Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle. #execution #gap #why #projects #dont

Requisition #: 16890 Our Mission: Powering Innovation That Drives Human Advancement When visionary companies need to know how their world-changing ideas will perform, they close the gap between design and reality with Ansys simulation. For more than 50 years, Ansys software has enabled innovators across industries to push boundaries by using the predictive power of simulation. From sustainable transportation to advanced semiconductors, from satellite systems to life-saving medical devices, the next great leaps in human advancement will be powered by Ansys. Innovate With Ansys, Power Your Career. Summary / Role Purpose The R&D Engineer II contributes to the development of software products and supporting systems. In this role, the R&D Engineer II will collaborate with a team of expert professionals to understand customer requirements and accomplish development objectives. Key Duties and Responsibilities Performs moderately complex development activities, including the design, implementation, maintenance, testing and documentation of software modules and sub-systems Understands and employs best practices Performs moderately complex bug verification, release testing and beta support for assigned products. Researches problems discovered by QA or product support and develops solutions Understands the marketing requirements for a product, including target environment, performance criteria and competitive issues Works under the general supervision of a development manager Minimum Education/Certification Requirements and Experience BS in Computer Science, Applied Mathematics, Engineering, or other natural science disciplines with 3-5 years' experience or MS with minimum 2 years experience Working experience within technical software development proven by academic, research, or industry projects. Good understanding and skills in object-oriented programming Experience with Java and C# / .NET Role can be remote, must be based on the East Coast due to timezone Preferred Qualifications and Skills Experience with C++, Python, in addition to Java and C# / .NET Knowledge of Task-Based Asynchronous design patternExposure to model-based systems engineering concepts Working knowledge of SysML Know-how on cloud computing technologies like micro-service architectures, RPC frameworks, REST APIs, etc. Knowledge of software security best practices Experience working on an Agile software development team Technical knowledge and experience with various engineering tools and methodologies, such as Finite Element simulation, CAD modeling, and Systems Architecture modelling is a plus Ability to assist more junior developers on an as-needed basis Ability to learn quickly and to collaborate with others in a geographically distributed team Excellent communication and interpersonal skills At Ansys, we know that changing the world takes vision, skill, and each other. We fuel new ideas, build relationships, and help each other realize our greatest potential. We are ONE Ansys. We operate on three key components: our commitments to stakeholders, our values that guide how we work together, and our actions to deliver results. As ONE Ansys, we are powering innovation that drives human advancement Our Commitments:Amaze with innovative products and solutionsMake our customers incredibly successfulAct with integrityEnsure employees thrive and shareholders prosper Our Values:Adaptability: Be open, welcome what's nextCourage: Be courageous, move forward passionatelyGenerosity: Be generous, share, listen, serveAuthenticity: Be you, make us stronger Our Actions:We commit to audacious goalsWe work seamlessly as a teamWe demonstrate masteryWe deliver outstanding resultsVALUES IN ACTION Ansys is committed to powering the people who power human advancement. We believe in creating and nurturing a workplace that supports and welcomes people of all backgrounds; encouraging them to bring their talents and experience to a workplace where they are valued and can thrive. Our culture is grounded in our four core values of adaptability, courage, generosity, and authenticity. Through our behaviors and actions, these values foster higher team performance and greater innovation for our customers. We're proud to offer programs, available to all employees, to further impact innovation and business outcomes, such as employee networks and learning communities that inform solutions for our globally minded customer base. WELCOME WHAT'S NEXT IN YOUR CAREER AT ANSYS At Ansys, you will find yourself among the sharpest minds and most visionary leaders across the globe. Collectively, we strive to change the world with innovative technology and transformational solutions. With a prestigious reputation in working with well-known, world-class companies, standards at Ansys are high - met by those willing to rise to the occasion and meet those challenges head on. Our team is passionate about pushing the limits of world-class simulation technology, empowering our customers to turn their design concepts into successful, innovative products faster and at a lower cost. Ready to feel inspired? Check out some of our recent customer stories, here and here . At Ansys, it's about the learning, the discovery, and the collaboration. It's about the "what's next" as much as the "mission accomplished." And it's about the melding of disciplined intellect with strategic direction and results that have, can, and do impact real people in real ways. All this is forged within a working environment built on respect, autonomy, and ethics.CREATING A PLACE WE'RE PROUD TO BEAnsys is an S&P 500 company and a member of the NASDAQ-100. We are proud to have been recognized for the following more recent awards, although our list goes on: Newsweek's Most Loved Workplace globally and in the U.S., Gold Stevie Award Winner, America's Most Responsible Companies, Fast Company World Changing Ideas, Great Place to Work Certified.For more information, please visit us at Ansys is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other protected characteristics.Ansys does not accept unsolicited referrals for vacancies, and any unsolicited referral will become the property of Ansys. Upon hire, no fee will be owed to the agency, person, or entity.Apply NowLet's start your dream job Apply now Meet JobCopilot: Your Personal AI Job HunterAutomatically Apply to Remote Full-Stack Programming JobsJust set your preferences and Job Copilot will do the rest-finding, filtering, and applying while you focus on what matters. Activate JobCopilot #ansys #rampampd #engineer #remote #east

Modern healthcare innovations span AI, devices, software, images, and regulatory frameworks, all requiring stringent coordination. Generative AI arguably has the strongest transformative potential in healthcare technology programmes, with it already being applied across various domains, such as R&D, commercial operations, and supply chain management.Traditional models for medical appointments, like face-to-face appointments, and paper-based processes may not be sufficient to meet the fast-paced, data-driven medical landscape of today. Therefore, healthcare professionals and patients are seeking more convenient and efficient ways to access and share information, meeting the complex standards of modern medical science. According to McKinsey, Medtech companies are at the forefront of healthcare innovation, estimating they could capture between billion and billion annually in productivity gains. Through GenAI adoption, an additional billion plus in revenue is estimated from products and service innovations. A McKinsey 2024 survey revealed around two thirds of Medtech executives have already implemented Gen AI, with approximately 20% scaling their solutions up and reporting substantial benefits to productivity.  While advanced technology implementation is growing across the medical industry, challenges persist. Organisations face hurdles like data integration issues, decentralised strategies, and skill gaps. Together, these highlight a need for a more streamlined approach to Gen AI deployment. Of all the Medtech domains, R&D is leading the way in Gen AI adoption. Being the most comfortable with new technologies, R&D departments use Gen AI tools to streamline work processes, such as summarising research papers or scientific articles, highlighting a grassroots adoption trend. Individual researchers are using AI to enhance productivity, even when no formal company-wide strategies are in place.While AI tools automate and accelerate R&D tasks, human review is still required to ensure final submissions are correct and satisfactory. Gen AI is proving to reduce time spent on administrative tasks for teams and improve research accuracy and depth, with some companies experiencing 20% to 30% gains in research productivity. KPIs for success in healthcare product programmesMeasuring business performance is essential in the healthcare sector. The number one goal is, of course, to deliver high-quality care, yet simultaneously maintain efficient operations. By measuring and analysing KPIs, healthcare providers are in a better position to improve patient outcomes through their data-based considerations. KPIs can also improve resource allocation, and encourage continuous improvement in all areas of care. In terms of healthcare product programmes, these structured initiatives prioritise the development, delivery, and continual optimisation of medical products. But to be a success, they require cross-functional coordination of clinical, technical, regulatory, and business teams. Time to market is critical, ensuring a product moves from the concept stage to launch as quickly as possible.Of particular note is the emphasis needing to be placed on labelling and documentation. McKinsey notes that AI-assisted labelling has resulted in a 20%-30% improvement in operational efficiency. Resource utilisation rates are also important, showing how efficiently time, budget, and/or headcount are used during the developmental stage of products. In the healthcare sector, KPIs ought to focus on several factors, including operational efficiency, patient outcomes, financial health of the business, and patient satisfaction. To achieve a comprehensive view of performance, these can be categorised into financial, operational, clinical quality, and patient experience.Bridging user experience with technical precision – design awardsInnovation is no longer solely judged by technical performance with user experiencebeing equally important. Some of the latest innovations in healthcare are recognised at the UX Design Awards, products that exemplify the best in user experience as well as technical precision. Top products prioritise the needs and experiences of both patients and healthcare professionals, also ensuring each product meets the rigorous clinical and regulatory standards of the sector. One example is the CIARTIC Move by Siemens Healthineers, a self-driving 3D C-arm imaging system that lets surgeons operate, controlling the device wirelessly in a sterile field. Computer hardware company ASUS has also received accolades for its HealthConnect App and VivoWatch Series, showcasing the fusion of AIoT-driven smart healthcare solutions with user-friendly interfaces – sometimes in what are essentially consumer devices. This demonstrates how technical innovation is being made accessible and becoming increasingly intuitive as patients gain technical fluency.  Navigating regulatory and product development pathways simultaneously The establishing of clinical and regulatory paths is important, as this enables healthcare teams to feed a twin stream of findings back into development. Gen AI adoption has become a transformative approach, automating the production and refining of complex documents, mixed data sets, and structured and unstructured data. By integrating regulatory considerations early and adopting technologies like Gen AI as part of agile practices, healthcare product programmes help teams navigate a regulatory landscape that can often shift. Baking a regulatory mindset into a team early helps ensure compliance and continued innovation. Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.Explore other upcoming enterprise technology events and webinars powered by TechForge here. #medtech #hardware #clinical #application #programmes

“Wait, can users actually add products to the cart?”Every prototype faces that question or one like it. You start to explain it’s “just Figma,” “just dummy data,” but what if you didn’t need disclaimers?What if you could hand clients—or your team—a working, data-connected mock-up of their website, or new pages and components, in less time than it takes to wireframe?That’s the challenge we’ll tackle today. But first, we need to look at:The problem with today’s prototyping toolsPick two: speed, flexibility, or interactivity.The prototyping ecosystem, despite having amazing software that addresses a huge variety of needs, doesn’t really have one tool that gives you all three.Wireframing apps let you draw boxes in minutes but every button is fake. Drag-and-drop builders animate scroll triggers until you ask for anything off-template. Custom code frees you… after you wave goodbye to a few afternoons.AI tools haven’t smashed the trade-off; they’ve just dressed it in flashier costumes. One prompt births a landing page, the next dumps a 2,000-line, worse-than-junior-level React file in your lap. The bottleneck is still there. Builder’s approach to website mockupsWe’ve been trying something a little different to maintain speed, flexibility, and interactivity while mocking full websites. Our AI-driven visual editor:Spins up a repo in seconds or connects to your existing one to use the code as design inspiration. React, Vue, Angular, and Svelte all work out of the box. Lets you shape components via plain English, visual edits, copy/pasted Figma frames, web inspos, MCP tools, and constant visual awareness of your entire website. Commits each change as a clean GitHub pull request your team can review like hand-written code. All your usual CI checks and lint rules apply.And if you need a tweak, you can comment to @builderio-bot right in the GitHub PR to make asynchronous changes without context switching.This results in a live site the café owner can interact with today, and a branch your devs can merge tomorrow. Stakeholders get to click actual buttons and trigger real state—no more “so, just imagine this works” demos.Let’s see it in action.From blank canvas to working mockup in five promptsToday, I’m going to mock up a fake business website. You’re welcome to create a real one.Before we fire off a single prompt, grab a note and write:Business name & vibe Core pages Primary goal Brand palette & toneThat’s it. Don’t sweat the details—we can always iterate. For mine, I wrote:1. Sunny Trails Bakery — family-owned, feel-good, smells like warm cinnamon. 2. Home, About, Pricing / Subscription Box, Menu. 3. Drive online orders and foot traffic—every CTA should funnel toward “Order Now” or “Reserve a Table.” 4. Warm yellow, chocolate brown, rounded typography, playful copy.We’re not trying to fit everything here. What matters is clarity on what we’re creating, so the AI has enough context to produce usable scaffolds, and so later tweaks stay aligned with the client’s vision. Builder will default to using React, Vite, and Tailwind. If you want a different JS framework, you can link an existing repo in that stack. In the near future, you won’t need to do this extra step to get non-React frameworks to function.An entire website from the first promptNow, we’re ready to get going.Head over to Builder.io and paste in this prompt or your own:Create a cozy bakery website called “Sunny Trails Bakery” with pages for: • Home • About • Pricing • Menu Brand palette: warm yellow and chocolate brown. Tone: playful, inviting. The restaurant is family-owned, feel-good, and smells like cinnamon. The goal of this site is to drive online orders and foot traffic—every CTA should funnel toward "Order Now" or "Reserve a Table."Once you hit enter, Builder will spin up a new dev container, and then inside that container, the AI will build out the first version of your site. You can leave the page and come back when it’s done.Now, before we go further, let’s create our repo, so that we get version history right from the outset. Click “Create Repo” up in the top right, and link your GitHub account.Once the process is complete, you’ll have a brand new repo.If you need any help on this step, or any of the below, check out these docs.Making the mockup’s order system workFrom our one-shot prompt, we’ve already got a really nice start for our client. However, when we press the “Order Now” button, we just get a generic alert. Let’s fix this.The best part about connecting to GitHub is that we get version control. Head back to your dashboard and edit the settings of your new project. We can give it a better name, and then, in the “Advanced” section, we can change the “Commit Mode” to “Pull Requests.”Now, we have the ability to create new branches right within Builder, allowing us to make drastic changes without worrying about the main version. This is also helpful if you’d like to show your client or team a few different versions of the same prototype.On a new branch, I’ll write another short prompt:Can you make the "Order Now" button work, even if it's just with dummy JSON for now?As you can see in the GIF above, Builder creates an ordering system and a fully mobile-responsive cart and checkout flow.Now, we can click “Send PR” in the top right, and we have an ordinary GitHub PR that can be reviewed and merged as needed.This is what’s possible in two prompts. For our third, let’s gussy up the style.If you’re like me, you might spend a lot of time admiring other people’s cool designs and learning how to code up similar components in your own style.Luckily, Builder has this capability, too, with our Chrome extension. I found a “Featured Posts” section on OpenAI’s website, where I like how the layout and scrolling work. We can copy and paste it onto our “Featured Treats” section, retaining our cafe’s distinctive brand style.Don’t worry—OpenAI doesn’t mind a little web scraping.You can do this with any component on any website, so your own projects can very quickly become a “best of the web” if you know what you’re doing.Plus, you can use Figma designs in much the same way, with even better design fidelity. Copy and paste a Figma frame with our Figma plugin, and tell the AI to either use the component as inspiration or as a 1:1 to reference for what the design should be.Now, we’re ready to send our PR. This time, let’s take a closer look at the code the AI has created.As you can see, the code is neatly formatted into two reusable components. Scrolling down further, I find a CSS file and then the actual implementation on the homepage, with clean JSON to represent the dummy post data.Design tweaks to the mockup with visual editsOne issue that cropped up when the AI brought in the OpenAI layout is that it changed my text from “Featured Treats” to “Featured Stories & Treats.” I’ve realized I don’t like either, and I want to replace that text with: “Fresh Out of the Bakery.”It would be silly, though, to prompt the AI just for this small tweak. Let’s switch into edit mode.Edit Mode lets you select any component and change any of its content or underlying CSS directly. You get a host of Webflow-like options to choose from, so that you can finesse the details as needed.Once you’ve made all the visual changes you want—maybe tweaking a button color or a border radius—you can click “Apply Edits,” and the AI will ensure the underlying code matches your repo’s style.Async fixes to the mockup with Builder BotNow, our pull request is nearly ready to merge, but I found one issue with it:When we copied the OpenAI website layout earlier, one of the blog posts had a video as its featured graphic instead of just an image. This is cool for OpenAI, but for our bakery, I just wanted images in this section. Since I didn’t instruct Builder’s AI otherwise, it went ahead and followed the layout and created extra code for video capability.No problem. We can fix this inside GItHub with our final prompt. We just need to comment on the PR and tag builderio-bot. Within about a minute, Builder Bot has successfully removed the video functionality, leaving a minimal diff that affects only the code it needed to. For example: Returning to my project in Builder, I can see that the bot’s changes are accounted for in the chat window as well, and I can use the live preview link to make sure my site works as expected:Now, if this were a real project, you could easily deploy this to the web for your client. After all, you’ve got a whole GitHub repo. This isn’t just a mockup; it’s actual code you can tweak—with Builder or Cursor or by hand—until you’re satisfied to run the site in production.So, why use Builder to mock up your website?Sure, this has been a somewhat contrived example. A real prototype is going to look prettier, because I’m going to spend more time on pieces of the design that I don’t like as much.But that’s the point of the best AI tools: they don’t take you, the human, out of the loop.You still get to make all the executive decisions, and it respects your hard work. Since you can constantly see all the code the AI creates, work in branches, and prompt with component-level precision, you can stop worrying about AI overwriting your opinions and start using it more as the tool it’s designed to be.You can copy in your team’s Figma designs, import web inspos, connect MCP servers to get Jira tickets in hand, and—most importantly—work with existing repos full of existing styles that Builder will understand and match, just like it matched OpenAI’s layout to our little cafe.So, we get speed, flexibility, and interactivity all the way from prompt to PR to production.Try Builder today. #mock #website #five #prompts

Reading Time: 9 minutes In the ever-evolving landscape of customer engagement, staying ahead of the curve is not just advantageous, it’s essential. That’s why, for Chapter 7 of “The Customer Engagement Book: Adapt or Die,” we sat down with Mirela Cialai, a seasoned expert in CRM and Martech strategies at brands like Equinox. Mirela brings a wealth of knowledge in aligning technology roadmaps with business goals, shifting organizational focuses from acquisition to retention, and leveraging hyper-personalization to drive success. In this interview, Mirela dives deep into building robust customer engagement technology roadmaps. She unveils the “PAPER” framework—Plan, Audit, Prioritize, Execute, Refine—a simple yet effective strategy for marketers. You’ll gain insights into identifying gaps in your Martech stack, ensuring data accuracy, and prioritizing initiatives that deliver the greatest impact and ROI. Whether you’re navigating data silos, striving for cross-functional alignment, or aiming for seamless tech integration, Mirela’s expertise provides practical solutions and actionable takeaways.   Mirela Cialai Q&A Interview 1. How do you define the vision for a customer engagement platform roadmap in alignment with the broader business goals? Can you share any examples of successful visions from your experience? Defining the vision for the roadmap in alignment with the broader business goals involves creating a strategic framework that connects the team’s objectives with the organization’s overarching mission or primary objectives. This could be revenue growth, customer retention, market expansion, or operational efficiency. We then break down these goals into actionable areas where the team can contribute, such as improving engagement, increasing lifetime value, or driving acquisition. We articulate how the team will support business goals by defining the KPIs that link CRM outcomes — the team’s outcomes — to business goals. In a previous role, the CRM team I was leading faced significant challenges due to the lack of attribution capabilities and a reliance on surface-level metrics such as open rates and click-through rates to measure performance. This approach made it difficult to quantify the impact of our efforts on broader business objectives such as revenue growth. Recognizing this gap, I worked on defining a vision for the CRM team to address these shortcomings. Our vision was to drive measurable growth through enhanced data accuracy and improved attribution capabilities, which allowed us to deliver targeted, data-driven, and personalized customer experiences. To bring this vision to life, I developed a roadmap that focused on first improving data accuracy, building our attribution capabilities, and delivering personalization at scale. By aligning the vision with these strategic priorities, we were able to demonstrate the tangible impact of our efforts on the key business goals. 2. What steps did you take to ensure data accuracy? The data team was very diligent in ensuring that our data warehouse had accurate data. So taking that as the source of truth, we started cleaning the data in all the other platforms that were integrated with our data warehouse — our CRM platform, our attribution analytics platform, etc. That’s where we started, looking at all the different integrations and ensuring that the data flows were correct and that we had all the right flows in place. And also validating and cleaning our email database — that helped, having more accurate data. 3. How do you recommend shifting organizational focus from acquisition to retention within a customer engagement strategy? Shifting an organization’s focus from acquisition to retention requires a cultural and strategic shift, emphasizing the immense value that existing customers bring to long-term growth and profitability. I would start by quantifying the value of retention, showcasing how retaining customers is significantly more cost-effective than acquiring new ones. Research consistently shows that increasing retention rates by just 5% can boost profits by at least 25 to 95%. This data helps make a compelling case to stakeholders about the importance of prioritizing retention. Next, I would link retention to core business goals by demonstrating how enhancing customer lifetime value and loyalty can directly drive revenue growth. This involves shifting the organization’s focus to retention-specific metrics such as churn rate, repeat purchase rate, and customer LTV. These metrics provide actionable insights into customer behaviors and highlight the financial impact of retention initiatives, ensuring alignment with the broader company objectives. By framing retention as a driver of sustainable growth, the organization can see it not as a competing priority, but as a complementary strategy to acquisition, ultimately leading to a more balanced and effective customer engagement strategy. 4. What are the key steps in analyzing a brand’s current Martech stack capabilities to identify gaps and opportunities for improvement? Developing a clear understanding of the Martech stack’s current state and ensuring it aligns with a brand’s strategic needs and future goals requires a structured and strategic approach. The process begins with defining what success looks like in terms of technology capabilities such as scalability, integration, automation, and data accessibility, and linking these capabilities directly to the brand’s broader business objectives. I start by doing an inventory of all tools currently in use, including their purpose, owner, and key functionalities, assessing if these tools are being used to their full potential or if there are features that remain unused, and reviewing how well tools integrate with one another and with our core systems, the data warehouse. Also, comparing the capabilities of each tool and results against industry standards and competitor practices and looking for missing functionalities such as personalization, omnichannel orchestration, or advanced analytics, and identifying overlapping tools that could be consolidated to save costs and streamline workflows. Finally, review the costs of the current tools against their impact on business outcomes and identify technologies that could reduce costs, increase efficiency, or deliver higher ROI through enhanced capabilities. Establish a regular review cycle for the Martech stack to ensure it evolves alongside the business and the technological landscape. 5. How do you evaluate whether a company’s tech stack can support innovative customer-focused campaigns, and what red flags should marketers look out for? I recommend taking a structured approach and first ensure there is seamless integration across all tools to support a unified customer view and data sharing across the different channels. Determine if the stack can handle increasing data volumes, larger audiences, and additional channels as the campaigns grow, and check if it supports dynamic content, behavior-based triggers, and advanced segmentation and can process and act on data in real time through emerging technologies like AI/ML predictive analytics to enable marketers to launch responsive and timely campaigns. Most importantly, we need to ensure that the stack offers robust reporting tools that provide actionable insights, allowing teams to track performance and optimize campaigns. Some of the red flags are: data silos where customer data is fragmented across platforms and not easily accessible or integrated, inability to process or respond to customer behavior in real time, a reliance on manual intervention for tasks like segmentation, data extraction, campaign deployment, and poor scalability. If the stack struggles with growing data volumes or expanding to new channels, it won’t support the company’s evolving needs. 6. What role do hyper-personalization and timely communication play in a successful customer engagement strategy? How do you ensure they’re built into the technology roadmap? Hyper-personalization and timely communication are essential components of a successful customer engagement strategy because they create meaningful, relevant, and impactful experiences that deepen the relationship with customers, enhance loyalty, and drive business outcomes. Hyper-personalization leverages data to deliver tailored content that resonates with each individual based on their preferences, behavior, or past interactions, and timely communication ensures these personalized interactions occur at the most relevant moments, which ultimately increases their impact. Customers are more likely to engage with messages that feel relevant and align with their needs, and real-time triggers such as cart abandonment or post-purchase upsells capitalize on moments when customers are most likely to convert. By embedding these capabilities into the roadmap through data integration, AI-driven insights, automation, and continuous optimization, we can deliver impactful, relevant, and timely experiences that foster deeper customer relationships and drive long-term success. 7. What’s your approach to breaking down the customer engagement technology roadmap into manageable phases? How do you prioritize the initiatives? To create a manageable roadmap, we need to divide it into distinct phases, starting with building the foundation by addressing data cleanup, system integrations, and establishing metrics, which lays the groundwork for success. Next, we can focus on early wins and quick impact by launching behavior-based campaigns, automating workflows, and improving personalization to drive immediate value. Then we can move to optimization and expansion, incorporating predictive analytics, cross-channel orchestration, and refined attribution models to enhance our capabilities. Finally, prioritize innovation and scalability, leveraging AI/ML for hyper-personalization, scaling campaigns to new markets, and ensuring the system is equipped for future growth. By starting with foundational projects, delivering quick wins, and building towards scalable innovation, we can drive measurable outcomes while maintaining our agility to adapt to evolving needs. In terms of prioritizing initiatives effectively, I would focus on projects that deliver the greatest impact on business goals, on customer experience and ROI, while we consider feasibility, urgency, and resource availability. In the past, I’ve used frameworks like Impact Effort Matrix to identify the high-impact, low-effort initiatives and ensure that the most critical projects are addressed first. 8. How do you ensure cross-functional alignment around this roadmap? What processes have worked best for you? Ensuring cross-functional alignment requires clear communication, collaborative planning, and shared accountability. We need to establish a shared understanding of the roadmap’s purpose and how it ties to the company’s overall goals by clearly articulating the “why” behind the roadmap and how each team can contribute to its success. To foster buy-in and ensure the roadmap reflects diverse perspectives and needs, we need to involve all stakeholders early on during the roadmap development and clearly outline each team’s role in executing the roadmap to ensure accountability across the different teams. To keep teams informed and aligned, we use meetings such as roadmap kickoff sessions and regular check-ins to share updates, address challenges collaboratively, and celebrate milestones together. 9. If you were to outline a simple framework for marketers to follow when building a customer engagement technology roadmap, what would it look like? A simple framework for marketers to follow when building the roadmap can be summarized in five clear steps: Plan, Audit, Prioritize, Execute, and Refine. In one word: PAPER. Here’s how it breaks down. Plan: We lay the groundwork for the roadmap by defining the CRM strategy and aligning it with the business goals. Audit: We evaluate the current state of our CRM capabilities. We conduct a comprehensive assessment of our tools, our data, the processes, and team workflows to identify any potential gaps. Prioritize: initiatives based on impact, feasibility, and ROI potential. Execute: by implementing the roadmap in manageable phases. Refine: by continuously improving CRM performance and refining the roadmap. So the PAPER framework — Plan, Audit, Prioritize, Execute, and Refine — provides a structured, iterative approach allowing marketers to create a scalable and impactful customer engagement strategy. 10. What are the most common challenges marketers face in creating or executing a customer engagement strategy, and how can they address these effectively? The most critical is when the customer data is siloed across different tools and platforms, making it very difficult to get a unified view of the customer. This limits the ability to deliver personalized and consistent experiences. The solution is to invest in tools that can centralize data from all touchpoints and ensure seamless integration between different platforms to create a single source of truth. Another challenge is the lack of clear metrics and ROI measurement and the inability to connect engagement efforts to tangible business outcomes, making it very hard to justify investment or optimize strategies. The solution for that is to define clear KPIs at the outset and use attribution models to link customer interactions to revenue and other key outcomes. Overcoming internal silos is another challenge where there is misalignment between teams, which can lead to inconsistent messaging and delayed execution. A solution to this is to foster cross-functional collaboration through shared goals, regular communication, and joint planning sessions. Besides these, other challenges marketers can face are delivering personalization at scale, keeping up with changing customer expectations, resource and budget constraints, resistance to change, and others. While creating and executing a customer engagement strategy can be challenging, these obstacles can be addressed through strategic planning, leveraging the right tools, fostering collaboration, and staying adaptable to customer needs and industry trends. By tackling these challenges proactively, marketers can deliver impactful customer-centric strategies that drive long-term success. 11. What are the top takeaways or lessons that you’ve learned from building customer engagement technology roadmaps that others should keep in mind? I would say one of the most important takeaways is to ensure that the roadmap directly supports the company’s broader objectives. Whether the focus is on retention, customer lifetime value, or revenue growth, the roadmap must bridge the gap between high-level business goals and actionable initiatives. Another important lesson: The roadmap is only as effective as the data and systems it’s built upon. I’ve learned the importance of prioritizing foundational elements like data cleanup, integrations, and governance before tackling advanced initiatives like personalization or predictive analytics. Skipping this step can lead to inefficiencies or missed opportunities later on. A Customer Engagement Roadmap is a strategic tool that evolves alongside the business and its customers. So by aligning with business goals, building a solid foundation, focusing on impact, fostering collaboration, and remaining adaptable, you can create a roadmap that delivers measurable results and meaningful customer experiences.     This interview Q&A was hosted with Mirela Cialai, Director of CRM & MarTech at Equinox, for Chapter 7 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Mirela Cialai Q&A: Customer Engagement Book Interview appeared first on MoEngage. #mirela #cialai #qampampa #customer #engagement

I recently came across an old jQuery tutorial demonstrating a “moving highlight” navigation bar and decided the concept was due for a modern upgrade. With this pattern, the border around the active navigation item animates directly from one element to another as the user clicks on menu items. In 2025, we have much better tools to manipulate the DOM via vanilla JavaScript. New features like the View Transition API make progressive enhancement more easily achievable and handle a lot of the animation minutiae.In this tutorial, I will demonstrate two methods of creating the “moving highlight” navigation bar using plain JavaScript and CSS. The first example uses the getBoundingClientRect method to explicitly animate the border between navigation bar items when they are clicked. The second example achieves the same functionality using the new View Transition API. The Initial Markup Let’s assume that we have a single-page application where content changes without the page being reloaded. The starting HTML and CSS are your standard navigation bar with an additional div element containing an id of #highlight. We give the first navigation item a class of .active. See the Pen Moving Highlight Navbar Starting Markupby Blake Lundquist. For this version, we will position the #highlight element around the element with the .active class to create a border. We can utilize absolute positioning and animate the element across the navigation bar to create the desired effect. We’ll hide it off-screen initially by adding left: -200px and include transition styles for all properties so that any changes in the position and size of the element will happen gradually. #highlight { z-index: 0; position: absolute; height: 100%; width: 100px; left: -200px; border: 2px solid green; box-sizing: border-box; transition: all 0.2s ease; } Add A Boilerplate Event Handler For Click Interactions We want the highlight element to animate when a user changes the .active navigation item. Let’s add a click event handler to the nav element, then filter for events caused only by elements matching our desired selector. In this case, we only want to change the .active nav item if the user clicks on a link that does not already have the .active class. Initially, we can call console.log to ensure the handler fires only when expected: const navbar = document.querySelector; navbar.addEventListener{ // return if the clicked element doesn't have the correct selector if')) { return; } console.log; }); Open your browser console and try clicking different items in the navigation bar. You should only see "click" being logged when you select a new item in the navigation bar. Now that we know our event handler is working on the correct elements let’s add code to move the .active class to the navigation item that was clicked. We can use the object passed into the event handler to find the element that initialized the event and give that element a class of .active after removing it from the previously active item. const navbar = document.querySelector; navbar.addEventListener{ // return if the clicked element doesn't have the correct selector if')) { return; } - console.log; + document.querySelector.classList.remove; + event.target.classList.add; }); Our #highlight element needs to move across the navigation bar and position itself around the active item. Let’s write a function to calculate a new position and width. Since the #highlight selector has transition styles applied, it will move gradually when its position changes. Using getBoundingClientRect, we can get information about the position and size of an element. We calculate the width of the active navigation item and its offset from the left boundary of the parent element. Then, we assign styles to the highlight element so that its size and position match. // handler for moving the highlight const moveHighlight ==> { const activeNavItem = document.querySelector; const highlighterElement = document.querySelector; const width = activeNavItem.offsetWidth; const itemPos = activeNavItem.getBoundingClientRect; const navbarPos = navbar.getBoundingClientRectconst relativePosX = itemPos.left - navbarPos.left; const styles = { left: ${relativePosX}px, width: ${width}px, }; Object.assign; } Let’s call our new function when the click event fires: navbar.addEventListener{ // return if the clicked element doesn't have the correct selector if')) { return; } document.querySelector.classList.remove; event.target.classList.add; + moveHighlight; }); Finally, let’s also call the function immediately so that the border moves behind our initial active item when the page first loads: // handler for moving the highlight const moveHighlight ==> { // ... } // display the highlight when the page loads moveHighlight; Now, the border moves across the navigation bar when a new item is selected. Try clicking the different navigation links to animate the navigation bar. See the Pen Moving Highlight Navbarby Blake Lundquist. That only took a few lines of vanilla JavaScript and could easily be extended to account for other interactions, like mouseover events. In the next section, we will explore refactoring this feature using the View Transition API. Using The View Transition API The View Transition API provides functionality to create animated transitions between website views. Under the hood, the API creates snapshots of “before” and “after” views and then handles transitioning between them. View transitions are useful for creating animations between documents, providing the native-app-like user experience featured in frameworks like Astro. However, the API also provides handlers meant for SPA-style applications. We will use it to reduce the JavaScript needed in our implementation and more easily create fallback functionality. For this approach, we no longer need a separate #highlight element. Instead, we can style the .active navigation item directly using pseudo-selectors and let the View Transition API handle the animation between the before-and-after UI states when a new navigation item is clicked. We’ll start by getting rid of the #highlight element and its associated CSS and replacing it with styles for the nav a::after pseudo-selector: <nav> - <div id="highlight"></div> <a href="#" class="active">Home</a> <a href="#services">Services</a> <a href="#about">About</a> <a href="#contact">Contact</a> </nav> - #highlight { - z-index: 0; - position: absolute; - height: 100%; - width: 0; - left: 0; - box-sizing: border-box; - transition: all 0.2s ease; - } + nav a::after { + content: " "; + position: absolute; + left: 0; + top: 0; + width: 100%; + height: 100%; + border: none; + box-sizing: border-box; + } For the .active class, we include the view-transition-name property, thus unlocking the magic of the View Transition API. Once we trigger the view transition and change the location of the .active navigation item in the DOM, “before” and “after” snapshots will be taken, and the browser will animate the border across the bar. We’ll give our view transition the name of highlight, but we could theoretically give it any name. nav a.active::after { border: 2px solid green; view-transition-name: highlight; } Once we have a selector that contains a view-transition-name property, the only remaining step is to trigger the transition using the startViewTransition method and pass in a callback function. const navbar = document.querySelector; // Change the active nav item on click navbar.addEventListener{ if')) { return; } document.startViewTransition=> { document.querySelector.classList.remove; event.target.classList.add; }); }); Above is a revised version of the click handler. Instead of doing all the calculations for the size and position of the moving border ourselves, the View Transition API handles all of it for us. We only need to call document.startViewTransition and pass in a callback function to change the item that has the .active class! Adjusting The View Transition At this point, when clicking on a navigation link, you’ll notice that the transition works, but some strange sizing issues are visible.This sizing inconsistency is caused by aspect ratio changes during the course of the view transition. We won’t go into detail here, but Jake Archibald has a detailed explanation you can read for more information. In short, to ensure the height of the border stays uniform throughout the transition, we need to declare an explicit height for the ::view-transition-old and ::view-transition-new pseudo-selectors representing a static snapshot of the old and new view, respectively. ::view-transition-old{ height: 100%; } ::view-transition-new{ height: 100%; } Let’s do some final refactoring to tidy up our code by moving the callback to a separate function and adding a fallback for when view transitions aren’t supported: const navbar = document.querySelector; // change the item that has the .active class applied const setActiveElement ==> { document.querySelector.classList.remove; elem.classList.add; } // Start view transition and pass in a callback on click navbar.addEventListener{ if')) { return; } // Fallback for browsers that don't support View Transitions: if{ setActiveElement; return; } document.startViewTransition=> setActiveElement); }); Here’s our view transition-powered navigation bar! Observe the smooth transition when you click on the different links. See the Pen Moving Highlight Navbar with View Transitionby Blake Lundquist. Conclusion Animations and transitions between website UI states used to require many kilobytes of external libraries, along with verbose, confusing, and error-prone code, but vanilla JavaScript and CSS have since incorporated features to achieve native-app-like interactions without breaking the bank. We demonstrated this by implementing the “moving highlight” navigation pattern using two approaches: CSS transitions combined with the getBoundingClientRectmethod and the View Transition API. Resources getBoundingClientRectmethod documentation View Transition API documentation “View Transitions: Handling Aspect Ratio Changes” by Jake Archibald #creating #ampampldquomoving #highlightampamprdquo #navigation #bar