferences on device (without the need for any host) at 4 TOPS of processing power (current Intel Movidius Myriad X). The new generation of VPUs promises a big leap in capabilities, allowing even more complex CV/AI applications to be deployed on edge.Any application related to agriculture and farming always captures my attention. For example, there is now a cow tracking and monitoring CV/AI application using drones.Our thanks to Gerard for sharing his perspective with us – keep up with his latest thoughts on LinkedIn and Twitter. And, learn more about how Unity can help your team generate synthetic data to improve computer vision model training with Unity Computer Vision.

Posted on : June 3, 2025 By Tech World Times Technology  Rate this post This article walks you through five practical steps to implement network segmentation effectively, backed by real-world use cases that showcase its value in different industries. Networks are constantly expanding across offices, cloud services, remote users, and connected devices. With so many moving parts, security gaps can easily form. Once attackers breach a weak point, they often move freely across the network, targeting critical systems and sensitive data. That’s where network segmentation comes in. It’s a practical approach to divide your network into smaller, manageable zones to control access, limit exposure, and isolate threats before they spread. But simply deploying VLANs or access rules isn’t enough. True segmentation needs planning, alignment with your business, and the right mix of technology. Step 1: Assess and Map Your Current Network Start by figuring out what’s on your network and how it communicates. Inventory Devices and Applications: List all system servers, user machines, IoT devices, cloud assets. Map Data Flows: Understand how applications and services interact. Which systems talk to each other? What ports and protocols are used? Identify Critical Assets: Highlight the systems that handle sensitive data, such as payment processing, health records, or intellectual property. Tip: Network discovery tools or NAC solutions can automate asset inventory and reveal communication paths you might miss. Step 2: Define Segmentation Goals and Policies Once you understand your environment, it’s time to set your objectives. Security Objectives: Do you want to reduce lateral movement, isolate sensitive systems, or meet a compliance mandate? Business Alignment: Segment by business unit, sensitivity of data, or risk profile-whatever makes the most operational sense. Compliance Requirements: PCI DSS, HIPAA, and other standards often require network segmentation. Example: A healthcare provider might create separate zones for patient records, lab equipment, guest Wi-Fi, and billing systems. Step 3: Choose the Right Segmentation Method Segmentation can be done in several ways. The right approach depends on your infrastructure goals and types: a. Physical Segmentation Use separate routers, switches, and cables. This offers strong isolation but can be costly and harder to scale. b. Logical Segmentation (VLANs/Subnets) Group devices into virtual segments based on function or department. It’s efficient and easier to manage in most environments. c. Micro segmentation Control access at the workload or application level using software-defined policies. Ideal for cloud or virtualized environments where you need granular control. d. Cloud Segmentation In the cloud, segmentation happens using security groups, VPCs, and IAM roles to isolate workloads and define access rules. Use a combination- VLANs for broader segmentation and micro segmentation for finer control where it matters. Step 4: Implement Controls and Monitor Traffic Time to put those policies into action. Firewalls and ACLs: Use access controls to manage what can move between zones. Block anything that isn’t explicitly allowed. Zero Trust Principles: Never assume trust between segments. Always validate identity and permissions. Monitoring and Alerts: Use your SIEM, flow monitoring tools, or NDR platform to watch for unusual traffic or policy violations. Common Pitfall: Avoid “allow all” rules between segments, it defeats the purpose. Step 5: Test, Validate, and Fine-Tune Even a well-designed segmentation plan can have gaps. Regular validation helps ensure it works as expected. Penetration Testing: Simulate attacks to check if boundaries hold. Review Policies: Business needs to change your segmentation strategy too. Performance Monitoring: Make sure segmentation doesn’t impact legitimate operations or application performance. Automation tools can help simplify this process and ensure consistency. Real-World Use Cases of Network Segmentation 1. Healthcare – Protecting Patient Data and Devices Hospitals use segmentation to keep medical devices, patient records, and visitor Wi-Fi on separate zones. This prevents an infected guest device from interfering with critical systems. Result: Reduced attack surface and HIPAA compliance. 2. Manufacturing – Isolating Industrial Systems Production environments often have fragile legacy systems. Segmenting OT (Operational Technology) from IT ensures ransomware or malware doesn’t disrupt manufacturing lines. Result: More uptime and fewer operational risks. 3. Finance – Securing Payment Systems Banks and payment providers use segmentation to isolate cardholder data environments (CDE) from the rest of the corporate network. This helps meet PCI DSS and keeps sensitive data protected. Result: Easier audits and stronger data security. 4. Education – Managing High-Volume BYOD Traffic Universities segment student Wi-Fi, research labs, and administrative systems. This keeps a vulnerable student device from spreading malware to faculty or internal systems. Result: Safer environment for open access campuses. 5. Cloud – Segmenting Apps and Microservices In the cloud, developers use security groups, VPCs, and IAM roles to isolate applications and limit who can access what. This reduces risk if one workload is compromised. Result: Controlled access and better cloud hygiene. Common Challenges Legacy Tech: Older devices may not support modern segmentation. Lack of Visibility: Hard to secure what you don’t know exists. Operational Hiccups: Poorly planned segmentation can block business workflows. Policy Complexity: Keeping access rules up to date across dynamic environments takes effort. Best Practices Start with High-Risk Areas: Prioritize zones handling sensitive data or vulnerable systems. Keep Documentation Updated: Maintain clear diagrams and policy records. Align Teams: Get buy-in from IT, security, and business units. Automate Where You Can: Especially for monitoring and policy enforcement. Review Regularly: Networks evolve- so should your segmentation. Final Thoughts Segmentation isn’t about creating walls it’s about building smart pathways. Done right, it helps you take control of your network, reduce risk, and respond faster when something goes wrong. It’s a foundational layer of cybersecurity that pays off in resilience, compliance, and peace of mind. About the Author: Prajwal Gowda is a cybersecurity expert with 10+ years of experience. He has built businesses and was a Business Unit Head for Compliance and Testing services. Currently, he is the Chief Technology Officer at Ampcus Cyber, leading the company’s technology strategy and innovation efforts. He has also been involved in the Payment Card Industry, Software Security Framework, ISO 27001 Controls Gap Analysis, ISMS, Risk Analysis, OCTAVE, ISO 27005, Information Security Audit and Network Security. Prajwal is a Master Trainer who has conducted 100+ cybersecurity training sessions worldwide. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com

Scientific research across fields like chemistry, biology, and artificial intelligence has long relied on human experts to explore knowledge, generate ideas, design experiments, and refine results. Yet, as problems grow more complex and data-intensive, discovery slows. While AI tools, such as language models and robotics, can handle specific tasks, like literature searches or code analysis, they rarely encompass the entire research cycle. Bridging the gap between idea generation and experimental validation remains a key challenge. For AI to autonomously advance science, it must propose hypotheses, design and execute experiments, analyze outcomes, and refine approaches in an iterative loop. Without this integration, AI risks producing disconnected ideas that depend on human supervision for validation. Before the introduction of a unified system, researchers relied on separate tools for each stage of the process. Large language models could help find relevant scientific papers, but they didn’t directly feed into experiment design or result analysis. Robotics can assist in automating physical experiments, and coding libraries like PyTorch can help build models; however, these tools operate independently of each other. There was no single system capable of handling the entire process, from forming ideas to verifying them through experiments. This led to bottlenecks, where researchers had to connect the dots manually, slowing progress and leaving room for errors or missed opportunities. The need for an integrated system that could handle the entire research cycle became clear. Researchers from the NovelSeek Team at the Shanghai Artificial Intelligence Laboratory developed NovelSeek, an AI system designed to run the entire scientific discovery process autonomously. NovelSeek comprises four main modules that work in tandem: a system that generates and refines research ideas, a feedback loop where human experts can interact with and refine these ideas, a method for translating ideas into code and experiment plans, and a process for conducting multiple rounds of experiments. What makes NovelSeek stand out is its versatility; it works across 12 scientific research tasks, including predicting chemical reaction yields, understanding molecular dynamics, forecasting time-series data, and handling functions like 2D semantic segmentation and 3D object classification. The team designed NovelSeek to minimize human involvement, expedite discoveries, and deliver consistent, high-quality results. The system behind NovelSeek involves multiple specialized agents, each focused on a specific part of the research workflow. The “Survey Agent” helps the system understand the problem by searching scientific papers and identifying relevant information based on keywords and task definitions. It adapts its search strategy by first doing a broad survey of papers, then going deeper by analyzing full-text documents for detailed insights. This ensures that the system captures both general trends and specific technical knowledge. The “Code Review Agent” examines existing codebases, whether user-uploaded or sourced from public repositories like GitHub, to understand how current methods work and identify areas for improvement. It checks how code is structured, looks for errors, and creates summaries that help the system build on past work. The “Idea Innovation Agent” generates creative research ideas, pushing the system to explore different approaches and refine them by comparing them to related studies and previous results. The system even includes a “Planning and Execution Agent” that turns ideas into detailed experiments, handles errors during the testing process, and ensures smooth execution of multi-step research plans. NovelSeek delivered impressive results across various tasks. In chemical reaction yield prediction, NovelSeek improved performance from a baseline of 24.2% (with a variation of ±4.2) to 34.8% (with a much smaller variation of ±1.1) in just 12 hours, progress that human researchers typically need months to achieve. In enhancer activity prediction, a key task in biology, NovelSeek raised the Pearson correlation coefficient from 0.65 to 0.79 within 4 hours. For 2D semantic segmentation, a task used in computer vision, precision improved from 78.8% to 81.0% in just 30 hours. These performance boosts, achieved in a fraction of the time typically needed, highlight the system’s efficiency. NovelSeek also successfully managed large, complex codebases with multiple files, demonstrating its ability to handle research tasks at a project level, not just in small, isolated tests. The team has made the code open-source, allowing others to use, test, and contribute to its improvement. Several Key Takeaways from the Research on NovelSeek include: NovelSeek supports 12 research tasks, including chemical reaction prediction, molecular dynamics, and 3D object classification. Reaction yield prediction accuracy improved from 24.2% to 34.8% in 12 hours. Enhancer activity prediction performance increased from 0.65 to 0.79 in 4 hours. 2D semantic segmentation precision improved from 78.8% to 81.0% in 30 hours. NovelSeek includes agents for literature search, code analysis, idea generation, and experiment execution. The system is open-source, enabling reproducibility and collaboration across scientific fields. In conclusion, NovelSeek demonstrates how combining AI tools into a single system can accelerate scientific discovery and reduce its dependence on human effort. It ties together the key steps, generating ideas, turning them into methods, and testing them through experiments, into one streamlined process. What once took researchers months or years can now be done in days or even hours. By linking every stage of research into a continuous loop, NovelSeek helps teams move from rough ideas to real-world results more quickly. This system highlights the power of AI not just to assist, but to drive scientific research in a way that could reshape how discoveries are made across many fields. Check out the Paper and GitHub Page . All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 95k+ ML SubReddit and Subscribe to our Newsletter. NikhilNikhil is an intern consultant at Marktechpost. He is pursuing an integrated dual degree in Materials at the Indian Institute of Technology, Kharagpur. Nikhil is an AI/ML enthusiast who is always researching applications in fields like biomaterials and biomedical science. With a strong background in Material Science, he is exploring new advancements and creating opportunities to contribute.Nikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces ARM and Ada-GRPO: Adaptive Reasoning Models for Efficient and Scalable Problem-SolvingNikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces WEB-SHEPHERD: A Process Reward Model for Web Agents with 40K Dataset and 10× Cost EfficiencyNikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces MMaDA: A Unified Multimodal Diffusion Model for Textual Reasoning, Visual Understanding, and Image GenerationNikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces Differentiable MCMC Layers: A New AI Framework for Learning with Inexact Combinatorial Solvers in Neural Networks

Reading Time: 11 minutes Choosing the right drip email software can be a game-changer for your marketing strategy. With a variety of options available, understanding the pricing models and features each tool offers is key to making an informed decision. In this guide, we’ll walk you through essential factors to consider when evaluating pricing, so you can select the best solution that fits your needs and budget for your drip email campaigns. Ready to dive deeper? Let’s explore your options.   What Does Drip Email Marketing Software Cost? Drip email marketing software typically follows a few different pricing models, depending on the provider. Here’s a quick breakdown of the most common ones: Pricing Based on MAUs (Monthly Active Users): You pay based on how many unique subscribers actually engage with your emails (or your system) each month, not your entire list size. It’s a much fairer, scalable way to pay, especially if your audience fluctuates. You only pay for real activity. Flat-Rate Pricing: You pay a fixed monthly fee, regardless of usage, list size, or activity. But flat rates are often bloated to cover all usage types, so you’re likely overpaying if you’re not sending a massive volume of emails. It’s not cost-efficient for scaling brands. List-Based Pricing: You pay based on the total number of contacts in your database, whether they engage or not. However, you end up paying for cold leads, dead emails, and inactive contacts. This makes your costs climb unnecessarily as your list grows. Email Volume-Based Pricing: You’re charged based on how many emails you send each month. It can discourage you from running important nurturing campaigns or re-engagement flows because every email adds to your bill. It’s unpredictable and can spike costs during promotions. For email marketers, this model means added pressure to limit sends, often at the cost of customer experience and long-term engagement. Some platforms even bundle unnecessary features into expensive tiers, which bloats the pricing, especially for features you may not actually need. This is where MoEngage stands out. The platform offers a more transparent and scalable approach so that pricing is aligned to your actual usage and outcomes rather than inflated send limits.   6 Biggest Factors that Affect Drip Email Pricing Drip email pricing depends on several factors. Here are some of the biggest ones: 1. Number of active contacts Some platforms, particularly the ones that use the MAU pricing model, charge based on the number of customers who interact with your emails. The higher the number of active customers, the higher the pricing. 2. List size Managing an email list is easier said than done. Nevertheless, if you have a large database of contacts, you will be charged a higher monthly fee. In this case, pricing will remain the same even if you don’t have many active subscribers on your list. 3. Email volume The number of emails you send plays a big role in pricing. This is because high-volume automated email marketing campaigns require significant infrastructure for email delivery, tracking, and reporting. 4. Advanced features Platforms offering advanced features like RFM segmentation, automation, A/B testing, analytics, and AI-driven personalization typically charge more than others. Some pricing models allow you to opt for some or all of these features, depending on your business requirements. 5. Automation complexity If your drip campaign involves complex workflows, like different stages, conditions, triggers, etc., it can impact the pricing. Automation requires more resources to set up and maintain, which increases the price. 6. Integration with other tools Connecting your email platform with CRMs, Ecommerce tools, or analytics systems can drive up costs, especially if platforms charge extra for native integrations or require third-party connectors. Before signing up, ask yourself: how many of these tools are truly essential? Can any be replaced with ones that integrate more easily? A cluttered tech stack not only costs more but also complicates your workflows.   Top Features to Look For in a Drip Email Marketing Software Since you’re on the lookout for a drip email marketing software platform, focus on the features we’ve mentioned below. Core features that drip email software absolutely needs These features are the must-haves. They are the foundational tools required to automate, personalize, and optimize your email drip campaigns at scale. Journey designer: Easily set up multi-step workflows triggered by parameters like customer actions, behaviors, or time delays with minimal coding. Behavioral targeting: Send emails based on real-time customer behavior, such as cart additions, subscriptions, app activity, and more, for highly relevant messaging. Personalization engine: Dynamically include customer attributes based on past interactions and preferences to personalize emails at scale. High inbox deliverability: Tools and practices that ensure you have a healthy sender reputation and high inbox placement. Campaign optimization with A/B testing: Test different email versions to learn what drives higher engagement and optimize your drip flows continuously. Real-time analytics and insights: Access detailed reports and dashboards that track key drip email marketing metrics like opens, clicks, and conversions, and identify drop-offs in your drip journeys. Other features that are very useful to have These features aren’t absolutely necessary to run an effective campaign, but they can improve customer experience and operational efficiency. AI-based predictive segmentation: Leverage AI to predict customer behavior like churn or likelihood of conversion, and automatically adjust campaigns accordingly. Omnichannel messaging: Integrate messaging across various channels, like push notifications, SMS, WhatsApp, and in-app messaging for a cohesive customer journey. Pre-built templates: Quickly access pre-built, customizable email templates to launch campaigns faster without heavy design work.   9 Steps to Choosing a Drip Email Marketing Software With so many options available in the market, choosing the right drip email marketing software can seem like an uphill battle. No worries! We’ll even walk you through exactly how to evaluate and compare drip email tools for yourself. Once you’ve asked the right questions and gathered the facts during demos, it’s time to break down your decision-making process into clear, actionable steps. Step 1: Define Your Non-Negotiable Features The first step is to make a list of all the features that are necessary for you. For example, if your goal is to send behavior-triggered drip campaigns (like abandoned cart emails or re-engagement nudges), then features like behavioral targeting and multi-step customer journey automation are non-negotiable. On the other hand, if you only need basic scheduled newsletters, you might not need advanced workflow builders or AI recommendations. Once you have a list of non-negotiable features, it becomes easier to narrow down your platform choices. Step 2: Research and Compare All Viable Options Don’t just go with the most well-known or even the most affordable-looking tool. Research platforms that fit your business size and industry. Use peer reviews, comparison guides, and case studies to understand how the platform performs in real-world use cases. Also, remember that low entry pricing can be misleading. What matters is the total cost of ownership. Look for things like hidden fees, integration costs, or feature-based tier upgrades. These will add to the pricing later. Step 3: Book a Personalized Demo (and Demand Proof) When choosing your drip email marketing tool, make sure you request a personalized demo based on your business context, use cases, and workflows. A simple, generic walkthrough isn’t helpful because this is your first real glimpse into how the platform is going to support you long-term. If the demo isn’t tailored to your business, that’s a red flag—because if they can’t offer personalized attention when they’re trying to win your business, you’re unlikely to get it during onboarding or implementation. Ask to see features live, rather than just screenshots or slide decks. If a feature is critical, ask to see it in action. At times, sales teams may promise features that are still ‘in development’. Step 4: Attend the Demo with a List of Questions Once you’ve booked a demo, prepare a checklist of questions, like the one we shared above. This will help you stay focused and gain the clarity you need. Ask whether the features you care about are included in the base plan or locked behind premium tiers. Dig into pricing: will the costs scale predictably as you grow, or are there hidden fees that only show up later? Some platforms may offer attractive deals upfront but raise prices later or charge extra for essentials like API access, automation workflows, or deliverability support. The demo is your chance to surface all of this before signing anything. Step 5: Evaluate Ease of Use The drip email software you choose must be easy to use. Since marketers with little to no technical knowledge are most likely to use the platform, look for solutions that allow you to build email campaigns, segment audiences, and personalize messages easily. Say no to complicated or clunky interfaces that are not intuitive and require a steep learning curve. Step 6: Check for Advanced Capabilities Ask about AI features like predictive segmentation or email send-time optimization. Even if you don’t need them right now, having future-ready capabilities ensures you won’t outgrow the tool too soon. Step 7: Test for Scalability and Deliverability This is an important one. Look for solutions that can handle large volumes of emails with good email deliverability rates. Make sure the software you choose has a high inbox placement rate. Check if they have a solid infrastructure and dedicated IPs, should you need them. Also, consider scalability: will this platform still meet your needs when your contact list grows from 10,000 to 100,000? Make sure you’re not locked into expensive pricing jumps or performance bottlenecks. Step 8: Review Integration Options Make sure the tool you choose fits seamlessly into your existing workflow. It should integrate with your CRM, mobile app, Ecommerce system, and anything else in your ecosystem. Even if it doesn’t directly integrate, ensure that it offers flexible APIs and webhooks, or supports third-party connectors like Zapier, so you can still automate data flow without manual workarounds. Step 9: Compare Customer Support Quality Good software with bad support can be a nightmare. Check for onboarding help, technical support, availability, account management, and resources. Ask about how quickly the support team responds and resolves software issues to ensure that you have minimal downtime.   5 Best Email Drip Campaign Software and Tools It’s time to weigh your options in choosing an email drip campaign software for your business. Give this list a quick read! 1. MoEngage: Best for Omnichannel Engagement and Behavioral Targeting   MoEngage is a comprehensive customer engagement platform designed to deliver personalized and automated drip email campaigns at scale. Its powerful AI capabilities allow you to use behavioral targeting to reach customers at the right time with the right message at different stages of their customer journey. Why MoEngage is Best for Omnichannel Engagement and Behavioral Targeting: MoEngage offers multiple features that allow you to provide cohesive customer experiences across various touchpoints. You can reach out to customers via not just email, but also SMS, push notifications, in-app messages, and even ad networks without missing a beat. Features like advanced segmentation enable you to send hyper-personalized drip email campaigns tailored to individual customer actions, such as cart abandonment or inactivity. This ensures that messages are timely, relevant, and effective in driving engagement. How Pricing Works: MoEngage offers flexible drip email pricing based on the scale of your business and the exact features you’d need. You can always reach out to their sales team to learn more about their custom pricing plans. How to Set Up a Demo: To experience MoEngage firsthand, you need to book a demo first. Their team will then contact you to schedule a personalized walkthrough that showcases how the platform can meet your specific drip email marketing goals. 2. ActiveCampaign: Best for Email and Marketing Automation ActiveCampaign is a marketing automation platform that allows you to create email campaigns on channels your customers connect with. The platform offers predictive content features that help you show customers the most meaningful content. Why ActiveCampaign is Best for Email and Marketing Automation: ActiveCampaign excels in delivering sophisticated automation campaign workflows that can be tailored to various customer journeys. How Pricing Works: ActiveCampaign offers a four-tiered drip email pricing plan. The basic plan starts at $15/month for 1K contacts, while the Enterprise plan starts at $1,169/month for 50K contacts. If you have contacts upwards of that number, you need to talk to their sales team. 3. Kit: Best for Creators Using Emails Kit is tailored for creators, bloggers, and solo entrepreneurs who want to send customer relationship emails. It offers a user-friendly interface with powerful automation capabilities. Why Kit is Best for Creators and Solo Entrepreneurs: Kit’s email-first operating system allows creators to build long-term connections with customers. Its intuitive email designer can be used to create effective on-brand emails that are optimized for deliverability. Plus, it allows you to send email broadcasts for announcing product launches, sharing content updates, or promoting limited-time offers to your entire list in bulk. How Pricing Works: Kit offers a free Newsletter plan with basic features like visual automation, opt-in forms, and email broadcasts to up to 10K subscribers. But you can implement just 1 visual automation and an email sequence on the free plan. Advanced plans start at $25 per month for up to 1K subscribers, and go up to $2,166/month for 400K contacts. 4. Drip: Best for Ecommerce Marketing Automation Drip is a marketing automation platform designed specifically for Ecommerce brands. It offers tools to create personalized email campaigns that drive customer engagement and sales. Why Drip is Best for Ecommerce Marketing Automation: Drip provides deep integrations with Ecommerce platforms, allowing businesses to leverage customer data for targeted campaigns. Features like behavior-based automation and pre-built workflows help in crafting effective drip campaigns. How Pricing Works: Drip’s pricing starts at $39/month for up to 2,500 contacts. The cost scales up to $1,999/month based on the number of contacts, with custom pricing available for larger lists of over 180K subscribers. 5. Mailmodo: Best for Interactive Email Marketing Mailmodo is an email marketing platform that enables the creation of interactive drip emails using AMP technology. This allows recipients to take actions like filling out forms or booking appointments directly within the email. Why Mailmodo is Best for Interactive Email Marketing: Mailmodo stands out by offering interactive email capabilities that enhance customer engagement and conversion rates. Its drag-and-drop editor simplifies the creation of dynamic emails without any coding required. How Pricing Works: Like the other drip email marketing software on this list, Mailmodo’s pricing is based on the number of contacts and emails sent per month. Its three-tiered pricing model starts at $39/month for 500 contacts, going up to $939/month for 250K subscribers. Any more contacts, and you have to reach out to their sales team.   How to Get the Most Value Out of Your Drip Email Software Here are some of the ways in which you can leverage your drip email software to its maximum potential. Save time through automation: Automate welcome emails, follow-ups, and re-engagement campaigns to free up your team for more strategic work. Boost engagement with timely messaging: Set up triggers so that emails are automatically sent based on customers’ actions. This keeps your audience interested at every stage of their customer journey. Drive higher conversions with targeted sequences: Send the right email at the right time to move leads through the sales funnel towards a conversion. Personalize customer experiences at scale: Use segmentation and dynamic content to create a personalized customer experience without manually customizing every email. Continuously optimize with data-driven insights: Track performance metrics like open rates and conversions to refine your drip email campaigns and maximize results over time.   Maximize Engagement With MoEngage’s Drip Email Marketing Software To sum it up, drip email marketing can be quite powerful for engaging customers at different stages of their journey. Having the right drip email software in your tech stack ensures smooth, efficient workflows. Your team can focus on higher-value tasks while automating routine processes. It also ensures that your drip emails always reach the right person with the right message at the perfect time. MoEngage’s powerful email automation platform allows you to automate personalized campaigns that drive higher engagement and conversions. With advanced segmentation, behavior-triggered messaging, and seamless integration with your ecosystem, you can nurture relationships more effectively than ever. Curious to see how MoEngage can elevate your campaigns? Schedule a discovery call today. The post Drip Email Software: The Ultimate Pricing and Buying Guide appeared first on MoEngage.

Michael Giannou, Global General Manager, HoneywellMay 29, 20254 Min ReadAndriy Popov via Alamy StockData centers are quickly becoming the backbone of our information-driven world. At the same time, the increasing sophistication of cybersecurity attacks, combined with the growing frequency of extreme climate events, means there is also greater operational risk than ever before, as bad actors have begun targeting cooling centers to purposefully compromise the equipment, causing irreversible loss and damage.  The best defense against these threats is an integrated system centered around situational awareness and security. By taking steps to safeguard key areas, data center operators can enhance the protection of their facility and data, helping prevent costly threats and downtime.  Seeing the Big Picture Developing a comprehensive awareness and monitoring system serves as a critical first step to protecting data centers. This is especially important as data centers begin to welcome more tenants into shared space, requiring vendors to consider each tenant individually and as part of the broader system. A threat to one tenant can quickly become a threat to all tenants. Centralizing all information in one system provides a single location for operators to view and analyze real-time data, allowing them to instantly access critical information, monitor incidents and respond quickly with pre-defined incident workflows. An intelligent system will integrate all security events -- including video recordings, access point clearance and data reporting -- together in one place to reduce coverage gaps and information silos.  Related:Another benefit of having one comprehensive system is the ability to integrate separate aspects of the system to improve response time. For example, a centralized security system could be configured to ensure that any fire or intruder alarm immediately triggers the CCTV cameras in the vicinity of the alarm, so the security team can quickly and efficiently respond to the situation. Close partnering between systems that transcend departments such as security, IT and the management of employees, contractors and visitors is key to protecting the facility and its data, both in low-friction (e.g. office space) and high-friction (e.g. server space) areas.  Addressing the Gaps Once a centralized security system is in place, operators can address the cybersecurity gaps where the data center is most vulnerable to bad actors. A strong, always-on cybersecurity program should be tailored to the specific facility and its compliance needs, often including:  Data encryption: Whether data is stored in the system or just passing through, encryption is key to preventing unauthorized access. A strong encryption process goes beyond thwarting attacks -- it is critical for establishing trust, ensuring the authenticity of data exchanged, guaranteeing the integrity of commands to smart devices and maintaining secrecy where it is needed most.  Related:Network security: Data center operators can help prevent unauthorized access and cyberattacks by developing strong intrusion detection/prevention systems, firewalls and network segmentation. Facility protection: By integrating technologies such as electronic access control, biometrics, CCTV and perimeter detection, operators can maintain security around the physical facility. Security also requires vendors to adhere to standard operating procedures, often overlooked in today’s technology-focused environment, such as enforcing visitor security policies and requiring visitors to have escorts.  Regular audits and updates: It may seem to be a lower priority than the often-urgent concerns set forth above, but out-of-date firmware carries a significant cybersecurity risk. Proactive attention and system maintenance can reduce operating costs in the long run and help avoid costly downtime. Related:Looking Ahead With so many current considerations to focus on, data center operators must also look ahead to future-proof their facility. As quickly as the industry has grown in recent years, the momentum will likely continue to accelerate. One new frontier emerging is quantum security: using quantum-enhanced randomness to deliver truly unpredictable key generation and safeguard sensitive information. This enables the system to develop armor that evolves just as quickly as cybersecurity threats. As the largest companies make significant investment in data centers -- for example, Microsoft’s plan to invest approximately $80 billion in AI-enabled datacenters in FY25 -- many in the industry are watching to see how these companies’ actions and investments shape the future of both data centers and building security overall.  Another forward-looking trend is military-grade solutions entering the commercial and industrial marketplace. It is clear to understand how a system hardened for integrated perimeter security in harsh environments can also fit the security and resilience needs of a data center. In addition, those solutions have often been certified through rigorous testing and evaluation, giving operators confidence their system can withstand almost all third-party attacks.  Finally, the industry will begin to prioritize modularity -- meaning systems that can be added to in the future, will work with third-party solutions and are both user-friendly and energy-efficient. This allows operators to expand their facilities to include the latest and greatest technology without a costly overhaul of their existing infrastructure. By integrating with their business systems and leaning into wider stakeholder influence, organizations can more effectively monitor and manage their facilities using modular systems. Cybersecurity risks can never truly be considered resolved -- it is constantly evolving. But by continuously revisiting the areas detailed above, data center operators can enhance their facility and systems protections, helping to protect their data now and in the future.  About the AuthorMichael GiannouGlobal General Manager, HoneywellMichael Giannou is a global sales executive with over 15 years of experience leading high-performing teams and driving growth in the data center and technology sectors. As Global General Manager of Data Centers at Honeywell, he built and led a global sales team, delivering double-digit growth and now leads the company’s global data center vertical. Previously, at Schneider Electric, he grew division sales from $70M to $350M over six years. Known for transforming underperforming programs and developing trusted customer relationships, Michael is a strategic, growth-focused leader passionate about mentoring enterprise sales professionals.  See more from Michael GiannouWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

Michael Giannou, Global General Manager, HoneywellMay 29, 20254 Min ReadAndriy Popov via Alamy StockData centers are quickly becoming the backbone of our information-driven world. At the same time, the increasing sophistication of cybersecurity attacks, combined with the growing frequency of extreme climate events, means there is also greater operational risk than ever before, as bad actors have begun targeting cooling centers to purposefully compromise the equipment, causing irreversible loss and damage.  The best defense against these threats is an integrated system centered around situational awareness and security. By taking steps to safeguard key areas, data center operators can enhance the protection of their facility and data, helping prevent costly threats and downtime.  Seeing the Big Picture Developing a comprehensive awareness and monitoring system serves as a critical first step to protecting data centers. This is especially important as data centers begin to welcome more tenants into shared space, requiring vendors to consider each tenant individually and as part of the broader system. A threat to one tenant can quickly become a threat to all tenants. Centralizing all information in one system provides a single location for operators to view and analyze real-time data, allowing them to instantly access critical information, monitor incidents and respond quickly with pre-defined incident workflows. An intelligent system will integrate all security events -- including video recordings, access point clearance and data reporting -- together in one place to reduce coverage gaps and information silos.  Related:Another benefit of having one comprehensive system is the ability to integrate separate aspects of the system to improve response time. For example, a centralized security system could be configured to ensure that any fire or intruder alarm immediately triggers the CCTV cameras in the vicinity of the alarm, so the security team can quickly and efficiently respond to the situation. Close partnering between systems that transcend departments such as security, IT and the management of employees, contractors and visitors is key to protecting the facility and its data, both in low-friction (e.g. office space) and high-friction (e.g. server space) areas.  Addressing the Gaps Once a centralized security system is in place, operators can address the cybersecurity gaps where the data center is most vulnerable to bad actors. A strong, always-on cybersecurity program should be tailored to the specific facility and its compliance needs, often including:  Data encryption: Whether data is stored in the system or just passing through, encryption is key to preventing unauthorized access. A strong encryption process goes beyond thwarting attacks -- it is critical for establishing trust, ensuring the authenticity of data exchanged, guaranteeing the integrity of commands to smart devices and maintaining secrecy where it is needed most.  Related:Network security: Data center operators can help prevent unauthorized access and cyberattacks by developing strong intrusion detection/prevention systems, firewalls and network segmentation. Facility protection: By integrating technologies such as electronic access control, biometrics, CCTV and perimeter detection, operators can maintain security around the physical facility. Security also requires vendors to adhere to standard operating procedures, often overlooked in today’s technology-focused environment, such as enforcing visitor security policies and requiring visitors to have escorts.  Regular audits and updates: It may seem to be a lower priority than the often-urgent concerns set forth above, but out-of-date firmware carries a significant cybersecurity risk. Proactive attention and system maintenance can reduce operating costs in the long run and help avoid costly downtime. Related:Looking Ahead With so many current considerations to focus on, data center operators must also look ahead to future-proof their facility. As quickly as the industry has grown in recent years, the momentum will likely continue to accelerate. One new frontier emerging is quantum security: using quantum-enhanced randomness to deliver truly unpredictable key generation and safeguard sensitive information. This enables the system to develop armor that evolves just as quickly as cybersecurity threats. As the largest companies make significant investment in data centers -- for example, Microsoft’s plan to invest approximately $80 billion in AI-enabled datacenters in FY25 -- many in the industry are watching to see how these companies’ actions and investments shape the future of both data centers and building security overall.  Another forward-looking trend is military-grade solutions entering the commercial and industrial marketplace. It is clear to understand how a system hardened for integrated perimeter security in harsh environments can also fit the security and resilience needs of a data center. In addition, those solutions have often been certified through rigorous testing and evaluation, giving operators confidence their system can withstand almost all third-party attacks.  Finally, the industry will begin to prioritize modularity -- meaning systems that can be added to in the future, will work with third-party solutions and are both user-friendly and energy-efficient. This allows operators to expand their facilities to include the latest and greatest technology without a costly overhaul of their existing infrastructure. By integrating with their business systems and leaning into wider stakeholder influence, organizations can more effectively monitor and manage their facilities using modular systems. Cybersecurity risks can never truly be considered resolved -- it is constantly evolving. But by continuously revisiting the areas detailed above, data center operators can enhance their facility and systems protections, helping to protect their data now and in the future.  About the AuthorMichael GiannouGlobal General Manager, HoneywellMichael Giannou is a global sales executive with over 15 years of experience leading high-performing teams and driving growth in the data center and technology sectors. As Global General Manager of Data Centers at Honeywell, he built and led a global sales team, delivering double-digit growth and now leads the company’s global data center vertical. Previously, at Schneider Electric, he grew division sales from $70M to $350M over six years. Known for transforming underperforming programs and developing trusted customer relationships, Michael is a strategic, growth-focused leader passionate about mentoring enterprise sales professionals.  See more from Michael GiannouWebinarsMore WebinarsReportsMore ReportsNever Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.SIGN-UPYou May Also Like

On this episode of the fxpodcast, we have an exclusive behind-the-scenes look at the visual effects work for Amazon’s Étoile, featuring an in-depth discussion with David Gaddie from Afterparty VFX. The team undertook the challenging face replacement work for the show’s ballet dancers, employing cutting-edge AI technology to seamlessly blend lead actors’ faces onto the performances of professional dance doubles. Étoile, the latest series from Amy Sherman-Palladino, renowned creator of The Marvelous Mrs. Maisel and Gilmore Girls, centers on elite ballet dancers. To realize this vision, the show’s VFX supervisor, Lesley Robson Foster, engaged Afterparty VFX to research and develop innovative AI-driven solutions capable of handling the demanding visual complexities inherent in ballet sequences. This task was notably difficult, as traditional deepfake tools are typically optimized for straightforward, frontal shots. Ballet, however, involves rapid spinning, flips, significant motion blur, and hair frequently obscuring faces, creating immense technical hurdles. Additionally, director Amy Sherman-Palladino preferred long, uninterrupted takes, some lasting nearly a full minute, eliminating conventional editing methods and cheats used to mask transitions between the actors and their dance doubles. Crucially, the final shots needed to authentically reflect the actors’ performances, rather than simply showcasing their doubles. In this episode, we explore in-depth how David Gaddie and the Afterparty VFX team developed proprietary solutions tailored specifically to these unique challenges. Their process combined computer-generated imagery, advanced AI, meticulous data segmentation, extensive manual refinements, and significant artistic skill to achieve convincing, performance-driven visual effects.

Reading Time: 8 minutes Sometimes, even the slickest emails can land with a thud in the spam folder. The culprit? Your email sender reputation. Just like a bank checks your credit history before lending you money, mailbox providers (like Gmail, Yahoo, etc.) check your sender reputation before deciding whether to deliver your customer relationship emails to the inbox or banish them to spam. So buckle up, because here, we’re about to unpack everything you need to know about what an email domain reputation is and how to keep yours squeaky clean. Now, you’re probably wondering…   What is Email Sender Reputation? Email sender reputation, also known as email domain reputation, is a measure of your brand’s trustworthiness as an email sender. It’s based on factors like your sending history, email engagement, and complaint rates, influencing whether mailbox providers deliver your messages to recipients’ inboxes or junk folders. A solid sender reputation is the golden ticket to inbox placement. Without it, your carefully crafted automated email marketing campaigns might as well be shouting into the void. Mailbox providers are constantly on the lookout for spammers and shady senders, and your reputation is a key indicator of whether you’re one of the good guys. But how do they know that?   5 Factors That Influence Email Marketing Sender Reputation Your email sending reputation isn’t built overnight; it’s a result of consistent behavior and several critical factors. Let’s break down the big five: 1. Quality of Your Email List Building your email list is hard, we know. But honestly, validating it to ensure that all email addresses are real and belong to existing subscribers helps you maintain a positive sender reputation score with mailbox providers. This is why you should use a proper email validation API, as it can help you quickly check if the email addresses are legitimate. Your reputation score can suffer if you’re labeled as a bad email sender, with all the bounces you get from a bad email list. 2. Email Sending History Having an established history with a particular IP address can boost the legitimacy and reputation score of your emails, which means the sender, messages, and recipients are all coming from a legitimate place. Spammers will often change IP addresses and, therefore, cannot establish a long and reputable sending history with IPs. 3. Consistency and Volume of Emails The number of emails you send and your consistency in sending them are also indicators of your legitimacy and reputation. Sending two emails every other week, for example, shows stability and predictability in terms of your sending volume and activities. Mailbox providers and Internet Service Providers (ISPs) also examine your sending patterns and frequency to determine whether you’re still on the right track or have turned to spamming. 4. Email Open Rates or Engagement This is a metric that records subscriber activity or your email engagement, such as the open or click-through rates. It’s very significant because mailbox providers value their subscribers’ preferences. Your emails could be filtered out if there is a very low response rate or no interactions at all. 5. Emails Marked as ‘SPAM’ Mailbox providers would take a cue from their subscribers’ preferences whenever they receive emails. So, if your email messages are consistently marked as ‘Spam’, then this feedback would result in your emails being screened or placed in the Spam or Junk folder. And that’s not where you’d want your emails to hang out.   How to Check Email Sender Reputation You can verify your email domain reputation by monitoring key metrics and using reputation checking tools. Many email marketing software platforms (like MoEngage, for example) provide dashboards and analytics that help you monitor these crucial indicators. MoEngage goes a step further by offering insights and tools to help you proactively manage and improve your email deliverability, making it easier to spot and address potential reputation issues before they escalate. In fact, you can achieve an inbox placement rate of over 95%! Coming back to the topic, the platform indicates email domain reputation as High, Medium, Low, or Bad. More specifically, it lets you: Filter campaigns based on reputation while exporting their data. See historical trends in your domain reputation. View more information, such as when the reputation information was last updated. Analyze email marketing metrics, like open rates and click-through rates. How an Email Sender Reputation Score Works Your email sender reputation score is a dynamic rating that mailbox providers assign to your sending domain and IP address. This score isn’t a fixed number, but rather, a constantly evolving assessment based on your list quality, sending history, and other factors we’ve discussed above. Higher scores generally mean better inbox placement, while lower scores can lead to the dreaded spam folder. Different mailbox providers have their own algorithms for calculating this score, and the exact formulas are usually kept secret. However, the underlying principles revolve around your sending behavior and recipient engagement. How Can You Do a Domain Reputation Test and How Often Should You Do This? You can run an email domain reputation test using various software tools (we’ll get to some of the best ones in a sec!). These reputation checkers analyze your domain and IP address against known blacklists and provide insights into your current standing. Ideally, you should be monitoring your key metrics within your ESP regularly (daily or weekly) and perform a more comprehensive domain reputation test at least monthly, or more frequently if you’re experiencing deliverability issues. Consistent monitoring helps you catch problems early and maintain a healthy reputation.   3 Best Email Domain Reputation Checkers Alright, let’s talk tools. While your ESP often provides built-in deliverability insights, these external domain reputation checkers can offer another layer of perspective. Let’s jump right in! 1. MoEngage Okay, we might be a little biased, but hear us out. MoEngage is more than just an email marketing platform; it’s a powerhouse for cross-channel customer engagement. Its robust analytics and deliverability features give you a clear view of your email performance, helping you proactively manage your email sender reputation. MoEngage stands out because it integrates domain reputation monitoring with tools to improve engagement and personalize your campaigns, leading to better deliverability in the long run. Unlike some standalone domain reputation checkers, MoEngage provides actionable insights within your workflow. How Pricing Works: MoEngage offers customized pricing plans based on your specific needs and scale. Contact the sales team for a personalized quote. Best For: Brands looking for an integrated customer engagement platform (CEP) with robust email deliverability management capabilities. 2. Spamhaus Project The Spamhaus Project allows you to track spam, malware, phishing, and other cybersecurity threats. ISPs and email servers filter out unwanted and harmful content using Spamhaus’s DNS-based blocklists (DNSBLs). How Pricing Works: Spamhaus provides its blacklist data and lookup tools for free to most users, as part of their mission to combat spam. Best For: Quickly checking if your domain or IP is on major spam blacklists. 3. MxToolbox You can use MxToolbox to check if your domain is mentioned on any email blocklists. It scans your domain for mail servers, DNS records, web servers, and any problems. While comprehensive in its checks, this domain reputation checker doesn’t provide the same level of integrated deliverability management and analytics that a platform like MoEngage offers. How Pricing Works: MxToolbox offers both free tools and paid subscription plans with more advanced features, with pricing starting from around $85 per month. Best For: Performing a broad check across numerous email blacklists.   How to Improve Your Email Domain Reputation So, your domain email reputation doesn’t look as shiny as you’d like? No worries! Here are concrete steps you can take to improve it. Think of it as spring cleaning for your email sending practices. 1. Manage a Clean Email List Email list management is foundational. Regularly prune inactive subscribers, remove bounced addresses, and promptly honor unsubscribe requests. Implement a double opt-in process to ensure subscribers genuinely want to hear from you. A clean, engaged email list signals to mailbox providers that you’re sending to interested recipients, and reduces bounce rates and spam complaints. It’s crucial for a positive email sender reputation score. 2. Send Confirmation Emails with Double Opt-Ins Include double opt-ins where you send automated confirmation emails to subscribers. This helps you distinguish valid email addresses from nonexistent ones. Basically, protecting your email sender reputation is easy when you adhere to best practices. Ensuring that your email messages are engaging and interesting helps you get more clicks and open rates. Attracting more interaction to your email messages sends a signal to mailbox providers that you have a legitimate and professional organization. Increasing the positive activities and reviews will help build and solidify your branding strategy, sending a message that is relatable and understood by your subscribers. 3. Pause Violating Campaigns Notice a sudden spike in bounces or spam complaints after a particular email marketing campaign? Pause the campaign immediately to investigate the cause. Ideally, you should not send transactional and non-transactional emails from the same domain (domain/IP set). If the compliance requirements are met, there is no need to pause transactional emails. However, you should pause all one-time emails. Continuing to send problematic emails will only further damage your email sending reputation. Addressing the issue swiftly demonstrates responsibility to mailbox providers. 4. Correct the Mistakes Once you’ve paused a problematic campaign, take the time to understand what went wrong. Did you use a purchased list? Was the content or subject line misleading? (In which case, you need to have a list of the best email subject lines handy). Identify the root cause and implement corrective measures so it doesn’t happen again. Showing that you learn from your mistakes helps rebuild trust with mailbox providers over time. Then, raise a ticket to Gmail or other ESP explaining the cause behind the reputation issues, your changes, and the next steps you plan to follow. Have checkpoints to detect issues immediately, so you can always stay on top of them. 5. Use Subdomains for Sending Emails Establish a subdomain you’re going to use only for sending emails to customers. That’s because if anything goes wrong, the subdomain will take the hit directly, while mildly affecting your company’s main registered domain. It’s like a backup. Also, hopefully, your customers will remember and recognize your subdomain with time. So even if your emails do land in the spam folder, customers might mark them as ‘Not spam’. Yay! 6. Resume and Ramp Up Your Email Frequency After addressing the issues and making necessary changes, don’t be afraid to resume sending. But take baby steps. Resume your transactional emails first. Don’t send transactional and promotional emails from the same domains and IPs. If you already have, separate them while correcting your email setup. Next, resume your personalized event-triggered campaigns. Then, slowly send one-time campaigns to email openers and clickers (such as emails that have been opened 5 times in the last 60 days). Send at a lower RPM and send only 2-3 campaigns per week. After the email domain reputation improves, gradually increase the overall sending frequency and volume (it could take 6-8 weeks). When emailing non-engaged customers, slowly raise your email frequency to prevent sudden volume spikes from triggering spam filters. This careful approach communicates to mailbox providers that you are a responsible sender. 7. Customize Your Sending Patterns Avoid sending all your emails at the same time to everyone on your list. Segment your audience and tailor your sending schedules based on their engagement and time zones. This shows mailbox providers that you’re sending relevant content to the right customers at the right time, improving engagement and your overall email marketing domain reputation. Create lifecycle campaigns to engage your customers. Use dynamic segments, so inactive customers get dropped off automatically. Implement personalization across every aspect of your email.   Maintaining Email Domain Reputation with MoEngage Maintaining a stellar email domain reputation is an ongoing effort, but it doesn’t have to be complicated. Hundreds of B2C brands trust MoEngage to provide the insights and tools they need to monitor deliverability, understand audience engagement, and proactively manage their sending practices. By leveraging the platform’s analytics and segmentation capabilities, our customers can be sure their emails consistently land in the inbox, where they belong. Ready to take control of your email deliverability and build a rock-solid email sender reputation? Explore MoEngage’s comprehensive email marketing solutions. Or better yet, request a demo to see MoEngage’s email solutions in action today. The post How to Check and Fix Your Email Sender Reputation appeared first on MoEngage.