From digital shelf insights to action: Building a growth operating model

From digital shelf insights to action: Building a growth operating model

Digital shelf analytics has moved beyond monitoring product pages and producing reports. Brands increasingly recognize that their presence across retailer websites, marketplaces, search engines, and AI-powered discovery experiences influences whether shoppers find, consider, and purchase their products.

Commercial performance today is shaped by these factors:

• Content quality
• Search visibility
• Pricing
• Availability
• Ratings
• Reviews
• Competitor activity

Recognizing the strategic importance of the digital shelf is only the beginning. Many brands have extensive data showing what is happening across online channels, but the harder challenge is turning it into coordinated decisions and measurable action. A dashboard may reveal a pricing disadvantage, declining visibility, or a content issue, but the insight has limited value if it does not reach the right team or trigger a response.

The next phase of digital shelf analytics will be defined less by how much data brands collect and more by how effectively they use it.

Brands need to connect insights to commercial priorities, establish ownership, create repeatable workflows, and measure results. It becomes a genuine growth lever when embedded into the way the organization operates.

eClerx was recognized in the Gartner^® Market Guide for Digital Shelf Analytics in both 2025 and 2026. We think it reflects the continued importance of digital shelf analytics as brands navigate increasingly complex digital commerce environments.

In our view, the recognition comes at a time when digital shelf performance is becoming much more than an eCommerce reporting function. For brands competing across marketplaces, retailer sites, digital channels, and emerging AI-powered discovery experiences, the digital shelf is now directly connected to visibility, conversion, pricing power, and growth.

Closing the insight-to-action gap

Many brands can identify when a product goes out of stock, a competitor changes its price, a product page loses visibility, or content no longer meets a retailer’s requirements. The harder question is what happens next.

Some symptoms might be:

• An alert appears in a dashboard, but it is not clear who should review it, whether it is commercially significant, or what action should follow.
• Brands can see what is happening, but lack the processes required to respond consistently and at speed.
• Analysts produce valuable findings, but commercial teams struggle to determine which recommendations deserve attention.
• Pricing teams react to competitor movements without knowing whether the change reflects a short-term promotion, an inventory shift, or a wider market trend.

Across thousands of products, retailers, and regions, minor changes can generate large numbers of alerts. Yet not every issue deserves the same response. A missing attribute on a low-volume item does not carry the same risk as inaccurate content on a flagship product, while a temporary promotion may matter less than a sustained pricing disadvantage across strategic retailers.

Digital shelf analytics becomes more valuable when brands distinguish between activity and impact. Issues should be prioritized according to the importance of the product, the value of the retailer, the scale and duration of the change, and whether competitors are gaining an advantage. Commercial context helps teams focus on the opportunities and risks most likely to affect growth.

Connecting signals across the business

Digital shelf signals are often managed by separate teams; content teams focus on product information and retailer compliance, pricing teams monitor competitiveness and margin, supply chain teams oversee availability, and customer experience teams track ratings and reviews. Although these responsibilities may be separated internally, the shopper experiences them as one connected journey.

Strong digital shelf performance depends on more than excelling in a single area: compelling content can be undermined by uncompetitive pricing, while the right price may have little impact if a product is unavailable or difficult to find. Even strong search visibility may not translate into engagement when ratings and reviews compare poorly with competing products.

The same principle applies to retailer algorithms, search engines, and AI-powered recommendation systems. These environments evaluate combinations of signals when deciding which products to display, rank, recommend, or summarize. Reviewing content, pricing, availability, and reviews in isolation may hide the reason a product is losing visibility or conversion.

A connected view makes it easier to identify root causes and avoid conflicting decisions. When visibility declines, teams should be able to assess whether the cause relates to content quality, stock levels, pricing, customer feedback, competitor activity, retailer changes, or several factors at once. Digital shelf intelligence is most useful when it explains relationships rather than reporting each metric independently.

Establishing ownership and commercial workflows

Technology can surface an issue, but resolving it often requires coordination across multiple teams. Content gaps may involve brand, legal, product, and retailer stakeholders, pricing changes may require commercial approval, availability issues may depend on inventory planning, and negative reviews can point to broader product concerns beyond the eCommerce function.

For digital shelf intelligence to translate into action, brands need clear ownership. Teams should understand who reviews pricing, content, availability, visibility, and customer feedback issues, as well as who can approve changes. Workflows should define how high-priority opportunities are routed, when escalation is needed, and how actions are tracked through resolution.

Without this structure, recommendations can disappear into dashboards, spreadsheets, email threads, and meetings. With it, digital shelf intelligence becomes part of how teams manage commercial performance. The goal is not to create a complicated process around every alert, but to ensure important insights reach the right people with enough context and authority to respond.

Strong operating models also measure what happens after action is taken. Teams should know whether a pricing adjustment improved conversion, new content increased visibility, or resolving an availability issue recovered lost sales. This closes the loop between insight and outcome and helps refine future decisions.

Using AI to support continuous optimization

AI can analyze larger volumes of digital shelf data, identify patterns, summarize performance changes, and recommend actions more quickly. Instead of manually reviewing multiple dashboards, teams can ask which products lost visibility, where competitors gained share, which pricing changes affected performance, and what contributed to a decline.

AI helps brands move more quickly from raw data to meaningful commercial insight by surfacing emerging issues, revealing connections across performance signals, and highlighting the products or channels that require the most attention. It can also translate complex analysis into clearer recommendations, making it easier for stakeholders to understand what is happening and decide how to respond.

Faster analysis does not automatically create faster execution. Brands still need to decide which recommendations align with strategy, how much risk they will accept, and which teams should act. AI is most valuable when it strengthens an established decision-making process rather than replacing commercial judgment. Without clear ownership and prioritization, brands may generate recommendations faster than the organization can absorb them.

The longer-term opportunity lies in creating a continuous cycle of optimization. By monitoring changes across content, pricing, availability, reviews, visibility, promotions, and competitor activity, brands can identify what is driving performance, focus on the most commercially significant issues, and measure the impact of each response. Those outcomes can then be used to sharpen future alerts, recommendations, and decision-making criteria.

Turning digital shelf data into commercial growth

The digital shelf will become more complex as brands compete across more retailers, marketplaces, search experiences, and AI-powered interfaces. Each channel introduces different requirements, competitors, and customer behaviors. Trying to manage that complexity by adding more dashboards is unlikely to solve the underlying challenge.

Brands need intelligence that explains what matters, why it matters, and what should happen next. They also need the processes and expertise to apply it across eCommerce, pricing, marketing, sales, supply chain, and product teams. The organizations that pull ahead will not necessarily collect the most data, but will connect their signals, focus on high-value opportunities, and act before competitors do.

Market360 combines AI-powered digital shelf technology with eClerx’s digital commerce expertise to help brands monitor and interpret product content, search visibility, pricing, promotions, availability, ratings, reviews, and competitor activity. By translating connected signals into prioritized insights, brands can move beyond passive reporting and make faster, more confident commercial decisions.

Digital shelf analytics is already a strategic growth lever. The next step is building the operating model that turns its potential into sustained commercial impact.

eClerx was recognized in the Gartner^® Market Guide for Digital Shelf Analytics in both 2025 and 2026. We think it reflects the continued importance of digital shelf analytics as brands navigate increasingly complex digital commerce environments.

In our view, the recognition comes at a time when digital shelf performance is becoming much more than an eCommerce reporting function. For brands competing across marketplaces, retailer sites, digital channels, and emerging AI-powered discovery experiences, the digital shelf is now directly connected to visibility, conversion, pricing power, and growth.

Visit the eClerx Market360™ page to learn more about how eClerx helps brands turn digital shelf signals into decision-ready market intelligence.

Disclaimer

Gartner^®, Market Guide for Digital Shelf Analytics, 18 May 2026. GARTNER is a trademark of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.

Why 9 out of 10 marketers still struggle to turn data into action

For years, marketing leaders have invested heavily in data, analytics, and martech platforms with the expectation that better insights would lead to more effective campaigns and stronger business outcomes.

Yet our latest survey reveals a striking reality: Only around 1 in 10 organizations believe they are highly effective at leveraging data to guide marketing investments.

Why is this happening? Marketing teams today have access to more customer data and more sophisticated technology than ever before. Yet many continue to struggle with the same challenges: fragmented data, inconsistent reporting, attribution blind spots, and an inability to optimize performance in real time.

The real challenge lies in turning insight into action, consistently, quickly, and at scale. This is what we call the activation gap. And as our research shows, it is becoming one of the defining challenges for modern marketing organizations.

What marketers are telling us

The activation gap shows up consistently in how marketing leaders evaluate their capabilities, measure performance, and assess their ability to act on data:

• Over 90% of organizations do not have fully integrated marketing data
• 9 out of 10 marketers say they are not fully leveraging available data to guide investments
• Nearly 9 out of 10 also say they struggle to deliver consistent customer experiences across channels

The challenge extends beyond data management. Measuring and optimizing performance is difficult for these teams too:

• 13% of respondents express high confidence in measuring cross-channel marketing ROI
• 1 in 8 organizations describe themselves as highly agile in monitoring and optimizing performance

When asked about the biggest barriers to improving marketing spend efficiency and data-driven decision-making, almost 90% of respondents pointed to structural issues like:

• Fragmented data sources
• Inconsistent reporting
• Unreliable measurement and attribution frameworks
• The lack of predictive models or real-time tracking

These responses reveal a consistent pattern: Martech stacks are collecting data and analytics effectively, but the systems, processes, and workflows needed to activate that data remain disconnected.

The hidden activation gap

Most marketing leaders have invested significantly and built mature martech stacks. But if data is collected in one system, analyzed in another, and acted upon through separate campaign and customer engagement platforms, the flow of data stagnates.

Along the way, insights are diluted or disconnected from the decisions they were meant to inform. As a result, valuable intelligence often remains trapped in dashboards and reports instead of influencing campaign optimization, customer journeys, and budget allocation.

The solution? A connective framework that links data, analytics, decision-making, and execution into a continuous cycle. When these elements work together, organizations evolve from reporting on performance to actively shaping it.

This is what we call activation architecture: the systems and workflows that enable data to flow seamlessly from insight to action.

What leading organizations do differently

Organizations that successfully close the activation gap have one thing in common: They’re creating the conditions that allow data to move seamlessly through their workflows.

Conclusion

As marketing ecosystems become more complex, competitive advantage will increasingly depend on how effectively organizations can leverage their data for decision-making. Those that succeed will move faster, optimize more effectively, and deliver more relevant customer experiences.

To understand the symptoms of the activation gap and how to close it, or to assess your own stack maturity, download our latest eClerx Marketing Report 2026: Mind the Gap.

Why digital shelf analytics is becoming a strategic growth lever for brands

Key takeaways

• Digital shelf management has become a primary driver of visibility, conversion, and revenue growth.
• Brands must connect pricing, content, availability, reviews, and competitive signals to understand true performance drivers.
• As digital commerce becomes more complex, small digital shelf issues can quickly translate into lost sales and market share.
• Leading brands are moving beyond reporting to prioritize actions that deliver measurable commercial impact.
• AI-powered discovery is raising the bar for digital shelf quality, consistency, and readiness..

eClerx was recognized in the Gartner^® Market Guide for Digital Shelf Analytics in both 2025 and 2026. We think it reflects the continued importance of digital shelf analytics as brands navigate increasingly complex digital commerce environments.

In our view, the recognition comes at a time when digital shelf performance is becoming much more than an eCommerce reporting function. For brands competing across marketplaces, retailer sites, digital channels, and emerging AI-powered discovery experiences, the digital shelf is now directly connected to visibility, conversion, pricing power, and growth.

The question for brands is no longer simply whether their products are listed online.

It is whether those products can be found, understood, trusted, compared, and purchased across every channel where shoppers make decisions.

That is why digital shelf analytics is becoming a strategic growth lever.

The digital shelf is now where brand performance is decided

Many brands have treated the digital shelf as a way to monitor product pages. Teams tracked whether content was complete, pricing was accurate, images were correct, products were available, and reviews were visible.

Those signals still matter, but the stakes are now much higher. Digital commerce intelligence is built around signals, with search rankings, recommendation engines, retail media placements, marketplace performance, and AI-powered discovery all shaped by the quality, consistency, and competitiveness of product information.

If a product has weak content, poor availability, inconsistent pricing, limited reviews, or low visibility, the impact is no longer isolated to one product page. It can affect how often the product appears, how confidently it is recommended, how it performs against competitors, and whether shoppers choose it at the point of decision.

Digital shelf analytics has therefore moved from a monitoring tool to a commercial intelligence layer.

It helps brands understand not only what is happening online, but why performance is changing and where action is needed.

Fragmented signals create fragmented decisions

Most brands are not short on data. Information such as product content, pricing, promotions, availability, reviews, ratings, search rankings, retailer performance, competitor movement, and marketplace changes are often tracked across separate dashboards, teams, and workflows.

The issue is that shoppers do not experience these signals separately. A shopper sees the full picture at once, weighing product content, price, availability, delivery options, reviews, competitor alternatives and marketplace ranking in the same decision moment.

Algorithms and AI systems evaluate these signals together, looking for product information that is relevant, reliable and trustworthy.

Brands need to understand the digital shelf as a connected system where a drop in pricing performance could stem from promotion timing, competitor moves, inventory issues or content gaps, while weaker visibility may be driven by availability, reviews, product attributes or inconsistent listings across retailers.

Without connected digital shelf management, teams risk solving symptoms instead of root causes.

Visibility is becoming harder to earn and easier to lose

Digital shelf visibility used to be easier to understand. Brands could track search placement, category rank, share of shelf, and product page performance across major retailers.

Visibility is now shaped by a moving mix of retailer rules and marketplace ranking shifts, along with paid placements, competitor price changes, stock levels and AI-generated recommendations that influence shoppers before they even reach a product page.

Brands need to look beyond surface-level visibility and understand what is helping or holding that visibility in place. Strong awareness may not be enough if product content is thin, a competitive offer can lose traction when availability drops, and even the right price may fail to convert when rivals have better reviews or more complete product information.

Digital shelf analytics solutions help brands identify these risks earlier and respond before performance declines become harder to reverse.

Move from reporting to action

The value of digital shelf management is not just in seeing more data. The real value comes from turning that data into action.

Brands need to understand which issues matter most, where they are happening and how long they have been active, as well as which competitors are benefiting and what the commercial impact may be.

Some examples include:

• A missing product image on a low-volume SKU may not require the same urgency as incorrect product content on a top-selling item during a major promotional period.
• A temporary price gap on one retailer may not carry the same risk as a broad pricing disadvantage across strategic channels.
• A stockout on a secondary marketplace may not matter as much as an availability issue on a priority retailer where the product usually drives significant volume.

Digital shelf analytic solutions becomes strategic when they help teams prioritize and give them a shared view of what is changing and what needs attention first.

That is how brands move from passive monitoring to faster, more confident decision-making.

Read our case study on how we partnered with a leading MRO and electronics distributor to build a market intelligence solution suite that powers decisions across 250,000 products daily.

AI raises the bar for digital shelf readiness

AI is changing how shoppers discover, compare, and evaluate products. Instead of scrolling through long lists of search results, shoppers can now ask for recommendations, comparisons, summaries, and product guidance.

This shift makes digital commerce intelligence more important because AI-powered discovery relies on many of the same signals brands already manage online, from product content and customer feedback to availability, pricing, category fit, product attributes and competitive positioning.

When these signals are incomplete or inconsistent, brands become harder for both shoppers and AI systems to evaluate correctly. That raises the importance of digital shelf readiness with product information needing to be accurate, structured and strong enough to support discovery, comparison and conversion.

AI does not replace digital shelf analytics; it makes stronger digital shelf intelligence essential.

Digital shelf analytics is now a growth discipline

The brands that pull ahead will be the ones that can turn digital shelf signals into clear commercial decisions. That requires a more connected view of performance, where visibility, content, price, promotions, availability, customer feedback and competitor movement are understood together ratherthan managed in isolation. It also requires teams to have the ownership and workflows in place to respond before small issues become bigger performance problems.

Technology can identify changes quickly as AI can make patterns easier to spot. However, improvement still depends on knowing which actions matter, who needs to act, and how those decisions connect to commercial outcomes.

Digital shelf optimization is becoming a growth lever because it helps brands defend visibility, improve conversion, stay competitive and respond faster as digital commerce continues to shift.

The real value is no longer just seeing what is happening on the digital shelf, but using those signals as market intelligence.

Want to go deeper?

Digital shelf optimization now depends on more than having access to data. Brands need the technology to connect fragmented signals at scale and the human expertise to interpret what those signals mean for performance, competitiveness and growth.

Market360 combines AI-driven technology with eClerx’s digital commerce expertise to help brands monitor, understand and act across key digital shelf signals including search visibility, product content, pricing, promotions, availability, ratings, reviews and competitor movement.

Visit the Market360 page to learn more about how eClerx helps brands turn digital shelf signals into decision-ready market intelligence.

Disclaimer

Gartner^®,Market Guide for Digital Shelf Analytics, 18 May 2026. GARTNER is a trademark of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.

Frequently Asked Questions

Q) Why is digital shelf analytics important for brands?

Digital shelf analytics helps brands understand how their products are performing across online channels, marketplaces, and retailer websites. By leveraging a digital Shelf analytics platform, brands can identify issues affecting visibility, pricing, content quality, and availability, enabling stronger digital shelf management and better commercial outcomes.

Q) How does digital shelf analytics improve product visibility?

Digital shelf analytics improves visibility by helping brands identify the factors that influence search rankings, category placement, and product discoverability. Through product visibility analytics and product content optimization, brands can enhance product listings, improve search performance, and increase the likelihood of being found by shoppers.

Q) What metrics should brands track on the digital shelf?

Brands should monitor metrics such as search rankings, share of shelf, pricing, promotions, ratings and reviews, content completeness, and stock availability. Effective online shelf monitoring combined with competitive pricing analytics helps brands understand performance drivers and respond quickly to changing market conditions.

Q) How does AI impact digital shelf performance?

AI is transforming how consumers discover and evaluate products by powering recommendations, comparisons, and search experiences. As AI-powered digital commerce continues to evolve, brands need strong product data, content quality, and product availability monitoring to ensure products remain visible, relevant, and competitive across digital channels.

Practical AI in financial crime compliance: Four key takeaways from industry leaders

Artificial intelligence continues to dominate conversations across financial services, but many compliance leaders are now moving beyond experimentation to ask a more practical question: how do we move AI from pilot programs into production while maintaining effective controls, governance, and measurable business outcomes?

During our recent webinar, Practical AI in Financial Crime Compliance, senior leaders from global financial institutions shared their experience implementing AI across KYC, sanctions screening, transaction monitoring, and fraud investigations. While every organization is at a different stage of maturity, several common themes emerged.

1. The industry is moving beyond exploration

Audience polling revealed that nearly half of participating organizations have already moved past experimentation and are implementing or scaling AI initiatives.

Panelists noted that the conversation has shifted significantly over the past 18-24 months. Rather than debating whether AI has a role in compliance, firms are now focused on identifying practical applications that deliver measurable value within established governance frameworks.

The consensus was clear: AI is becoming an important tool within the compliance operating model, but the core objectives of financial crime programs remain unchanged. Data quality, risk management, regulatory compliance, and sound operational controls are still fundamental.

2. Operational efficiency is driving adoption

When discussing the business case for AI, panelists consistently pointed to operational improvements rather than autonomous decision-making. Areas where organizations are seeing value include:

• Prioritizing and triaging analyst workloads
• Reducing manual administrative tasks
• Improving consistency across review processes
• Enhancing analyst productivity and investigative effectiveness
• Freeing up time for higher-value work

Panelists were clear that AI is not replacing compliance professionals. Organizations are using it to streamline repetitive activity and support better decision-making, with human oversight remaining central. The analyst’s role remains critical, both as a control function and for delivering effective client and regulatory outcomes.

3. Data readiness remains the largest obstacle

Despite growing momentum, panelists agreed that data readiness is one of the most significant barriers to scaling AI. Audience polling reinforced this, as respondents identified data quality and availability as a greater challenge than budget, organizational adoption, or technology selection.

Several speakers noted that organizations often focus first on model selection and technical capability, when the real challenge lies elsewhere: ensuring data is accessible, accurate, well-governed, and fit for purpose.

The implementation sequence must begin with establishing trusted data foundations, then deploying AI. Without reliable underlying data, even the most advanced capabilities struggle to produce meaningful outcomes.

4. Regulatory expectations are becoming clearer

Panelists noted a marked shift since 2019: regulators are increasingly recognizing the benefits AI can bring to compliance functions, and appetite for AI-enabled approaches has grown substantially. But the governing principles that determine whether a use case clears regulatory scrutiny remain exactly what they’ve always been—explainability, transparency into how models work, clarity on where data originates, and a clear line of sight into how decisions are made.

The framing that resonated most: regulators aren’t evaluating AI as a category. They’re evaluating risk relative to use case, which means the institutions moving fastest are the ones who can speak fluently about both.

Moving from pilot to production

Perhaps the most important takeaway is that the question is no longer whether AI can be applied within financial crime compliance, but how to operationalize it effectively.

Organizations seeing success share a common approach: practical use cases, strong data foundations, appropriate governance, and human accountability throughout. As AI adoption matures, these foundational elements are proving to be the differentiators between pilot projects and sustainable, enterprise-wide programs.

Dive into the full panel discussion For additional insights, including perspectives on governance, data readiness, operational implementation, and regulatory considerations, watch the full webinar recording.

eClerx unifies AI leadership to deliver outcome-driven results at enterprise scale

NEW YORK, May 20, 2026: eClerx Services Ltd (ECLERX.NS), a global leader in AI-powered analytics, digital operations, and business process management, today announced the formation of a unified AI organization to accelerate its enterprise AI strategy. John Flowers, former Head of BFSI at eClerx, will lead this new organization in partnership with Dr. Sanjay Kukreja, Chief Technology Officer, bringing together eClerx’s AI investments, infrastructure, and go-to-market capabilities under a single, focused leadership structure.

The move reflects eClerx’s conviction that the next wave of enterprise value creation is shifting away from open-ended transformation programs toward outcome-driven engagements. With its proven model of embedding AI directly into operational workflows, combined with its 25+ years of domain knowledge and process depth, the company offers a durable advantage that technology alone cannot replicate.

That accountability is already evident in results. eClerx’s Agentic AI deployments have brought significant automation savings, improvement in client NPS, and reduced time to market. These outcomes are enabled by eClerx’s AI framework of operational knowledge, contextual intelligence, and AI orchestration, applied at enterprise scale.

Responsible AI deployment is central to that framework. In 2025, eClerx became one of the first five companies globally to achieve ISO 42001:2023 certification for responsible, secure, and ethical AI, a standard that mirrors the governance and compliance rigor eClerx applies on behalf of its clients every day. Additionally, Forrester recognized eClerx as a “Notable Provider” for AI consulting excellence and systems integration, reflecting the company’s ability to bridge strategy and execution.

To learn more about eClerx’s enterprise AI framework, and responsible AI approach, visit  https://eclerx.com/artificial-intelligence/

About eClerx

eClerx provides AI-powered analytics, digital operations services, automation, and business process management to help clients unlock growth and drive business outcomes. eClerx partners with Fortune 500 enterprises across financial services, telecom, media & entertainment, luxury, retail & fashion, and manufacturing. A publicly listed company, eClerx operates across 17 countries with over 22,000 employees, serving clients globally across the Americas, APAC, and EMEA.

Media contact

Prathibha Das
Head – Brand & Corporate Marketing
prathibha.das@eclerx.com

How Answer Engine Optimization (AEO) Is Reshaping Customer Experience and Conversion

AI is no longer just influencing discovery. It’s now becoming the primary entry point to your brand.

AEO reflects a fundamental shift in how customers find, evaluate, and engage with products. As buyers increasingly rely on AI assistants, generative search, and recommendation engines for answers, assumptions about journeys, attribution, and conversion are changing.

AI-referred customers behave differently; they arrive with higher intent, clearer expectations, and far less patience for friction, inconsistency, or irrelevant experiences.

In this webinar, experts across eClerx, Radisson, and adidas explore how enterprise brands are responding to AEO-driven journeys changing user experience (UX) and content requirements, where existing CRO and analytics models fall short, and how leading teams are adapting their experience and measurement strategies to stay competitive.

This webinar covers:

• How AI-referred customers behave differently and how these patterns are surfacing in enterprise data
• How leading brands are redesigning UX, content, and journeys to turn AEO-driven discovery into measurable outcomes
• What CRO and customer experience (CX) leaders need to change today as AI assistants increasingly replace traditional search paths

Speakers

Raul Alvarez Barrera

Global VP, Digital, Radisson Hotel Group

eClerx

Bas Bunck

Director Consumer Experience, adidas

eClerx

Ryan Scott

Head, CRO and Analytics, eClerx

eClerx

Adam Curran

Head of Product Marketing

eClerx

Brian Warmoth

Director of Editorial & Retail

eClerx

eClerx at Gartner Finance Symposium/Xpo™ 2026

Finance at the Forefront: From Tools to Operating Models

Gartner Finance Symposium/Xpo™ brings together CFOs and senior finance executives to tackle the priorities shaping the future of finance: AI, cost optimization, ERP modernization, leadership effectiveness, growth planning, risk, and profitability in a volatile environment. 

At eClerx, we believe finance transformation doesn’t start and stop with technology. The future of finance will be defined by how work gets done — across systems, data, processes, and teams.

Why Attend

Gartner Finance Symposium/Xpo™ is designed for CFOs and finance leaders focused on improving efficiency, managing risk, driving profitability, and enabling future growth. The agenda includes key topics such as AI in finance, cost optimization, leadership effectiveness, growth planning and capital budgeting, and ERP finance. 

Here’s what you can expect at the event:

• Explore how AI is reshaping finance operations, from automation and predictive analytics to smarter decision-making
• Learn how finance leaders are rethinking cost structures, operating models, and ERP strategies for long-term performance
• Connect with CFOs, senior finance executives, Gartner analysts, and solution providers focused on what’s next for finance

How eClerx Helps

Finance leaders don’t need more disconnected tools. They need operating models that make transformation (actually) work.

eClerx helps organizations bring together:

• Process expertise to improve precision, control, and consistency
• Scalable global talent to flex capacity and strengthen execution
• AI-enabled efficiency to reduce manual work and accelerate outcomes

From finance operations and analytics to automation and transformation support, eClerx helps turn strategy into measurable execution.

Meet Us in National Harbor

Join us at Gartner Finance Symposium/Xpo™ 2026 to discuss how your finance organization can move beyond tools and build an operating model ready for the future.

Link to the event:https://www.gartner.com/en/conferences/na/cfo-finance-us

Attending from eClerx

Manish Sharma

CRO, Industry Head – BFSI, High Tech, Manufacturing & Retail

Steve Casey

VP Finance and Accounting Solutions

eClerx

Joe Pistacchio

Director Finance and Accounting Solutions

eClerx

Anant Kode

Global Head – Finance & Accounting Transformation

eClerx

Manoj Yohannan

Global Head – Growth Strategy & GTM

eClerx

Alessandra Paris

Vice President | Lead – Analyst & Partner Relations

eClerx

eClerx at FBA Fiber Connect 2026

Bringing together the leaders, innovators, and visionaries shaping the future of fiber broadband, the Fiber Broadband Association’s (FBA) 2026 Fiber Connect event explores the technologies, partnerships, and policies driving the next wave of connected communities across the world.

eClerx is excited to be attending Fiber Connect 2026, connecting with experts all over the fiber broadband industry to discuss the current state of the sector, as well as the trends and technologies driving its future.

Here’s what you can expect at the event:

• Keynotes from industry experts, as well as world-renowned futurist and theoretical physicist Dr. Michio Kaku, that delve into how AI and other emerging demand drivers will impact broadband strategies, infrastructure, and workforce
• Focused, hands-on workshops and practical playbooks that provide the expertise needed to build, launch, and scale digital and organizational transformations faster
• Opportunities to network, share ideas, and collaborate with ISPs, SBOs, and vendors and discover the new tech, software, and hardware shaping the future of the broadband industry.

Join us from May 17-20 to connect with our team and learn more about how we leveraged our domain expertise in areas like customer experience, dispatch, quality assurance, and digital marketing.

Additionally, make sure to RSVP to our mixer event cohosted with the Strong Women Alliance on Tuesday, May 19^th to celebrate the women shaping the future of technology, media, and telecom.

Website link: https://fiberconnect.fiberbroadband.org/

Attending from eClerx

Robert Schwietz

Vice President of Global Business Development

eClerx

April Valentino

VP of Global Business Development

eClerx

AI alone won’t transform your business

AI has become table stakes in digital commerce, with nearly every organization now using AI-driven analytics, automation, or predictive tools to monitor performance, optimize pricing, and personalize experiences. Despite this, many businesses are still struggling to convert their AI investments into sustained growth, consistent execution, and durable competitive advantages for their brand.

The reason behind this is simple but uncomfortable: AI alone does not transform businesses. It accelerates them.

To embrace true transformation, digital commerce brands shouldn’t only look dashboards, models, or automation in isolation. Providing a system that continuously turns market signals into decisions, decisions into actions, and actions into measurable outcomes, Market Intelligence is the missing key that can prevent these AI initiatives from stalling out.

In this white paper, eClerx’s Marketing Intelligence and AI experts outline what specifically is going wrong with many AI transformations within digital commerce operations, and how Market Intelligence operating modes can enable these organizations to scale revenue, protect margins, and execute with confidence in an increasingly complex online market.

AI Isn’t the Problem. Your Operating Model Is.

AI is everywhere in digital commerce. From pricing and promotions to content optimization and demand forecasting, organizations have invested heavily in AI-driven tools to improve performance across the digital shelf. The expectation was that better technology would lead to better outcomes.

For many teams however, that hasn’t happened; growth is still inconsistent, execution is still slow, and teams still spend more time debating data than acting on it. Despite more sophisticated tools, the gap between insight and impact remains.

This is because AI in itself was never the fix. Instead, it’s the amplifier of what is currently being executed.

The uncomfortable truth about AI in eCommerce

The uncomfortable reality is that AI doesn’t transform businesses, it accelerates them. If the underlying operating model is fragmented, misaligned, or disconnected from how decisions actually get made, AI simply helps organizations move faster in the wrong direction.

We’ve noticed that most organizations are currently fragmented:

• Pricing decisions happen in isolation
• Content updates lag behind demand signals
• Channel teams operate independently
• Data exists everywhere but alignment exists nowhere

This creates a dangerous environment as teams appear to be optimizing performance, but in reality they are optimizing in isolation.

Why digital shelf performance still breaks down

The impact of this disconnect can be seen in everyday scenarios:

• A pricing model recommends lowering price without factoring in MAP exposure
• A keyword opportunity is flagged but the product is out of stock
• Content scores look complete but conversion still lags

In each case, the insight is technically correct but not actionable.

Rather than a failure of AI, it’s a failure of the operating model around it.

Dashboards alone don’t grow revenue

Over the past several years, organizations have built increasingly complex digital stacks, including layering analytics platforms, automation tools, and AI models across every part of the customer journey. The result is more visibility than ever before, but not necessarily better decisions.

Because dashboards don’t grow revenue. Decisions do.

Decisions only improve when insights are prioritized, contextualized, and embedded into the way teams actually work. Without that data becomes noise, making teams hesitate, overanalyze, or pursue actions that look right in theory but fail in execution.

Market Intelligence as a system

What leading organizations have recognized is that the real advantage doesn’t come from AI alone. It comes from how AI is operationalized.

Instead of treating analytics as reporting, they treat it as a system that continuously connects market signals to decisions, and decisions to execution. This system captures what’s happening across the digital shelf, interprets those signals in the context of real commercial constraints, translates them into prioritized actions, and measures the impact to improve future decisions.

This is what Market Intelligence actually looks like in practice. Not a collection of dashboards for the sake of dashboards, but a repeatable decision engine.

It only works when three elements operate together: technology, industry expertise, and operating discipline. Remove any one of them and the system breaks.

Key takeaway – lead with the operating model

The shift that separates high-performing teams from everyone else is subtle but powerful. It’s the move from asking, “What does the data say?” to answering, “What should we do next and how do we execute it?”

This shift reduces friction between teams, accelerates decision-making, and ensures that insights actually translate into measurable outcomes.

AI exposes what was already broken. Fix your operating model and suddenly AI starts driving the kind of impact it always promised.

Turning AI into impact

What does fixing the operating model actually look like in practice?

If AI is the amplifier, then what you need is a system that ensures it’s amplifying the right things.

eClerx’s AI-powered approach is built around a Market Intelligence framework that goes beyond dashboards and isolated automation.

By using agentic AI systems (spanning monitoring, decision-making, execution, and feedback) it creates a continuous loop that connects signals to action across the digital shelf.

Instead of surfacing more insights, it orchestrates what actually matters:

• What’s changing in your market
• Why it matters commercially
• What action to take next and how to execute it

This is how organizations move from fragmented AI initiatives to a fully operationalized system that drives visibility, conversion, and margin.

The Future Is Automation Combined with Expertise

The digital shelf is no longer a static display. It’s a dynamic engine of growth.

Winning in this environment requires more than intelligence. It requires the ability to act on that intelligence with consistently and at scale.

Organizations that combine AI automation with industry expertise and operating discipline won’t just react faster. They’ll lead.

If your AI isn’t driving outcomes, this is where to start.

Watch the on-demand webinar: AI-Powered eCommerce: Optimize and Win