Financial institutions are at a pivotal moment. As customer expectations evolve and AI reshapes digital engagement, leaders in marketing, CX, and IT must rethink how they deliver value.

Adobe’s report, “State of Customer Experience in Financial Services in an AI-Driven World,” reveals that only 36% of the customer journey is currently personalized, despite 74% of executives acknowledging rising customer expectations. With transformation already underway, financial leaders face five imperatives that demand immediate action to drive relevance, trust, and growth.

1. Make Personalization More Meaningful

Personalization has long been a strategic focus, but today’s consumers expect more than basic segmentation or name-based greetings. They want real-time, omnichannel interactions that align with their financial goals, life stages, and behaviors.

To meet this demand, financial institutions must evolve from reactive personalization to predictive, intent-driven engagement. This means leveraging AI to anticipate needs, orchestrate journeys, and deliver content that resonates with individual context.

Perficient Adobe-consulting principal Ross Monaghan explains, “We are still dealing with disparate data and slow progression into a customer 360 source of truth view to provide effective personalization at scale. What many firms are overlooking is that this isn’t just a data issue. We’re dealing with both a people and process issue where teams need to adjust their operational process of typical campaign waterfall execution to trigger-based and journey personalization.”

His point underscores that personalization challenges go beyond technology. They require cultural and operational shifts to enable real-time, AI-driven engagement.

2. Redesign the Operating Model Around the Customer

Legacy structures often silo marketing, IT, and operations, creating friction in delivering cohesive customer experiences. To compete in a digital-first world, financial institutions must reorient their operating models around the customer, not the org chart.

This shift requires cross-functional collaboration, agile workflows, and shared KPIs that align teams around customer outcomes. It also demands a culture that embraces experimentation and continuous improvement.

Only 3% of financial services firms are structured around the customer journey, though 19% say it should be the ideal.

3. Build Content for AI-Powered Search

As AI-powered search becomes a primary interface for information discovery, the way content is created and structured must change. Traditional SEO strategies are no longer enough.

Customers now expect intelligent, personalized answers over static search results. To stay visible and trusted, financial institutions must create structured, metadata-rich content that performs in AI-powered environments. Content must reflect experience-expertise-authoritativeness-trustworthiness principles and be both machine-readable and human-relevant. Success depends on building discovery journeys that work across AI interfaces while earning customer confidence in moments that matter.

4. Unify Data and Platforms for Scalable Intelligence

Disconnected data and fragmented platforms limit the ability to generate insights and act on them at scale. To unlock the full potential of AI and automation, financial institutions must unify their data ecosystems.

This means integrating customer, behavioral, transactional, and operational data into a single source of truth that’s accessible across teams and systems. It also involves modernizing MarTech and CX platforms to support real-time decisioning and personalization.

But Ross points out, “Many digital experience and marketing platforms still want to own all data, which is just not realistic, both in reality and cost. The firms that develop their customer source of truth (typically cloud-based data platforms) and signal to other experience or service platforms will be the quickest to marketing execution maturity and success.”

His insight emphasizes that success depends not only on technology integration but also on adopting a federated approach that accelerates marketing execution and operational maturity.

5. Embed Guardrails Into GenAI Execution

As financial institutions explore GenAI use cases, from content generation to customer service automation, governance must be built in from the start. Trust is non-negotiable in financial services, and GenAI introduces new risks around accuracy, bias, and compliance.

Embedding guardrails means establishing clear policies, human-in-the-loop review processes, and robust monitoring systems. It also requires collaboration between legal, compliance, marketing, and IT to ensure responsible innovation.

At Perficient, we use our PACE (Policies, Advocacy, Controls, Enablement) Framework to holistically design tailored operational AI programs that empower business and technical stakeholders to innovate with confidence while mitigating risks and upholding ethical standards.

The Time to Lead is Now

The future of financial services will be defined by how intelligently and responsibly institutions engage in real time. These five imperatives offer a blueprint for action, each one grounded in data, urgency, and opportunity. Leaders who move now will be best positioned to earn trust, drive growth, and lead in the AI-powered era.

Learn About Perficient and Adobe’s Partnership

Are you looking for a partner to help you transform and modernize your technology strategy? Perficient and Adobe bring together deep industry expertise and powerful experience technologies to help financial institutions unify data, orchestrate journeys, and deliver customer-centric experiences that build trust and drive growth.

Get in Touch With Our Experts

I think about the early ATMs now and then. No one knew the “right” way to use them. I imagine a customer in the 1970s standing there, card in hand, squinting at this unfamiliar machine and hoping it would give something back; trying to decide if it really dispensed cash…or just ate cards for sport. That quick panic when the machine pulled the card in is an early version of the same confusion customers feel today in digital banking.

People were not afraid of machines. They were afraid of not understanding what the machine was doing with their money.

Banks solved it by teaching people how to trust the process. They added clear instructions, trained staff to guide customers, and repeated the same steps until the unfamiliar felt intuitive. 

However, the stakes and complexity are much higher now, and AI for financial product transparency is becoming essential to an optimized banking UX.

Today’s banking customer must navigate automated underwriting, digital identity checks, algorithmic risk models, hybrid blockchain components, and disclosures written in a language most people never use. Meanwhile, the average person is still struggling with basic money concepts.

FINRA reports that only 37% of U.S. adults can answer four out of five financial literacy questions (FINRA Foundation, 2022).

Pew Research finds that only about half of Americans understand key concepts like inflation and interest (Pew Research Center, 2024).

Financial institutions are starting to realize that clarity is not a content task or a customer service perk. It is structural. It affects conversion, compliance, risk, and trust. It shapes the entire digital experience. And AI is accelerating the pressure to treat clarity as infrastructure.

When customers don’t understand, they don’t convert. When they feel unsure, they abandon the flow. 

How AI is Improving UX in Banking (And Why Institutions Need it Now)

Financial institutions often assume customers will “figure it out.” They will Google a term, reread a disclosure, or call support if something is unclear. In reality, most customers simply exit the flow.

The CFPB shows that lower financial literacy leads to more mistakes, higher confusion, and weaker decision-making (CFPB, 2019). And when that confusion arises during a digital journey, customers quietly leave without resolving their questions.

This means every abandoned application costs money. Every misinterpreted term creates operational drag. Every unclear disclosure becomes a compliance liability. Institutions consistently point to misunderstanding as a major driver of complaints, errors, and churn (Lusardi et al., 2020).

Sometimes it feels like the industry built the digital bank faster than it built the explanation for it.

Where AI Makes the Difference

Many discussions about AI in financial services focus on automation or chatbots, but the real opportunity lies in real-time clarity. Clarity that improves financial product transparency and streamlines customer experience without creating extra steps.

In-context Explanations That Improve Understanding

Research in educational psychology shows people learn best when information appears the moment they need it. Mayer (2019) demonstrates that in-context explanations significantly boost comprehension. Instead of leaving the app to search unfamiliar terms, customers receive a clear, human explanation on the spot.

Consistency Across Channels

Language in banking is surprisingly inconsistent. Apps, websites, advisors, and support teams all use slightly different terms. Capgemini identifies cross-channel inconsistency as a major cause of digital frustration (Capgemini, 2023). A unified AI knowledge layer solves this by standardizing definitions across the system.

Predictive Clarity Powered by Behavioral Insight

Patterns like hesitation, backtracking, rapid clicking, or form abandonment often signal confusion. Behavioral economists note these patterns can predict drop-off before it happens (Loibl et al., 2021). AI can flag these friction points and help institutions fix them.

24/7 Clarity, Not 9–5 Support

Accenture reports that most digital banking interactions now occur outside of business hours (Accenture, 2023). AI allows institutions to provide accurate, transparent explanations anytime, without relying solely on support teams.

At its core, AI doesn’t simplify financial products. It translates them.

What Strong AI-Powered Customer Experience Looks Like

Onboarding that Explains Itself

• Mortgage flows with one-sentence escrow definitions.
• Credit card applications with visual explanations of usage.
  
• Hybrid products that show exactly what blockchain is doing behind the scenes. The CFPB shows that simpler, clearer formats directly improve decision quality (CFPB, 2020).

A Unified Dictionary Across Channels

The Federal Reserve emphasizes the importance of consistent terminology to help consumers make informed decisions (Federal Reserve Board, 2021). Some institutions now maintain a centralized term library that powers their entire ecosystem, creating a cohesive experience instead of fragmented messaging.

Personalization Based on User Behavior

Educational nudges, simplified paths, multilingual explanations. Research shows these interventions boost customer confidence (Kozup & Hogarth, 2008). 

Transparent Explanations for Hybrid or Blockchain-backed Products

Customers adopt new technology faster when they understand the mechanics behind it (University of Cambridge, 2021). AI can make complex automation and decentralized components understandable.

The Urgent Responsibilities That Come With This

GenAI can mislead customers without strong data governance and oversight. Poor training data, inconsistent terminology, or unmonitored AI systems create clarity gaps. That’s a problem because those gaps can become compliance issues. The Financial Stability Oversight Council warns that unmanaged AI introduces systemic risk (FSOC, 2023). The CFPB also emphasizes the need for compliant, accurate AI-generated content (CFPB, 2024).

Customers are also increasingly wary of data usage and privacy. Pew Research shows growing fear around how financial institutions use personal data (Pew Research Center, 2023). Trust requires transparency.

Clarity without governance is not clarity. It’s noise.

And institutions cannot afford noise.

What Institutions Should Build Right Now

To make clarity foundational to customer experience, financial institutions need to invest in:

• Modern data pipelines to improve accuracy
• Consistent terminology and UX layers across channels
• Responsible AI frameworks with human oversight
• Cross-functional collaboration between compliance, design, product, and analytics
• Scalable architecture for automated and decentralized product components
• Human-plus-AI support models that enhance, not replace, advisors

When clarity becomes structural, trust becomes scalable.

Why This Moment Matters

I keep coming back to the ATM because it perfectly shows what happens when technology outruns customer understanding. The machine wasn’t the problem. The knowledge gap was. Financial services are reliving that moment today.

Customers cannot trust what they do not understand.

And institutions cannot scale what customers do not trust.

GenAI gives financial organizations a second chance to rebuild the clarity layer the industry has lacked for decades, and not as marketing. Clarity, in this new landscape, truly is infrastructure.

Related Reading

• The Personalization Gap Is Hurting Financial Services, Here’s How to Close It: A discussion of how personalization shortfalls are holding back financial services from meeting customer expectations. 

• Closing the Gap Between Expectations and Experience in Financial Services: Analysis of rising customer expectations and why legacy systems struggle to keep up. 

• Trust Is the New Currency in Financial Services and Customers Are Setting the Terms: A look at how trust, speed, transparency, and control are reshaping what customers expect from their institutions. 

References 

• Accenture. (2023). Banking top trends 2023. https://www.accenture.com
• Capgemini. (2023). World retail banking report 2023. https://www.capgemini.com
• Consumer Financial Protection Bureau. (2019). Financial well-being in America. https://www.consumerfinance.gov
• Consumer Financial Protection Bureau. (2020). Improving the clarity of mortgage disclosures. https://www.consumerfinance.gov
• Consumer Financial Protection Bureau. (2024). Supervisory highlights: Issue 30. https://www.consumerfinance.gov
• Federal Reserve Board. (2021). Consumers and mobile financial services. https://www.federalreserve.gov
• FINRA Investor Education Foundation. (2022). National financial capability study. https://www.finrafoundation.org
• Financial Stability Oversight Council. (2023). Annual report. https://home.treasury.gov
• Kozup, J., & Hogarth, J. (2008). Financial literacy, public policy, and consumers’ self-protection. Journal of Consumer Affairs, 42(2), 263–270.
• Loibl, C., Grinstein-Weiss, M., & Koeninger, J. (2021). Consumer financial behavior in digital environments. Journal of Economic Psychology, 87, 102438.
• Lusardi, A., Mitchell, O. S., & Oggero, N. (2020). The changing face of financial literacy. University of Pennsylvania, Wharton School.
• Mayer, R. (2019). The Cambridge handbook of multimedia learning. Cambridge University Press.
• Pew Research Center. (2023). Americans and data privacy. https://www.pewresearch.org
• Pew Research Center. (2024). Americans and financial knowledge. https://www.pewresearch.org
• University of Cambridge. (2021). Global blockchain benchmarking study. https://www.jbs.cam.ac.uk

Sitecore has introduced the Content SDK for XM Cloud-now Sitecore AI to streamline the process of fetching content and rendering it on modern JavaScript front-end applications. If you’re building a website on Sitecore AI, the new Content SDK is the modern, recommended tool for your development team.

Think of it as a specialized, lightweight toolkit built for one specific job: getting content from Sitecore AI and displaying it on your modern frontend application (like a site built with Next.js).

Because it’s purpose-built for Sitecore AI, it’s fast, efficient, and doesn’t include a lot of extra baggage. It focuses purely on the essential “headless” task of fetching and rendering content.

What About the JSS SDK?
This is the original toolkit Sitecore created for headless development.

The key difference is that the JSS SDK was designed to be a one-size-fits-all solution. It had to support both the new, headless Sitecore AI and Sitecore’s older, all-in-one platform, Sitecore XP/XM.

To do this, it had to include extra code and dependencies to support older features, like the “Experience Editor”. This makes the JSS SDK “bulkier” and more complex. If you’re only using Sitecore AI, you’re carrying around a lot of extra weight you simply don’t need.

The Sitecore Content SDK is the modern, purpose-built toolkit for developers using Sitecore AI, providing seamless, out-of-the-box integration with the platform’s most powerful capabilities. This includes seamless visual editing that empowers marketers to build and edit pages in real-time, as well as built-in hooks for personalization and analytics that simplify the delivery and tracking of targeted user experiences. For developers, it provides GraphQL utilities to streamline data fetching and is deeply optimized for Next.js, enabling high-performance features like server-side rendering. Furthermore, with the recent introduction of App Router support (in beta), the SDK is evolving to give developers even more granular control over performance, SEO, bundle sizes, and security through a more modern, modular code structure.

What does the Content SDK offer?

1) App Router support (v1.2)

With version 1.2.0, Sitecore Content SDK introduces App Router support in beta. While the full fledged stable release is expected soon, developers can already start exploring its benefits and work flow with 1.2 version.
This isn’t just a minor update; it’s a huge step toward making your front-end development more flexible and highly optimized.

Why should you care? –
The App Router introduces a fantastic change to your starter application’s code structure and how routing works. Everything becomes more modular and declarative, aligning perfectly with modern architecture practices. This means defining routes and layouts is cleaner, content fetching is neatly separated from rendering, and integrating complex Next.js features like dynamic routes is easier than ever. Ultimately, this shift makes your applications much simpler to scale and maintain as they grow on Sitecore AI.

Performance: Developers can fine-tune route handling with nested layouts and more aggressive and granular caching to seriously boost overall performance, leading to faster load times.

Bundle Size: Smaller bundle size because it uses React Server Components (RSC) to render components. It help fetch and render component from server side without making the static files in bundle.

Security: It helps with security by giving improved control over access to specific routes and content.

With the starter kit applications, this is how app router routing structure looks like:

2) New configs – sitecore.config.ts & sitecore.cli.config.ts

The sitecore.config.ts file, located in the root of your application, acts as the central configuration point for Content SDK projects. It is replacement of the older temp/config file used by the JSS SDK. It contains properties that can be used throughout the application just by importing the file. It contains important properties like sitename, defaultLanguage, edge props like contextid. Starter templates include a very lightweight version containing only the mandatory parameters necessary to get started. Developers can easily extend this file as the project grows and requires more specific settings.

Key Aspects:

Environment Variable Support: This file is designed for deployment flexibility using a layered approach. Any configuration property present in this file can be sourced in three ways, listed in order of priority:

1. Explicitly defined in the configuration file itself.
2. Fallback to a corresponding environment variable (ideal for deployment pipelines).
3. Use a default value if neither of the above is provided.

This layered approach ensures flexibility and simplifies deployment across environments.

The sitecore.cli.config.ts file is dedicated to defining and configuring the commands and scripts used during the development and build phases of a Content SDK project.

Key Aspects:

CLI Command Configuration: It dictates the commands that execute as part of the build process, such as generateMetadata() and generateSites(), which are essential for generating Sitecore-related data and metadata for the front-end.

Component Map Generation: This file manages the configuration for the automatic component map generation. This process is crucial for telling Sitecore how your front-end components map to the content structure, allowing you to specify file paths to scan and define any files or folders to exclude. Explored further below.

Customization of Build Process: It allows developers to customize the Content SDK’s standard build process by adding their own custom commands or scripts to be executed during compilation.

While sitecore.config.ts handles the application’s runtime settings (like connection details to Sitecore AI), sitecore.cli.config.ts works in conjunction to handle the development-time configuration required to prepare the application for deployment.

3) Component map

In Sitecore Content SDK-based applications, every custom component must be manually registered in the .sitecore/component-map.ts file located in the app’s root. The component map is a registry that explicitly links Sitecore renderings to their corresponding frontend component implementations. The component map tells the Content SDK which frontend component to render for each component receives from Sitecore. When the rendering gets added to any page via presentation, component map tells which frontend rendering should be rendered at the place.

Key Aspects:

Unlike JSS implementations that automatically maps components, the Content SDK’s explicit component map enables better tree-shaking. Your final production bundle will only include the components you have actually registered and use, resulting in smaller, more efficient application sizes.

This is how it looks like: (Once you start creating custom component, you have to add the component name here to register.)

4) Import map

The import map is a tool used specifically by the Content SDK’s code generation feature. It manages the import paths of components that are generated or used during the build process. It acts as a guide for the code generation engine, ensuring that any new code it creates correctly references your existing components.
Where it is: It is a generated file, typically found at ./sitecore/import-map.ts, that serves as an internal manifest for the build process. You generally do not need to edit this file manually.
It simplifies the logic of code generation, guaranteeing that any newly created code correctly and consistently references your existing component modules.

The import map generation process is configurable via the sitecore.cli.config.ts file. This allows developers to customize the directories scanned for components.

5) defineMiddleware in the Sitecore Content SDK

defineMiddleware is a utility for composing a middleware chain in your Next.js app. It gives you a clean, declarative way to handle cross-cutting concerns like multi-site routing, personalization, redirects, and security all in one place. This centralization aligns perfectly with modern best practices for building scalable, maintainable functions.

The JSS SDK leverages a “middleware plugin” pattern. This system is effective for its time, allowing logic to be separated into distinct files. However, this separation often requires developers to manually manage the ordering and chaining of multiple files, which could become complex and less transparent as the application grew. The Content SDK streamlines this process by moving the composition logic into a single, highly readable utility which can customizable easily by extending Middleware

6) Debug Logging in Sitecore Content SDK

Debug logging helps you see what the SDK is doing under the hood. Super useful for troubleshooting layout/dictionary fetches, multisite routing, redirects, personalization, and more. The Content SDK uses the standard DEBUG environment variable pattern to enable logging by namespace. You can selectively turn on logging for only the areas you need to troubleshoot, such as: content-sdk:layout (for layout service details) or content-sdk:dictionary (for dictionary service details)
For all available namespaces and parameters, refer to sitecore doc – https://doc.sitecore.com/sai/en/developers/content-sdk/debug-logging-in-content-sdk-apps.html#namespaces 

7) Editing & Preview

In the context of Sitecore’s development platform, editing and preview render optimization with the Content SDK involves leveraging middleware, architecture, and framework-specific features to improve the performance of rendering content in editing and preview modes. The primary goal is to provide a fast and responsive editing experience for marketers using tools like Sitecore AI Pages and the Design Library. EditingRenderMiddleware: The Content SDK for Next.js includes optimized middleware for editing scenarios. Instead of a multi-step process involving redirects, the optimized middleware performs an internal, server-side request to return the HTML directly. This reduces overhead and speeds up rendering significantly.
This feature Works out of the box in most environments: Local container, Vercel / Netlify, SitecoreAI (defaults to localhost as configured)

For custom setups, override the internal host with: SITECORE_INTERNAL_EDITING_HOST_URL=https://host
This leverages a Integration with XM Cloud/Sitecore AI Pages for visual editing and testing of components.

8) SitecoreClient

The SitecoreClient class in the Sitecore Content SDK is a centralized data-fetching service that simplifies communication with your Sitecore content backend typically with Experience Edge or preview endpoint via GraphQL endpoints.
Instead of calling multiple services separately, SitecoreClient lets you make one organized request to fetch everything needed for a page layout, dictionary, redirects, personalization, and more.

Key Aspect:

Unified API: One client to access layout, dictionary, sitemap, robots.txt, redirects, error pages, multi-site, and personalization.
To understand all key methods supported, please refer to sitecore documentation: https://doc.sitecore.com/sai/en/developers/content-sdk/the-sitecoreclient-api.html#key-methods

9) Built-In Capabilities for Modern Web Experiences

GraphQL Utilities: Easily fetch content, layout, dictionary entries, and site info from Sitecore AI’s Edge and Preview endpoints.
Personalization & A/B/n Testing: Deploy multiple page or component variants to different audience segments (e.g., by time zone or language) with no custom code.
Multi-site Support: Seamlessly manage and serve content across multiple independent sites from a single Sitecore AI instance.
Analytics & Event Tracking: Integrated support via the Sitecore Cloud SDK for capturing user behavior and performance metrics.
Framework-Specific Features: Includes Next.js locale-based routing for internationalization, and supports both SSR and SSG for flexible rendering strategies.

10) Cursor for AI development

Starting with Content SDK version 1.1, Sitecore has provided comprehensive “Cursor rules” to facilitate AI-powered development.
The integration provides Cursor with sufficient context about the Content SDK ecosystem and Sitecore development patterns. These set of rules and context helps to accelerate the development. The cursor rules are created for contentsdk with starter application under .cursor folder. This enables the AI to better assist developers with tasks specific to building headless Sitecore components, leading to improved development consistency and speed following same patterns just by providing few commands in generic terms. Example given in below screenshot for Hero component which can act as a pattern to create another similar component by cursor.

11) Starter Templates and Example Applications

To accelerate development and reduce setup time, the Sitecore Content SDK includes a set of starter templates and example applications designed for different use cases and development styles.
The SDK provides a Next.js JavaScript starter template that enables rapid integration with Sitecore AI. This template is optimized for performance, scalability, and best practices in modern front-end development.
Starter Applications in examples

basic-nextjs -A minimal Next.js application showcasing how to fetch and render content from Sitecore AI using the Content SDK. Ideal for SSR/SSG use cases and developers looking to build scalable, production-ready apps.

basic-spa -A single-page application (SPA) example that demonstrates client-side rendering and dynamic content loading. Useful for lightweight apps or scenarios where SSR is not required.

Other demo site to showcase Sitecore AI capabilities using the Content SDK:

kit-nextjs-article-starter

kit-nextjs-location-starter

kit-nextjs-product-starter

kit-nextjs-skate-park

Final Thoughts

The Sitecore Content SDK represents a major leap forward for developers building on Sitecore AI. Unlike the older JSS SDK, which carried legacy dependencies, the Content SDK is purpose-built for modern headless architectures—lightweight, efficient, and deeply optimized for frameworks like Next.js. With features like App Router support, runtime and CLI configuration flexibility, and explicit component mapping, it empowers teams to create scalable, high-performance applications while maintaining clean, modular code structures.

In financial services, trust has always been foundational. But today, it’s being redefined, not by brand reputation or policy language, but by how customers experience speed, control, and transparency in real time. 

According to Adobe’s report, “State of Customer Experience in Financial Services in an AI-Driven World,” 96% of financial services executives say customers value privacy and data protection, and 63% say they expect transparent pricing. These have become operational expectations, and they’re shaping how trust is built moment by moment.

Trust Is Built in the Details Customers Can See

A face-ID login. A real-time transaction alert. A personalized financial nudge. These micro-moments now carry more weight than any static privacy policy. Customers judge trustworthiness by how responsive and secure their digital experiences feel—especially when managing sensitive tasks like wire transfers, credit approvals, or investment decisions. 

In this new landscape, trust is engineered, not assumed. 

Designing for Trust Means Designing for the Customer

Customers today expect more than digital convenience. They want to feel in control of their money, identity, and digital footprint and engage with institutions that respect their time, values, and privacy. Trust is no longer built solely through face-to-face interactions or legacy brand reputation. Trust is earned through every digital touchpoint.

To meet these expectations, financial institutions must deliver on three critical fronts:

1. Mobile-First Journeys With Instant Authentication

Customers expect secure access anytime, anywhere. A mobile-first design can enable frictionless, secure interactions that reinforce a sense of control and safety. Biometric authentication, real-time alerts, and intuitive navigation all contribute to a trustworthy experience.

2. Personalized Recommendations That Reflect Their Financial Goals

Trust grows when customers feel understood. Using AI and data responsibly to deliver tailored insights, whether it’s budgeting tips, investment opportunities, or credit alerts, shows that the institution is aligned with the customer’s financial well-being. Transparency in how data is used is key to maintaining that trust.

3. Seamless, Omnichannel Experiences That Feel Consistent and Secure

Whether a customer is engaging via app, website, call center, or in-branch, the experience should feel unified and secure. Consistency in branding, messaging, and service quality reinforces reliability, while secure data handling across channels ensures peace of mind.

Institutions that fail to deliver these experiences risk losing not just attention but loyalty. In a competitive landscape where switching providers is easier than ever, trust becomes a differentiator and a strategic imperative.

From Compliance Output to Design Input

Trust has become a core design principle. Instead of treating it as the outcome of compliance, financial institutions are embedding it into the very fabric of the customer experience. This shift reflects a broader understanding: trust is emotional, experiential, and earned in moments, not just mandated in policies.

That means:

Aligning products, security, and experience teams.

Trustworthy experiences require collaboration across silos. When product managers, cybersecurity experts, and UX designers work together, they can create solutions that are not only secure but also intuitive and empathetic. This alignment ensures that security features enhance, not hinder, the user experience.

Ensuring Personalization respects boundaries and data use is clearly communicated.

Customers want tailored experiences, but also want to know their data is safe. Leading institutions are adopting privacy-by-design principles, making it easy for users to understand how their data is used and giving them control over personalization settings. Transparency builds confidence; ambiguity erodes it.

Embedding transparency and predictability into every screen and interaction.

From clear language in disclosures to consistent UI patterns, every detail matters. Predictable flows, upfront information, and visible security cues (like encryption badges or session timers) help users feel safe and informed. These micro-moments of clarity add up to a macro-impact on trust.

This evolution requires cross-functional collaboration and a deep understanding of customer expectations.

Ready to Build Trust Through Experience Design?

Download the full Adobe report to explore the top 10 insights shaping the future of financial services, and discover how your organization can lead with intelligence, responsibility, and trust.

Learn About Perficient and Adobe’s Partnership

Perficient and Adobe bring together deep industry expertise and powerful experience technologies to help financial services organizations unify data, orchestrate journeys, and deliver customer-centric experiences that build trust and drive growth.

Get in Touch With Our Experts

We’re pleased that Perficient has been honored with a second award for our transformative work with a budget-friendly international airline. The Silver W3 Award in the Mobile Apps & Sites – Travel & Tourism category from the Academy of Interactive and Visual Arts (AIVA) celebrates our commitment to delivering exceptional digital experiences that drive real-world impact.

The W3 Awards, now in their 20th year, spotlight the best in digital creativity across websites, mobile apps, video, social media, and emerging tech. With thousands of global entries, only the top 20% earn Silver distinction—making this achievement especially meaningful.

A Budget-Friendly Airline, Reimagined

Our award-winning submission showcased how Perficient partnered with the international airline to modernize their digital experience and better serve budget-conscious travelers. The project focused on:

• Enhancing mobile usability for travelers booking international flights
• Streamlining the user journey from search to checkout
• Improving accessibility and performance across devices

The result? A mobile experience that’s not only intuitive and visually engaging but also aligned with the organization’s mission to offer affordable travel without compromising quality. You can read the full success story here.

Celebrating Digital Excellence

The W3 Awards are judged by AIVA, a prestigious panel of experts from top-tier organizations including Disney, Netflix, Deloitte Digital, and IBM. Entries are evaluated against a standard of excellence, not each other, ensuring that every winner truly represents the best in their category.

Looking Ahead

This award is a testament to the talent and dedication of our teams who consistently push boundaries to deliver impactful digital solutions. We’re proud to be recognized among the industry’s top innovators and look forward to continuing our work with clients to elevate digital experiences across industries.

In today’s financial landscape, personalization is no longer a luxury; it’s a customer expectation. Yet, according to Adobe’s latest State of Customer Experience in Financial Services in an AI-Driven World report, only 36% of the customer journey is currently personalized, despite 74% of financial services executives acknowledging that their customers expect tailored interactions.

This gap isn’t just a missed opportunity; it’s a trust breaker.

Why Personalization Matters More Than Ever

Financial decisions are deeply personal. Whether a customer is exploring mortgage options, planning for retirement, or managing small business finances, they expect advice and experiences that reflect their unique goals and life stage. Generic nudges and one-size-fits-all messaging simply don’t cut it anymore.

Early-stage interactions—like product discovery or financial education—are especially critical. These are high-value moments where relevance builds trust and guides decision-making. Yet many institutions fall short, lacking the orchestration needed to deliver personalized engagement across these initial touchpoints.

What’s Holding Institutions Back?

The report highlights several barriers:

• Fragmented data systems that prevent a unified view of the customer
• Legacy operating models that prioritize product silos over customer journeys
• Compliance concerns that limit personalization efforts, even when customers expect it

These challenges are compounded by the rise of AI-powered experiences, which demand real-time, context-aware personalization across channels.

The Path Forward: Adaptive, Lifecycle Personalization

To close the gap, financial institutions must evolve from episodic personalization to adaptive, full-lifecycle engagement. That means:

• Investing in unified customer profiles and behavioral insights
• Building real-time content engines that respond to customer signals
• Designing personalization strategies that grow with the relationship and not just the transaction

Download the full Adobe report to explore the top 10 insights shaping the future of financial services, and discover how your organization can lead with intelligence, responsibility, and trust.

Learn About Perficient and Adobe’s Partnership

Are you looking for a partner to help you transform and modernize your technology strategy? Perficient and Adobe bring together deep industry expertise and powerful experience technologies to help financial services organizations unify data, orchestrate journeys, and deliver customer-centric experiences that build trust and drive growth.

Get in Touch With Our Experts

As customer expectations continue to rise, financial services organizations are under increasing pressure to deliver personalized, seamless, and secure digital experiences. Adobe’s latest report, The Total Economic Impact of Adobe’s Content Supply Chain Solution, reveals how Generative AI and connected data are reshaping the industry and why now is the time for financial institutions to evolve.

A Wake-Up Call for Financial Services

Consumers today expect more than just secure transactions. They want personalized recommendations, consistent omnichannel experiences, and transparency in how their data and AI-generated content are used. Yet, Adobe’s research shows a significant gap between these expectations and what financial services brands currently deliver:

• 90% of consumers rate data privacy as critical, but only 58% feel their data is handled securely
• 79% expect consistent experiences across channels, but just 47% say brands deliver
• Only 33% feel brands anticipate their needs with relevant offers, despite 70% expecting it

This disconnect presents a clear opportunity for financial institutions to differentiate themselves by investing in AI-powered personalization and content delivery.

GenAI Moves From Concept to Competitive Advantage

Generative AI is no longer a futuristic concept; it is now a reality. It’s a strategic imperative. In 2025, 56% of financial services organizations are prioritizing GenAI to improve client interactions and employee productivity. Wealth and asset management firms lead the charge with 60% focusing on AI-driven client engagement compared to 52% in retail banking.

Use cases are expanding rapidly:

• Chatbots are the most mature application, with 49% of organizations already using them
• Journey optimization and data analysis are gaining traction, with over 40% of firms piloting or deploying solutions
• AI is also being used to automate workflows, generate creative content, and personalize customer experiences across channels

Efficiency, Engagement, and Growth

Executives are already seeing tangible benefits from AI adoption:

• 51% report major gains in content production speed
• 50% see improved team productivity
• 47% note freed-up resources for strategic initiatives

These improvements are driving better customer engagement and laying the foundation for scalable, personalized marketing.

Overcoming Compliance, Data Silos, and Culture

Despite the momentum, scaling AI in financial services isn’t without challenges. Governance, compliance, and privacy concerns top the list, especially in retail banking, where 59% of executives cite compliance as the biggest hurdle. Siloed data is another major issue, particularly in wealth and asset management, where 51% struggle to unify customer insights.

To move forward, organizations must:

• Establish cross-functional AI governance committees
• Invest in real-time data platforms
• Prioritize ethical AI practices to protect brand reputation

The Road Ahead

The Adobe report paints a clear picture: financial services organizations must embrace AI and digital transformation to stay competitive. Key trends shaping the future include:

• Hyper-Personalization | Real-time, one-to-one interactions are the goal, but only 33% of firms can update offers based on browsing history.
• Omnichannel Consistency | Practitioners feel pressure to deliver more content across more channels, with 43% citing increased volume demands.
• Sustainable Innovation | Wealth managers are leading the way in sustainable investing, responding to growing consumer demand.

To succeed, financial institutions must take a methodical, compliant approach to AI adoption, balancing innovation with trust. The winners will be those who connect data, content, and customer insights to deliver meaningful, personalized experiences at scale.

Ready to Transform Your Digital Experience Strategy?

Navigating the complexities of AI adoption, data governance, and digital transformation requires more than just technology. It demands deep industry expertise and a strategic partner who understands the nuances of financial services.

Our experts bring together Adobe solutions, generative AI innovation, and financial services experience to help you:

• Deliver personalized, compliant, and scalable digital experiences
• Break down data silos and activate real-time insights
• Accelerate content creation and journey optimization with AI
• Build trust through secure, transparent, and consistent customer interactions

Whether you’re modernizing for next-gen customers, launching new digital offerings, or scaling AI across your organization, we’re here to help you move forward with confidence.

Let’s connect and explore how we can elevate your customer experience together.

The headlines are troubling but predictable. The Trump administration will launch a program next year to find out how much money an artificial intelligence algorithm could save the federal government by denying care to Medicare patients. Meanwhile, a survey of physicians published by the American Medical Association in February found that 61% think AI is “increasing prior authorization denials, exacerbating avoidable patient harms and escalating unnecessary waste now and into the future.”

We’re witnessing the healthcare industry’s narrow vision of AI in action: algorithms designed to say “no” faster and more efficiently than ever before. But what if we’re missing the bigger opportunity?

The Current AI Problem: Built to Deny, Not to Help

The recent expansion of AI-powered prior authorization reveals a fundamental flaw in how we’re approaching healthcare technology. “The more expensive it is, the more likely it is to be denied,” said Jennifer Oliva, a professor at the Maurer School of Law at Indiana University-Bloomington, whose work focuses on AI regulation and health coverage.

This approach creates a vicious cycle: patients don’t understand their benefits, seek inappropriate or unnecessary care, trigger costly prior authorization processes, face denials, appeal those denials, and ultimately either give up or create even more administrative burden for everyone involved.

The human cost is real. Nearly three-quarters of respondents thought prior authorization was a “major” problem in a July poll published by KFF, and we’ve seen how public displeasure with insurance denials dominated the news in December, when the shooting death of UnitedHealthcare’s CEO led many to anoint his alleged killer as a folk hero.

A Better Vision: The AI Concierge Approach

What if instead of using AI to deny care more efficiently, we used it to help patients access the right care more effectively? This is where the AI Concierge concept transforms the entire equation.

An AI Concierge doesn’t wait for a claim to be submitted to make a decision. Instead, it proactively:

• Educates patients about their benefits before they need care
• Guides them to appropriate providers within their network
• Explains coverage limitations in plain language before appointments
• Suggests preventive alternatives that could avoid more expensive interventions
• Streamlines pre-authorization by ensuring patients have the right documentation upfront

The Quantified Business Case

The financial argument for AI Concierge services is compelling:

Star Ratings Revenue Impact: A half-star increase in Medicare Star Ratings is valued at approximately $500 per member. For a 75,000-member plan, that translates to $37.5 million in additional funding. An AI Concierge directly improves patient satisfaction scores that drive these ratings.

Operational Efficiency Gains: Healthcare providers implementing AI-powered patient engagement systems report 15-20% boosts in clinic revenue and 10-20% reductions in overall operational costs. Clinics using AI tools see 15-25% increases in patient retention rates.

Cost Avoidance Through Prevention: Utilizing AI to help patients access appropriate care could save up to 50% on treatment costs while improving health outcomes by up to 40%. This happens by preventing more expensive interventions through proper preventive care utilization.

The HEDIS Connection

HEDIS measures provide the perfect framework for demonstrating AI Concierge value. With 235 million people enrolled in plans that report HEDIS results, improving these scores directly impacts revenue through bonus payments and competitive positioning.

An AI Concierge naturally improves HEDIS performance in:

• Preventive Care Measures: Proactive guidance increases screening and immunization rates
• Care Gap Closure: Identifies and addresses gaps before they become expensive problems
• Patient Engagement: Improves medication adherence and chronic disease management

Beyond the Pilot Programs

While government initiatives like the WISeR pilot program focus on “Wasteful and Inappropriate Service Reduction” through AI-powered denials, forward-thinking healthcare organizations have an opportunity to differentiate themselves with AI-powered patient empowerment.

The math is simple: preventing a $50,000 hospitalization through proactive care coordination delivers better ROI than efficiently denying the claim after it’s submitted.

AI Healthcare Concierge Implementation Strategy

For healthcare leaders considering AI Concierge implementation:

• Phase 1: Deploy AI-powered benefit explanation tools that reduce call center volume and improve patient understanding
• Phase 2: Integrate predictive analytics to identify patients at risk for expensive interventions and guide them to preventive alternatives
• Phase 3: Expand to comprehensive care navigation that optimizes both patient outcomes and organizational performance

The Competitive Advantage

While competitors invest in AI to process denials faster, organizations implementing AI Concierge services are investing in:

• Member satisfaction and retention (15-25% improvement rates)
• Star rating improvements ($500 per member value per half-star)
• Operational cost reduction (10-20% typical savings)
• Revenue protection through better member experience

Conclusion: Choose Your AI Future

The current trajectory of AI in healthcare—focused on denial optimization—represents a massive missed opportunity. As one physician noted about the Medicare pilot: “I will always, always err on the side that doctors know what’s best for their patients.”

AI Healthcare Concierge services align with this principle by empowering both patients and providers with better information, earlier intervention, and more effective care coordination. The technology exists. The business case is proven. The patient need is urgent.

The question isn’t whether AI will transform healthcare—it’s whether we’ll use it to build walls or bridges between patients and the care they need.

The choice is ours. Let’s choose wisely.

We’re proud to announce that we’ve earned our 8th Adobe specialization in Adobe’s Real-time Customer Data Platform. This milestone reflects our continued commitment to delivering exceptional digital experiences and deepens our already robust Adobe partnership.

View our other specializations in the Adobe partner directory.

What is Adobe’s Real-time CDP?

Real-time Customer Data Platform is a powerful solution that enables organizations to unify customer data from multiple sources in real-time, creating actionable profiles that drive personalized, omnichannel experiences. As customer expectations continue to rise, Real-time CDP empowers brands to activate their data with precision, speed, and relevance.

Why This Specialization Matters

Achieving an Adobe specialization is no small feat. Adobe’s rigorous program evaluates partners on their technical expertise, successful implementations, and proven customer impact. This new Real-time CDP specialization validates Perficient’s ability to architect and deploy scalable data solutions that help clients unlock the full potential of their customer data.

Delivering Real-time Impact Across Industries

Our team has already helped leading brands across industries leverage Adobe’s Real-time CDP to:

• Break down data silos and unify fragmented customer information
• Build real-time, privacy-compliant customer profiles
• Activate audiences across channels for personalized engagement
• Drive measurable business outcomes through data-driven marketing

“This specialization is a testament to our team’s deep expertise in Adobe Experience Cloud and our ability to help clients harness real-time data to deliver meaningful customer experiences,” said Lynn Brading, Global Adobe Alliance Director at Perficient.

How We’re Innovating and Growing With Adobe

As we continue to expand our Adobe capabilities, this specialization reinforces our position as a trusted advisor for enterprise organizations seeking to modernize their digital ecosystems. Whether you’re just beginning your journey with Real-time CDP or looking to optimize an existing implementation, Perficient is ready to help.

Let’s Connect

Explore our Adobe partner page to learn more about our specializations, success stories, and how we can help you turn data into a strategic advantage.

In today’s hyper-personalized digital world, delivering the right message to the right customer at the right time is non-negotiable. 

Adobe Commerce is a powerful eCommerce engine, but when coupled with Adobe Real-Time CDP (Customer Data Platform), it evolves into an intelligent experience machine, which is capable of deep AI-powered personalization, dynamic segmentation, and real-time responsiveness. 

What is Adobe Real-Time CDP? 

Adobe Real-Time CDP is a Customer Data Platform that collects and unifies data across various sources (websites, apps, CRM, etc.) into a single, comprehensive real-time customer profile. This data is then accessible to other systems for marketing, sales, and service. 

Key Capabilities of Real-time CDP

• Real-time data ingestion and activation.  
• Identity resolution across devices and platforms 
• AI-driven insights and audience segmentation 
• Data governance and privacy compliance tools 

Why Integrate Adobe Commerce with Adobe CDP? 

Adobe Commerce offers native customer segmentation, but it’s limited to session or behavior data within the commerce environment. When the customer data is vast, the native segmentation becomes very slow, impacting overall performance.  

What We Gain with Real-Time CDP

Use Cases

1. Win-back Campaign: Identify dormant users in CDP and activate personalized discounts  
2. Cart Recovery: Capture cart abandonment events. 
3. High-Intent Buyers: Target customers who browse premium products but didn’t convert 

Integration of Adobe Commerce with Adobe Real-Time CDP 

Data Layer Implementation

• Install Adobe Experience Platform Web SDK to enable real-time event tracking and identity collection.  
• Define and deploy a custom XDM schema aligned with Commerce events. 

Customer Identity Mapping

• Implement Adobe Identity Service to build unified customer profiles across anonymous and logged-in sessions. 
• Ensure login/signup events are tracked for persistent identification. 

Data Collection Configuration

• Tag key Commerce events (add to cart, purchase, product) to collect data. 
• Set up batch or streaming ingestion using the following extensions: 
  • audiences-activation 
  • experience-platform-connector
• Admin configuration for Organization ID, Dataset ID & Data Stream ID:  
  • System -> Services -> Data Connection 
  • System -> Services -> Commerce Service Connector 

Audience Segmentation & Activation

• Create dynamic audiences using behavioral, transactional, and CRM data.  
• Assign Audience in Adobe Commerce. 

Personalization Execution

• Leverage Adobe Target or Adobe Experience Manager (AEM) to serve personalized content.
• CDP can be used for decision making, like suppressing offers to churn customers. 

Challenges to Consider 

• Data Governance: Ensure GDPR/CCPA compliance with CDP’s consent management tools. 
• Identity Resolution Complexity: Work closely with marketing teams to define identity rules. 
• Cross-Team Collaboration: Integration touches data engineering, commerce, marketing, and legal teams.

Conclusion 

Integrating Adobe Commerce with CDP empowers both business and technical teams to unify profiles and stay ahead in a dynamic marketplace by delivering personalization.  

Adobe Real-Time CDP is not just a marketing tool, it’s an asset for creating commerce experiences that adapt to the customer in real-time.   

In earlier blogs – Why AI-Led Experiences Are the Future — And How Sitecore Stream Delivers Them and Creating a Brand Kit in Stream: Why It Matters and How It helps Organizations, I tried to explore what Sitecore Stream is, how it powers AI-led content management, and how features like Brand Kit and Assist streamline your creative process. Those were all about content creation and brand consistency.

But here’s the next big leap:

Imagine this: You’re enhancing your website, launching a new campaign, or rolling out a promotional activity — and you can plan, manage, and execute it all without ever leaving Sitecore portal. No switching between tools. No messy integrations. No lost time.

With AI seamlessly integrated into project creation and management, Sitecore Stream becomes more than just a workspace — it becomes your smart workspace. From automatically generating project outlines, suggesting tasks, and assigning responsibilities, to tracking progress and flagging risks, AI acts as your proactive co-pilot every step of the way.

• One Unified Platform – Content, creative assets, AI planning, project tracking — all in one place.
• Smarter, Faster Execution – AI recommendations help you plan and launch in record time.
• Team Alignment Without the Chaos – Everyone works in the same environment, with instant visibility into priorities and progress.
• Eliminate Context Switching – Stay focused by keeping everything connected inside Sitecore Stream.

Why Manage Projects in Sitecore Stream?

Traditional workflows often mean hopping between:

• A PM tool for scheduling and tasks
• A content platform for asset creation
• A chat app for collaboration

With Sitecore Stream, you get:

• A centralized workspace to create and manage projects
• Built-in AI to help suggest deliverables and tasks
• Direct Sitecore product actions (e.g., linking straight into XM Cloud or Personalize or CDP)
• Multiple visual views (List, Kanban, Timeline, Funnel) for different working styles
• Integrated file storage for creative assets and documents

Let’s walk through the steps to create and manage your first project in Sitecore Stream.

Creating Your First Project — Step-by-Step

1. Check Permissions

To create projects, you need:

• Admin app role in Stream, or
• Org Admin / Owner in Sitecore Cloud Portal

If you don’t have these permissions, request them from your Sitecore Cloud admin.

2. Create the Project

• Navigate to Projects → Create project
• Fill in:
  • Project name
  • Start and End dates (the UI will calculate total days)
  • Brand Kit – link directly to your approved assets
  • Labels – for easy filtering
  • Thumbnail – for quick visual recognition
• Click Save to open your Project Details page

Tip: If you have a Brand Kit, always link it when creating a campaign — it keeps every deliverable aligned with approved brand standards.

3. Add Team Members

• Admins can invite members directly or approve/reject access requests.
• Keep project access restricted to relevant stakeholders to reduce noise and maintain focus.
• Click on +(Plus) icon on top right corner to add new team member

Add Deliverables – Turning Ideas into Action:

Deliverables are the big-ticket outputs your project needs – the stepping stones between concept and execution.

Manual Creation

From the Project Details -> List tab:

• Click Add deliverable
• Enter:
  • Name
  • Due date
  • Funnel stage (Top, Middle, Bottom)
  • Funnel tactic (predefined or custom)
  • Labels (optional)
• Save

AI-Powered Creation

As Sitecore stream is AI packed, its helps you in every step from brainstorming to executions, Use Suggest deliverables with AI:

• Stream analyzes your project name and description
• Add a prompt for more context for creating deliverable. Ex: In below screenshot, I have given context to create deliverable to add campaign and stream has generated deliverables.
• AI proposes deliverables across funnel stages
  – Pick, refine, or regenerate until it fits your plan

Breaking It Down Further: Tasks

Tasks are the day-to-day actions needed to complete each deliverable.

Manual Task Creation

Under a deliverable in the List tab:

• Click Add task
• Give it a name and save
• Open the task pane to set:
  • Labels
  • Status (Not started / In progress / Done)
  • Start & end dates (Stream shows remaining days)
  • Assignee
  • Priority (High / Medium / Low)
  • Description
  • Attachments (DOCX, PDF, PNG, JPG)
  • Dependencies
  • Actions (predefined calls into Sitecore products)

AI-Powered Task Suggestions

• Click Suggest tasks with AI under a deliverable
• AI proposes tasks — you can save, edit, or remove as needed

Linking Sitecore Actions

You can add Sitecore actions to a task — e.g., a button to create an specific item in XM Cloud. This bridges planning and doing in one click.  You can add action for sitecore products like Personalize, CDP, XMcloud, once you choose resource, you can select action to be performed in the products.

Working Your Way: Multiple Views

Different teams prefer different ways of visualizing work. Sitecore Stream gives you five interactive views:

1. List View (Default)

• Hierarchical view of deliverables and tasks
• Best for editing, filtering, and using AI suggestions

2. Kanban View

• Drag task cards between statuses
• Perfect for daily standups and quick progress tracking
• Expand/collapse deliverables for focus

3. Timeline View (Gantt-Style)

• Visualize start/end dates, durations, and dependencies
• Drag-and-drop to adjust schedules
• Switch between Day/Week/Month/Quarter for planning at different levels

4. Funnel View

• Organize deliverables into Top, Middle, Bottom stages
• See funnel coverage at a glance
• Drag between stages to reassign

5. Attachments View

• Centralized file repository for your project
• Search, preview, filter, and download creative assets

The Value of Stream’s Orchestration

Sitecore Stream doesn’t just bolt project management onto a content tool — it blends them into a single marketing execution hub. The benefits are tangible:

• No context switching between PM tools and content platforms
• AI assistance for faster planning
• Visual views for different work styles
• Integrated Sitecore actions to reduce clicks and friction
• Built-in asset management for projects

When your campaign planning, creative production, and execution all live in one system, your team can move faster and with more confidence that nothing is falling through the cracks.

Sitecore Stream moves marketing orchestration into the same ecosystem as content and product tools. You’ll gain a unified space for ideation, execution, and optimization — keeping strategy, tasks, and assets aligned from start to finish.

That combination cuts down context switches, lesser dependencies, AI help for ideation, speeds campaigns, and makes funnel coverage and task ownership visible at a glance. If you already use Sitecore products, the integrated actions are particularly time-saving.

The digital world isn’t slowing down, and neither are your customers. They expect fast, around-the-clock support in their language. For global businesses, meeting that demand can be costly. Hiring multilingual agents in every region adds up quickly. That’s why more companies are turning to real-time translation tools. They offer a more scalable, cost-effective way to deliver consistent, high-quality service across languages.

In this blog article, I will guide you through how we, at Perficient, are addressing this challenge by leveraging Twilio’s ConversationRelay and AI translation technology to deliver real-time voice translation for contact centers. The result is a quick, accurate, and natural conversation with an agent who can speak in the customer’s native language. Pretty impressive, isn’t it?

What Is Twilio ConversationRelay?

For real-time voice translation with Twilio ConversationRelay, developers can access live Media Streams between the customer and agent, and improve their conversation in real-time. Think of it as a smart audio bridge that enables you to plug in AI features such as text-to-speech, real-time translation, speech-to-text transcription, or an LLM. As a result, it provides a strong basis for creating dynamic, multilingual voice experiences in modern contact centers.

Now, let’s see how the backend of our real-time voice translation demo is put together.

Twilio ConversationRelay captures live audio when a customer speaks in their native language, for example, Spanish, using Programmable Voice. That stream is then routed through WebSockets to maintain a quick and responsive connection.

The procedure reverses itself when the agent responds in English, recording their voice, transcribing it, translating it back into the customer’s language, and then turning it back into speech.

It’s fascinating how AI makes it possible to have seamless, two-way, real-time conversation between speakers of different languages without the need for a human interpreter.

Why It Matters

Real-time voice translation is revolutionizing the way businesses communicate with customers by enabling support in the customer’s language without needing an agent who speaks it natively.

But it’s not just about translating words. This method helps support teams truly understand what customers are saying, including the tone and emotion behind their message. That results in fewer misunderstandings, quicker resolution times, and a smoother overall experience.

More importantly, it helps build trust and empathy in conversations that might otherwise feel distant or disconnected. With that, customer satisfaction isn’t just possible, it’s almost guaranteed.

Challenges And Considerations

Real-time voice translation is a game-changer, but making it work seamlessly in a live contact center is a whole different story.

One of the biggest hurdles is latency. Even a slight delay, just a few hundred milliseconds, can disrupt the natural flow of a conversation and make things feel awkward or disjointed.

Then there’s the issue of accuracy. In industries like healthcare or finance, where precise language and industry-specific terms matter, generic translation tools can easily miss the mark.

And let’s not forget about privacy and compliance. When you’re dealing with live audio and sensitive data, you have to play by the rules, whether it’s GDPR, HIPAA, or PCI DSS.

That’s why building a multilingual contact center solution isn’t just about plugging in a translation tool. It takes careful planning, the right tech stack, and thorough testing to get it right.

At Perficient, our Customer Care practice is actively focused on minimizing latency in real-time voice translation for cloud contact centers. Leveraging Twilio ConversationRelay, we are optimizing low-latency audio streaming and integrating optimal ASR and translation models tailored to a specific industry. We also embed secure, compliant workflows that protect sensitive data while preserving natural conversational flow.

See It in Action

We’ve put together a live demo that walks through the full experience, from capturing the customer’s voice to translating it in real-time and vice versa within a cloud contact center.

Curious to see it in action? Or wondering how something like this could level up your contact center? Let’s connect, and we’d love to show you what’s possible.