People, Processes & Applications Archives - Gigaom

GigaOm Key Criteria for Evaluating Primary Storage Solutions

Whit Walters — Thu, 19 Dec 2024 18:31:05 +0000

Primary storage has evolved significantly beyond its traditional role of structured data management. Today’s solutions must address a complex array of enterprise requirements that span on-premises, cloud, and edge environments. While continuing to provide the persistent block storage that serves as the foundation for mission-critical applications and databases, modern primary storage systems are increasingly called upon to support emerging workloads like artificial intelligence (AI) and machine learning (ML).

Organizations across industries depend on primary storage to support their most critical business operations, from processing financial transactions to powering customer-facing applications. As the technology has matured, solutions now offer sophisticated data services, automation capabilities, and integration features that extend far beyond basic storage functions.

The modern storage infrastructure landscape presents several key imperatives for organizations. They must support an increasingly diverse mix of workloads while meeting stringent environmental sustainability targets. Data mobility across different environments needs to be seamless, even as organizations strengthen their defenses against ransomware and other cybersecurity threats. All of this must be accomplished while maintaining cost efficiency in the face of relentless data growth and simplifying operations through increased automation.

Business Imperative
For CxOs, primary storage represents both a critical operational requirement and a strategic investment. Modern solutions must deliver beyond traditional metrics of performance and capacity to support key business initiatives. Organizations now demand storage solutions that can accelerate digital transformation efforts while meeting environmental, social, and governance (ESG) goals through improved efficiency. These systems must enable AI/ML and analytics initiatives while ensuring business continuity and cyber resilience. Additionally, they need to optimize infrastructure costs and provide robust support for hybrid and multicloud strategies.

The stakes are high, as primary storage decisions can significantly impact an organization’s ability to innovate, compete, and operate efficiently in today’s data-driven business environment. Organizations must carefully evaluate solutions that meet their current needs and provide the flexibility and capabilities to support future growth and emerging technologies.

Sector Adoption Score
To help executives and decision-makers assess the potential impact and value of deploying a primary storage solution, this GigaOm Key Criteria report provides a structured assessment of the sector across five factors: benefit, maturity, urgency, impact, and effort. By scoring each factor based on how strongly it compels or deters adoption of a primary storage solution, we provide an overall Sector Adoption Score (Figure 1) of 4 out of 5, with 5 indicating the strongest possible recommendation to adopt. This indicates that a primary storage solution is a credible candidate for deployment and worthy of thoughtful consideration.

The factors contributing to the Sector Adoption Score for primary storage are explained in more detail in the Sector Brief section that follows.

Key Criteria for Evaluating Category Solutions

Sector Adoption Score

Deters
Adoption

Discourages
Adoption

Merits
Consideration

Encourages
Adoption

Compels
Adoption

Figure 1. Sector Adoption Score for Primary Storage

This is the fifth year that GigaOm has reported on the primary storage space in the context of our Key Criteria and Radar reports. This report builds on our previous analysis and considers how the market has evolved over the last year.

This GigaOm Key Criteria report highlights the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) for selecting an effective primary storage solution. The companion GigaOm Radar report identifies vendors and products that excel in those decision criteria. Together, these reports provide an overview of the market, identify leading primary storage offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.

GIGAOM KEY CRITERIA AND RADAR REPORTS

The GigaOm Key Criteria report provides a detailed decision framework for IT and executive leadership assessing enterprise technologies. Each report defines relevant functional and nonfunctional aspects of solutions in a sector. The Key Criteria report informs the GigaOm Radar report, which provides a forward-looking assessment of vendor solutions in the sector.

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Seth Byrnes

Seth Byrnes — Tue, 12 Nov 2024 20:37:18 +0000

Seth Byrnes has extensive experience in developing strategic roadmaps, implementing robust technology solutions, and leading cross-functional teams to drive operational excellence.

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CEO Podcast – with James Winebrenner of Elisity

Ben Book — Tue, 29 Oct 2024 17:00:15 +0000

GigaOm’s Ben Book sits down with Elisity CEO James Winebrenner to discuss leadership and building a company in the tech industry.

The post CEO Podcast – with James Winebrenner of Elisity appeared first on Gigaom.

Driving AI Transformation

Howard Holton — Wed, 23 Oct 2024 21:10:29 +0000

As we head into 2025, CEOs are focused on a clear set of priorities—AI-enabled growth, dynamic capacity, risk management, and human-machine integration. Yet, many CIOs are still too focused on managing IT infrastructure and not stepping into their rightful role as strategic advisors. To meet the needs of today’s CEO, the CIO must transform from a technology manager into a leader who drives digital business transformation. This shift isn’t just about adopting AI; it’s about aligning technology with the larger business strategy, creating value, and managing the balance between innovation and risk.

Here are the key actions CIOs should take to ensure they’re not just managing IT, but actively enabling their organizations to grow, innovate, and transform in 2025 and beyond.

1. Build AI Literacy and Trust Within IT First

The first step in leading AI transformation is starting within your own organization. CIOs should focus on building AI literacy programs within their IT teams, ensuring they have a solid understanding of what AI can do and how it applies to their work. This is where quick wins come into play—focus on immediate pain points within IT, such as improving operational efficiency or automating repetitive tasks, to deliver fast results. These early wins will create internal champions who can advocate for AI, helping spread the message across the organization.

Ask Yourself: Am I starting with quick, high-impact AI initiatives within my own team that can demonstrate real value? Have I identified the internal champions who will sell the success of these initiatives to their peers?

“AI isn’t just a tool—it’s your path to transformation. If you’re still managing technology, you’re missing the point.”

2. Win Hearts and Minds by Making AI Personal and Measurable

To ensure sustained AI adoption across the business, CIOs must focus on making the workday easier for employees. Every AI initiative should have two clear outcomes: personal impact on employees and quantifiable data for leadership. By showing how AI simplifies tasks or enhances productivity for individuals, while simultaneously delivering metrics that prove its impact, CIOs can win over both employees and leadership. This balance avoids the risk of AI feeling like “big brother” and ensures that AI is seen as a value-add, not a threat.

Ask Yourself: Are my AI projects producing measurable business value while also making a positive difference in employees’ daily work? Am I balancing these two outcomes to ensure broad adoption and trust?

3. Start with Existing Problems to Drive Dynamic Capacity

When it comes to AI-enabled dynamic capacity, the key is to start where the company’s current bottlenecks are. Whether it’s production outpacing logistics, supply chain inefficiencies, or gaps in customer service, target the areas where problems already exist. By using AI and automation to solve these issues, CIOs can deliver immediate value that resonates across the business. Once that first problem area is resolved, the ripple effects will spread, allowing you to expand AI adoption gradually, eventually moving the entire operational chain from data-informed to data-driven decision-making.

Ask Yourself: Am I focusing AI efforts on the biggest pain points in the business today? Have I built a feedback loop to expand AI and automation from these problem areas out to the rest of the organization?

4. Keep Human Oversight Until Trust is Earned

The shift from data-informed to fully data-driven decision-making doesn’t happen overnight. It requires building trust in the data. Until teams trust the data enough to follow its guidance without hesitation, human oversight is essential. Once you reach the point where the organization consistently relies on data and follows AI’s lead without doubts or complaints, you can start to introduce more prescriptive AI models. This gradual shift ensures the transition is smooth and minimizes resistance.

Ask Yourself: Is my team ready to trust AI and data-driven decisions, or do we need more time with human oversight to build confidence? How can I help foster that trust through smaller wins?

5. Collaborate with HR to Lead the Human-Machine Workforce

Integrating AI into the workforce is a delicate balance, and collaborating with HR is critical to success. CIOs must build a strong relationship with HR leaders, focusing on creating AI literacy programs for the broader organization and preparing for a human-machine workforce integration. By aligning early with HR, CIOs can co-lead this transition, ensuring it’s done thoughtfully and with employee trust at its core. The focus here should be on building trust first, so that when it’s time for transformation, both sides are ready to lead together.

Ask Yourself: Have I built a strong relationship with HR to co-lead AI-driven workforce changes? Am I preparing the organization for this integration before it becomes an imperative?

6. Lay the Foundation with Accurate, Trustworthy Data

For AI and dynamic capacity to succeed, data is king. Moving from a fixed to dynamic capacity model requires accurate, timely, and trustworthy data. One of the first steps in this process is establishing a standardized lexicon of business terms and data definitions across the company. There should be one definition of a sale, a customer, or an employee. With a unified understanding of these core metrics, the organization can then scale AI and automation initiatives with confidence.

Ask Yourself: Is my organization’s data consistent and trustworthy? Have we established a common language across the business to ensure that AI initiatives are built on a strong foundation?

7. Balance Innovation with Security from the Start

Security should never be an afterthought. In the rush to innovate and adopt AI, security must be considered before defining or quantifying the value of any project. This means working closely with the CISO from the beginning to ensure security is a core component of every AI and automation effort. By reducing friction between IT and cybersecurity teams and presenting a unified front, CIOs can streamline innovation while ensuring the organization remains protected.

Ask Yourself: Is security baked into my AI and data initiatives from the outset? Am I working closely with the CISO to reduce friction and create a seamless, secure environment for innovation?

8. Scale AI Adoption by Creating an Executive Steering Committee

Once you’ve gained momentum from smaller wins, it’s time to scale. As leaders see the success of early AI initiatives, they’ll naturally be more willing to commit to larger projects. At this point, CIOs should create an executive steering committee, comprised of key decision-makers from across the organization. This committee will help prioritize AI initiatives based on cost/benefit analysis and will ensure that future projects have executive buy-in from the start. Keep the group small, focusing on CIO peers and those who can actively contribute.

Ask Yourself: Do I have the right executive steering committee in place to help scale AI initiatives? Am I leveraging the early success of AI projects to build further momentum across the leadership team?

Conclusion

The role of the CIO is evolving, and CEOs are looking for leaders who can drive AI transformation, build dynamic capacity, and manage the shift toward a human-machine workforce. By focusing on small, personal wins, building trust in data, and collaborating closely with HR and cybersecurity, CIOs can lead their organizations through these complex transformations with confidence.

If you’re unsure how to take these steps or need guidance on how to align your AI initiatives with CEO priorities, my team and I are here to help. We have the experience to guide you through the process, ensuring your organization is set up for success and that you’re positioned as a trusted advisor at the executive table.

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The Modern CIO

Howard Holton — Wed, 23 Oct 2024 14:26:26 +0000

At the recent Gartner Symposium, there was no shortage of data and insights on the evolving role of the CIO. While the information presented was valuable, I couldn’t help but feel that something was missing—the real conversation about how CIOs can step into their role as true agents of transformation. We’ve moved beyond the days of simply managing technology; today, CIOs must be enablers of business growth and innovation.

Gartner touched on some of these points, but I believe they didn’t go far enough in addressing the critical questions CIOs should be asking themselves. The modern CIO is no longer just a technology steward—they are central to driving business strategy, enabling digital transformation, and embedding technology across the enterprise in meaningful ways.

Below is my actionable guide for CIOs—a blueprint for becoming the force for innovation your organization needs. If you’re ready to make bold moves, these are the steps you need to take.

1. Forge Strong, Tailored Relationships with Each CxO

Instead of approaching each CxO with the standard “tech equals efficiency” pitch, CIOs should actively engage with them to uncover deeper business drivers.

CFO: Go beyond cost management. Understand the financial risks the company faces, such as cash flow volatility or margin pressures, and find ways technology can mitigate these risks.
COO: Focus not just on operational efficiency but on process innovation—how can technology fundamentally change how work gets done, not just make it faster?
CMO: Delve into the customer journey and experience. Understand how technology can be a key differentiator in enhancing customer intimacy or scaling personalization efforts.
CHRO: Understand their challenges in talent acquisition and employee engagement. How can technology make the workplace more attractive, productive, and aligned with HR strategies to develop talent?
Product/BU Leaders: Work closely to drive product innovation, not just from a technical perspective but to discover how technology can create competitive advantages or new revenue streams.

Ask Yourself: Do I truly understand what drives each of my CxOs at a strategic level, or am I stuck thinking in tech terms? If I don’t have the insight I need, what steps can I take to get there—and am I leveraging external expertise where needed to fill the gaps?

2. Prioritize Based on Shared Commitment and Strategic Value

Not all CxOs will be equally engaged or ready to partner closely with the CIO, but this should influence prioritization. CIOs should assess:

CxO Commitment: Is the CxO fully bought into digital transformation and willing to invest time and resources? If they aren’t, start with those who are.
Technology Team Enthusiasm: Does the ask from the CxO spark excitement within the technology team? If the IT team can see the challenge as an inspiring and innovative project, prioritize it.
Potential for Broader Impact: Will this initiative create a success story that can inspire other parts of the business? Choose projects that not only solve immediate problems but also demonstrate value to other BUs.
Business Impact: Does this move the needle enough? Focus on projects that are impactful enough to gain visibility and drive momentum across the organization.

Ask Yourself: Am I working with the most committed and strategic partners, or am I spreading myself thin trying to please everyone? How can I ensure my efforts focus on high-impact initiatives that inspire others? If I’m not sure which projects have this potential, who can I turn to for a fresh perspective?

3. Develop a Communication Strategy to Be the Executive Team’s Trusted Advisor

The CIO needs to craft a communication strategy to regularly update the C-suite on what’s happening in technology, why it matters, and—most importantly—how it applies to their specific business challenges. This is not about sending generic updates or forwarding research articles.

Provide insights on emerging trends like AI, automation, or cybersecurity, and explain how they can solve real problems or create real opportunities for their business.
Create a visionary narrative that places your company at the forefront of industry evolution, emphasizing how specific technologies will help each CxO achieve their goals.

Ask Yourself: Do I have a proactive communication strategy that positions me as the go-to advisor for technology insights within the C-suite? Am I demonstrating how technology directly impacts their business outcomes? If I’m struggling to create this narrative, who can help me fine-tune it?

4. Champion Digital Experience (DX) and Build KPIs Around Adoption and Value

While the CIO doesn’t need to own the day-to-day design conversations, they must champion the importance of digital experience (DX) and ensure that it’s a KPI across the company. Build a culture where every digital initiative is measured not just by completion, but by how well it’s adopted and how it sustains value over time.

Ensure KPIs include sustained usage, not just launch metrics.
Build Management by Objectives (MBOs) that tie DX and adoption rates into performance metrics for teams using the tools, ensuring continuous focus on the user experience.

Ask Yourself: Am I setting the right metrics to measure the long-term success of digital initiatives, or am I just tracking short-term implementation? How can I establish sustained adoption as a core business KPI? And if I don’t have a strong framework in place, who can help me build it?

5. Cultivate Multidisciplinary Fusion Teams with Curious, Collaborative Members

Create multidisciplinary fusion teams where business and IT collaborate on solving real business problems. Initially, look for those who are naturally curious and collaborative—people who are eager to break down silos and innovate. As you scale, formalize selection processes but ensure that it doesn’t become a bureaucratic process. Encourage progress-driven contributions, where results are measured and where teams feel empowered to iterate, rather than meet to discuss roadblocks endlessly.

Ask Yourself: Am I identifying the right people to drive multidisciplinary collaboration, or am I waiting for teams to form on their own? Are my teams making progress, or are they stuck in meetings that don’t lead to results? Who can I consult to get these teams moving in the right direction?

6. Be the Early Advocate for Emerging Technologies

Emerging technologies like AI, automation, and low-code/no-code platforms are already enterprise-ready but often fail due to a lack of understanding of how to drive real business value. CIOs must be early advocates for these technologies, preparing the organization to adopt them when they’re at the right point on the maturity curve. This prevents shadow IT from adopting technologies outside the CIO’s purview and ensures that IT is seen as an enabler, not an obstacle.

Ask Yourself: Am I advocating for emerging tech early enough, or am I waiting too long to act? How can I ensure the organization is ready when the technology hits the right maturity curve? If I’m unsure where to start, who can help me assess our readiness?

7. Foster a Culture of Cross-Functional Digital Leadership

Create an organic ecosystem where IT leaders move into business roles and business leaders spend time in IT. This exchange creates a more integrated understanding of how technology drives value across the business. Work with HR to launch a pilot exchange program with a willing BU, and ensure that this doesn’t become another bureaucratic initiative. Instead, keep it agile, fast, and focused on creating leaders who are equally strong in tech and business.

Ask Yourself: Am I fostering an agile and collaborative environment where digital leadership can flourish across functions? Or are we too siloed in our thinking? If I need guidance on how to get this started, who should I bring in to help make it happen?

8. Align Technology Outcomes with Clear Business Goals

Every tech project must have clear business goals and measurable metrics that matter to the business. Don’t aim for perfection—aim for progress. Track and report metrics regularly to keep the project’s business value visible to stakeholders.

Ask Yourself: Are all my technology projects aligned with clear business goals, and do I have the right metrics in place to measure their impact? If I don’t have a process for this, what support do I need to create one that works?

9. Track Adoption and Engagement Metrics Beyond the Initial Rollout

Adoption isn’t just about getting users on board for launch—it’s about measuring ongoing engagement. CIOs should track:

Satisfaction rates: How do users feel about the tool or platform over time?
Improvement metrics: Are there measurable improvements in efficiency, productivity, or revenue tied to the tech?
Feature requests: How often do users ask for new features or enhancements?
Number of users/BU’s using the platform: Track growth or stagnation in usage across teams.
New projects spawned from existing tech: What new initiatives are being created because of successful platform use?

Ask Yourself: Am I tracking the right metrics to measure long-term success and adoption, or am I too focused on the initial rollout? If I’m unsure of how to keep engagement high, who can I turn to for expert advice on optimizing these KPIs?

Transformation doesn’t happen by chance, and it won’t happen if CIOs stay in the background, waiting for others to drive change. It requires intentional, strategic action, a commitment to aligning technology with business outcomes, and a willingness to ask the tough questions. The steps I’ve outlined are designed to challenge your thinking, help you prioritize where to focus your efforts, and ensure you’re seen as a leader, not just a technologist.

If you’re unsure how to move forward or need guidance in turning these insights into action, remember that you don’t have to go it alone. My team and I have worked with CIOs across industries to turn complex challenges into strategic advantages, and we’re here to help. Becoming an agent of transformation starts with taking that first step—and we’re ready to walk with you through the journey.

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CEO SPEAKS with Gleb Budman of Backblaze

Ben Book — Tue, 22 Oct 2024 16:30:44 +0000

GigaOm’s Ben Book sits down with Backblaze CEO Gleb Budman to discuss tech leadership and growth in the industry today.

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GigaOm Radar for Intelligent Document Processing (IDP)

Dana Hernandez — Fri, 18 Oct 2024 15:00:30 +0000

Intelligent document processing (IDP) solutions enable the transformation of documents (both paper and electronic) containing unstructured, semistructured, and structured data into digital assets quickly and accurately. IDP solutions use AI/ML, plus natural language processing (NLP) and deep learning, to improve data extraction accuracy and enable faster processing.

IDP solutions involve pre-processing and post-processing stages: the first primes the document in terms of shape and size, and the second ensures that a substantial degree of accuracy in processing unstructured data can be achieved.

The availability of AI/ML/NLP capabilities in IDP ensures that the strike rate in processing data is significantly higher than what a mere optical character recognition (OCR) tool can deliver. AI/ML/NLP features have self-training, self-learning capabilities that lead to continuous improvement in the accuracy of processing all types of documents.

Prebuilt AI/ML capabilities and business rules enable automated verification and validation of data as well as continuous learning and improvements based on AI/ML algorithms and user input. IDP combines OCR, data capture, and AI/ML to automate the retrieval, understanding, and integration of documents required for executing a business process. Know your customer (KYC), invoice processing, insurance claims, patient onboarding, patient records, proof of delivery, bills of lading, and commercial order forms are some of the key use case processes and document types suited for IDP solutions. IDP can also be useful for industry-specific processes, such as customer onboarding, mortgage processing, financial trading, and legal proceedings. Some of the key buyers of IDP solutions are leaders in a variety of business areas: shared services, process automation CoE, global business services (GBS), digital transformation, and finance.

Decision-makers will want to determine the specific requirements of their organization to use as a baseline for assessing the features they need in an IDP solution. Some solutions offer prebuilt processes supporting specific industries, which can speed the implementation of the solution. In contrast, some IDP solutions offer a template-free approach and can be trained on new document types and layouts by using sample documents; such solutions will usually deliver greater value at a lower cost. IDP solutions should be adopted as part of a broader enterprise automation strategy in which suitable software products are used for meeting various task, process, and document automation requirements.

There are more than 60 vendors that provide IDP-type capabilities. In this GigaOm Radar report, we focus only on vendors with a noteworthy footprint in terms of scaled IDP implementations for which the IDP product involves more than an add-on to a broader robotic process automation (RPA) or intelligent automation platform. We excluded vendors whose solutions were more service based as well as those that offer basic OCR-based document capture without significant advancement in AI/ML capabilities.

This is our third year evaluating the IDP space in the context of our Key Criteria and Radar reports. This report builds on our previous analysis and considers how the market has evolved over the last year.

This GigaOm Radar report examines 18 of the top IDP solutions and compares offerings against the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) outlined in the companion Key Criteria report. Together, these reports provide an overview of the market, identify leading IDP offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.

GIGAOM KEY CRITERIA AND RADAR REPORTS

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CEO SPEAKS With Sandeep Johri of Checkmarx

Ben Book — Tue, 15 Oct 2024 14:54:08 +0000

GigaOm’s Ben Book sits down with Sandeep Johri, CEO of Checkmarx to discuss business leadership and development in tech spaces.

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GigaOm Radar for E-Discovery

Sue Clarke — Mon, 14 Oct 2024 15:00:31 +0000

Organizations can face new litigation or discovery requests under regulations like GDPR at any time. Discovery must be undertaken in a timely fashion, and the ability to undertake an early case assessment (ECA) will allow counsel and courts to determine whether a matter is worth pursuing or if a settlement should be sought.

Without an e-discovery solution, it’s time consuming and expensive to find the right digital data assets among the millions of items that enterprises have stored. Often, the volume of the final dataset is not known at the start of the project, and so-called “smoking guns,” or relevant items of information that no one knew existed, may be discovered during litigation, landing the organization in trouble and resulting in larger fines or settlements.

For that reason, it’s in the best interest of organizations to have an e-discovery solution already in place when a request is received. This proactive measure allows organizations the time to properly compare solutions well before the need for one becomes critical, ensuring they invest in a solution that best meets their requirements.

E-discovery solutions accelerate the search for and retrieval of assets. The increasing use of automation for tasks such as review, redaction, and tagging reduces the manual effort required and helps deliver depositions to opposing counsel, a court, or regulator in a shorter time frame. By helping organizations to address access requests and prepare for litigation more quickly, e-discovery solutions can also reduce the cost of the e-discovery process.

E-discovery solutions follow the electronic discovery reference model (EDRM), a framework that defines all of the stages of e-discovery, from identifying needed data to presenting it to a court. Some solutions provide end-to-end capabilities, while others stick to either the initial stages (identification, preservation, collection, and processing) or the later stages of the model (review, analysis, production, and presentation).

There are two distinct audiences that e-discovery software must support: organizations that undertake the initial searches for data that may be relevant to a case or matter, and legal teams—either legal departments within large enterprises or law firms—responsible for reviewing and putting together the final dataset of content.

This is our third year evaluating the e-discovery space in the context of our Key Criteria and Radar reports. This report builds on our previous analysis and considers how the market has evolved over the last year.

This GigaOm Radar report examines 19 of the top e-discovery solutions and compares offerings against the capabilities (table stakes, key features, and emerging features) and nonfunctional requirements (business criteria) outlined in the companion Key Criteria report. Together, these reports provide an overview of the market, identify leading e-discovery offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.

GIGAOM KEY CRITERIA AND RADAR REPORTS

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Digital Experience Platforms: Transforming Marketing in the 21st Century

Sue Clarke — Tue, 01 Oct 2024 17:32:10 +0000

In today’s fast-paced digital landscape, creating engaging and personalized customer experiences is paramount to business success. Enter digital experience platforms (DXPs)—powerful systems designed to revolutionize how companies interact with their audiences across various digital channels. Let’s dive into the fascinating world of DXPs and explore how they are reshaping marketing strategies.

The Genesis of Digital Experience Platforms

The roots of DXPs can be traced back to the late 1980s when the World Wide Web emerged. Initially, websites were static, providing information that didn’t change. However, by the late 1990s, the development of the Document Object Model (DOM) allowed content updates, albeit still requiring developer intervention.

Fast forward to the turn of the century, and web content management (WCM) vendors began offering solutions for creating and centrally managing multiple websites. These platforms allowed non-technical users to publish content dynamically using templates. However, true interactivity was still limited.

Limited analytics allowed marketers to gather basic customer data from website engagements including the journey through the website, key clicks, abandoned visits, and the route to a sale, enabling marketers to make offers based on pages viewed. Aggregating this data provided the number of hits per page, most and least popular pages, and patterns in abandoned visits—a sign that the site had an issue. Limited customer profiles were possible for known visitors, enabling personalization at a basic level.

A/B testing was another innovation during this time, allowing marketers to experiment with different content variations to discover which was the most successful and likely to produce the most sales.

From Web Content Management to Digital Experience Platforms

Many WCM solutions became part of larger enterprise content management (ECM) portfolios of content management solutions. However, by 2015, these mega-platforms had become too big and unruly to implement and manage easily, so the vendors started to break them down, separating their WCM solutions. Within a few years, DXP was born.

Here’s what sets DXPs apart:

Holistic customer experiences: DXPs go beyond website management. They enable seamless experiences across all digital touchpoints, including websites, mobile apps, social media, and more. Marketers can create consistent, personalized journeys for users, enhancing brand loyalty and engagement.

Headless architecture: DXPs embrace a headless approach, separating content from the application layer. Content becomes reusable and can be delivered to multiple channels and devices, ensuring flexibility and scalability.

Data-driven insights: DXPs collect valuable data on user behavior, preferences, and interactions. Marketers gain insights to tailor content, optimize campaigns, and drive conversions.

Content creation and collaboration: DXPs empower both creative teams and marketers to create and publish content effortlessly. Intuitive interfaces allow rapid content development and deployment.

The Power of Personalization

DXPs enable hyper-personalization. Imagine a user visiting your website—a DXP can dynamically serve content based on their past interactions, preferences, and demographics.

Here’s how DXPs enhance personalization:

Segmentation and targeting: DXPs analyze user data to create segments (by interests, location, or behavior, for example). Targeted content resonates better with specific audiences.

A/B testing: Marketers experiment with different content variations to identify what resonates best. DXPs provide insights into which version drives more engagement or conversions.

Real-time optimization: DXPs adapt content in real time based on user behavior. Imagine a personalized homepage that changes as the user navigates.

2024 Is the Year of GenAI

DXPs continue to evolve, integrating AI, machine learning, and omnichannel capabilities. Last year, many vendors experimented with GenAI to generate text and images from written instructions. The next 12 months will be the year of implementing the technology for business benefits in areas like process automation, conversational assistants that can perform tasks dynamically, and interacting with IoT devices to react to real-time events to ensure optimized performance.

As businesses strive to deliver exceptional digital experiences, DXPs will remain at the forefront of marketing transformation.

Navigating the Future with Headless DXPs

As enterprises sail through the ever-changing tides of technology, one thing is clear: future-proofing is essential. Therefore, a DXP should be on the shopping list of every business that wants to create personalized experiences across various channels. Let’s chart our course and explore what enterprises should do to stay ahead:

Embrace headless DXPs: Headless architecture is the compass guiding modern DXPs. It separates content from presentation, allowing flexibility and scalability. With a headless DXP, content resides in a repository, ready to be reused across multiple channels and applications.

Build roadmaps and have strategy discussions: Engage in candid conversations with DXP vendors. Explore their roadmaps and product development plans. Understand their vision for the future. Are they aligning with emerging technologies? Look for clarity and transparency.

Follow the AI North Star: Seek vendors that infuse AI into their DXPs. Imagine predictive analytics, personalized recommendations, and automated content delivery—all powered by AI.

Dive into use cases: How can a headless DXP benefit your enterprise? Picture seamless customer journeys, dynamic content delivery, and real-time personalization.

In summary, set sail with a headless DXP, navigate strategic discussions, and keep an eye on AI innovations. The horizon is bright, and the journey promises transformative experiences for your enterprise.

Next Steps

To learn more, take a look at GigaOm’s DXP Key Criteria and Radar reports. These reports provide a comprehensive overview of the market, outline the criteria you’ll want to consider in a purchase decision, and evaluate how a number of vendors perform against those decision criteria.

If you’re not yet a GigaOm subscriber, sign up here.

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People, Processes & Applications Archives - Gigaom

GigaOm Key Criteria for Evaluating Primary Storage Solutions

Key Criteria for Evaluating Category Solutions

Sector Adoption Score

DetersAdoption

DiscouragesAdoption

MeritsConsideration

EncouragesAdoption

CompelsAdoption

GIGAOM KEY CRITERIA AND RADAR REPORTS

Seth Byrnes

CEO Podcast – with James Winebrenner of Elisity

Driving AI Transformation

1. Build AI Literacy and Trust Within IT First

“AI isn’t just a tool—it’s your path to transformation. If you’re still managing technology, you’re missing the point.”

2. Win Hearts and Minds by Making AI Personal and Measurable

3. Start with Existing Problems to Drive Dynamic Capacity

4. Keep Human Oversight Until Trust is Earned

5. Collaborate with HR to Lead the Human-Machine Workforce

6. Lay the Foundation with Accurate, Trustworthy Data

7. Balance Innovation with Security from the Start

8. Scale AI Adoption by Creating an Executive Steering Committee

Conclusion

The Modern CIO

1. Forge Strong, Tailored Relationships with Each CxO

2. Prioritize Based on Shared Commitment and Strategic Value

3. Develop a Communication Strategy to Be the Executive Team’s Trusted Advisor

4. Champion Digital Experience (DX) and Build KPIs Around Adoption and Value

5. Cultivate Multidisciplinary Fusion Teams with Curious, Collaborative Members

6. Be the Early Advocate for Emerging Technologies

7. Foster a Culture of Cross-Functional Digital Leadership

8. Align Technology Outcomes with Clear Business Goals

9. Track Adoption and Engagement Metrics Beyond the Initial Rollout

CEO SPEAKS with Gleb Budman of Backblaze

GigaOm Radar for Intelligent Document Processing (IDP)

GIGAOM KEY CRITERIA AND RADAR REPORTS

CEO SPEAKS With Sandeep Johri of Checkmarx

GigaOm Radar for E-Discovery

GIGAOM KEY CRITERIA AND RADAR REPORTS

Digital Experience Platforms: Transforming Marketing in the 21st Century

The Genesis of Digital Experience Platforms

From Web Content Management to Digital Experience Platforms

The Power of Personalization

2024 Is the Year of GenAI

Navigating the Future with Headless DXPs

Next Steps

Deters
Adoption

Discourages
Adoption

Merits
Consideration

Encourages
Adoption

Compels
Adoption