Product-Led Revenue (PLR) applications enable brands to drive customer acquisition, engagement, and retention through their product. They encourage users to try, adopt, and ultimately pay for additional features or services based on their experience. The typical features include user engagement tracking, personalized experiences, and integration with sales and marketing tools to identify and nurture potential leads and opportunities for upselling or cross-selling. Focusing on the product as the main growth driver, these applications help product managers, marketers, sales teams, and customer success staff to scale efficiently, reduce sales costs, and build a customer-centric business.

Product-Led Revenue Applications

3D Print Service Bureaus

3D Printing Workflow Software

4G and 5G Private Mobile Network Services

4PLs

5G Enterprise Data Services

5G Network Infrastructure for Communications Service Providers (Transitioning to CSP 5G Core Network Infrastructure Solutions ; CSP 5G RAN Infrastructure Solutions)

A/B Testing Tools

AI Avatars

AI Code Assistants

AI Offerings in CSP Network Operations

AI and Data and Analytics (D&A) Service Providers

AI in CSP Customer and Business Operations

AI-Augmented Software-Testing Tools

AI-Enabled Interview Intelligence

AI-Enabled Translation Services

AIOps Platforms

API Management

API Protection

Absence Management Software

Access Management

Account-Based Marketing Platforms

Account-Planning Tools

Accounting Practice Management Software (APMS)

Accounts Payable (AP) Recovery Audit Services

Accounts Payable Invoice Automation Solutions (Transitioning to Accounts Payable Applications)

Active Metadata Management

Ad Tech Platforms

Ad Verification Tools

Adaptive Project Management and Reporting

Advanced Analytics Service Providers for Marketing

Advanced Contract Analytics

Advanced Distribution Management Systems

Affiliate Marketing Platforms

Alternative Legal Service Providers (ALSPs)

Analytics Query Accelerators

Analytics and Business Intelligence Platforms

Analytics and Decision Intelligence Platforms in Supply Chain

Anti Money Laundering (AML) Software

Applicant Tracking Systems (ATS) (Transitioning to 'Talent Acquisition (Recruiting) Suites')

Application Composition Platform

Application Crowdtesting Services

Application Delivery Controllers

Application Development Life Cycle Management

Application Integration Platforms

Application Platforms

Application Portfolio Management Tools

Application Security Posture Management (ASPM) Tools

Application Security Testing

Application Testing Services, Worldwide

Artificial Intelligence Applications in IT Service Management

Asset Investment Planning Solutions for Energy and Utilities

Asset Leasing Software

Asset Performance Management Software

Audience Intelligence Platforms

Audit Management Solutions

Augmented Analytics

Augmented Data Quality Solutions

Augmented Reality Development Software

B2B Customer Community Platforms

B2B Gateway Software

B2B Marketing Automation Platforms

B2B Profit Optimization Software

BPM-Platform-Based Case Management Frameworks

Background Check Software

Backup as a Service

Balance Sheet Management Software

Banking Payment Hub Platforms

Bankruptcy Software

Barcode Software

Benchmarking Services for Transportation Rates and Logistics Performance

Benefits Management Software

Blockchain Advertising Platforms

Blockchain Consulting and Proof-of-Concept Development Services

Blockchain Platforms

Blockchain as a Service

Brand Advocacy Services

Brand Compliance Software

Brand Protection Software

Brand Strategy Agencies

Breach and Attack Simulation (BAS) Tools

Business Continuity Management Program Solutions

Business Process Automation Tools

Business Process Management Platforms

Business Valuation Software

Business-Outcome-Driven Enterprise Architecture Consulting

CPS Protection Platforms

CRM Customer Engagement Center

CRM and Customer Experience Implementation Services

CRM in Life Sciences

CSP 5G Core Network Infrastructure Solutions

CSP 5G RAN Infrastructure Solutions

CSP Customer Management and Experience Solutions

CSP Revenue Management and Monetization Solutions

CSP Service Design and Orchestration Solutions

CSP Service and Network Assurance Solutions

Candidate Relationship Management (CRM) Software

Capital Investment Management Software

Carbon Accounting and Management Software

Carbon Offset Platforms

Cash Flow Management Software

1) Curious Mind. Leaders need to answer the WHY question. Why adopt such technology? What business outcomes are you trying to achieve?


2) Cross-Functional Approach. Often tech initiatives are IT-led which is the number one reason for poor ROI and lack of business value. Tech initiatives should be a cross-functional activity that involves the wider business. IT is just an enabler.


3) Technological Awareness: Leaders need to possess a strong understanding of emerging technologies, such as artificial intelligence, machine learning, automation, and data analytics. They should be able to grasp the potential impact of these technologies on their industry, business models, and operational processes.

4) Tech Literate. Leaders need to stay one step ahead and continuously scan the horizon for new tech that will impact business. Impact on revenue growth, cost optimisation, or risk mitigation. 


5) Ethical. With great power, comes great responsibility. Be aware of biased introduced by tech, privacy concerns, etc.


6) Partnerships. Leaders will need to build strategic partnerships with other organisations that supplement their offerings.


7) Risk Mitigation. Any new tech introduces new risks. Leaders need to assess the new risks and develop mitigation strategies.


These are some of the fundamental leadership capabilities needed to survive the non-stop innovation train!

Unless your company sells AI, you need to be able to develop partnerships and tell a story about value.  You'll never be staffed for emerging technologies, and you'll never have access to resources or data on other teams unless everyone understands the value.  I see leaders in ai and analytics as evangelists first with a small team of execution minded, team oriented people who are empowered to deliver product.

Well ... If you ask the question of ChatGPT one of the answers which you could get back is ....


In an era of exponential technology and AI innovation, leaders need to possess certain fundamental capabilities to navigate the rapidly changing landscape and effectively harness the potential of these advancements. Here are some essential leadership capabilities for this context:


1. Technological Literacy: Leaders must have a solid understanding of emerging technologies, such as artificial intelligence, machine learning, robotics, and automation. They should stay updated with the latest trends, developments, and potential applications of these technologies. This literacy enables leaders to make informed decisions, drive innovation, and effectively communicate with technical experts.


2. Adaptability and Agility: The pace of technological change demands leaders who can adapt quickly to new circumstances, embrace uncertainty, and lead with agility. They need to be open to learning, flexible in their thinking, and comfortable with experimentation. Embracing change and encouraging a culture of continuous learning and adaptation is crucial.


3. Strategic Vision: Leaders need to develop a clear and compelling vision for their organizations in the context of exponential technology and AI innovation. They should be able to anticipate future trends, identify new opportunities, and set strategic directions that leverage these technologies to drive growth and competitive advantage.


4. Ethical and Human-Centric Mindset: As technology continues to advance, leaders must prioritize ethical considerations and ensure that AI and other technologies are developed and deployed in a manner that aligns with human values and societal well-being. They should be committed to responsible innovation, addressing potential biases, privacy concerns, and the impact on jobs and society.


5. Collaboration and Team Building: Effective leaders understand the importance of collaboration and cross-functional teamwork. They foster an environment where diverse perspectives are valued, encourage interdisciplinary collaboration, and build teams that can work effectively with emerging technologies. Collaboration with external partners, such as startups, research institutions, and industry networks, also becomes crucial for accessing expertise and driving innovation.


6. Continuous Learning and Reskilling: Leaders must prioritize their own continuous learning and reskilling to keep up with the evolving landscape. They should encourage and support ongoing learning opportunities for their teams, enabling them to acquire new skills and competencies required in an era of AI and exponential technology. Lifelong learning becomes essential for leaders and their organizations to remain competitive.


7. Change Management and Transformation: The advent of AI and exponential technology often requires significant organizational change and transformation. Leaders must have strong change management capabilities to guide their teams through these transitions. They should be adept at inspiring and motivating employees, managing resistance to change, and creating a culture that embraces innovation and digital transformation.


8. Emotional Intelligence: As technology takes on more routine tasks, leaders need to focus on developing their emotional intelligence (EQ). EQ skills, such as empathy, self-awareness, and effective communication, become critical in leading diverse teams and fostering collaboration. Leaders who can understand and empathize with the impact of technology on individuals and address concerns will be more successful.


9. Risk Management: With the introduction of new technologies, leaders must be adept at assessing and managing risks effectively. They should be able to navigate the ethical, legal, and security challenges associated with AI and exponential technology. Balancing innovation with risk mitigation strategies becomes crucial to ensure responsible and sustainable deployment.


These fundamental leadership capabilities can empower leaders to navigate the complex and dynamic landscape of exponential technology and AI innovation, seize opportunities, and drive positive impact within their organizations and beyond.

You need to be able to determine what activity requires what skill.

Are you:


1/ In-sourcing
2/ Out-sourcing
3/ AI-sourcing

1/ In-sourcing

This is where you determine what activities are best carried out by a human as part of your team (think high-value revenue generating / cost reduction type activities)

2/ Out-sourcing

This is where you determine what activities are best carried out by a team overseas for a cheaper rate (think data entry, customer service, repetitive creative tasks)


3/ AI-sourcing

This is where you determine what activities are best carried out by AI (think high-level data analysis, virtual assistant jobs like meeting minutes, and basic admin activities like creating documentation)


Then scale from there.

In not too long we'll be thinking about 'hiring' AI in the same way we hire people.

That or the AIs will be thinking about how they hire humans ;)

Does this make sense?

1) willingness to write off sunk cost / past work in favor of things that are clearly superior, no matter how painful or unpopular

2) C-level mandate that every single person/department/function learns to fully embrace and leverage generative AI. Not optional. Not tomorrow or next week. Now.

3) Proper training, guard rails, governance, privacy and security rules etc. to ensure appropriate use of the tooling.

4) Focus on what makes your company and product special, and leave the plumbing to the hyperscalers and dedicated companies like OpenAI. Trying to compete with them or recreate what they have built is a distraction you do not want or need.

5) Accept that a tsunami of job losses is inevitable, and that new opportunities and jobs will soon follow. Prepare for the coming flood of layoffs and how you plan to manage through that. It won’t be pretty or pleasant. It will be swift, painful, and disruptive. We are already seeing the first wave of this in tech and that is just the tip of the iceberg.

Vision.


A major headwind in AI innovation is when the consumers and DS/AI products cannot understand it, refuse to adopt it, or fail to evolve their existing processes with it.



To take AI innovation across the finish line, it will require assessing organizational readiness, improving data literacy, and driving large scale philosophical changes in thinking and processes, especially in larger, older organizations. 


Is it the job of the leader to a envision the future state organization driven by Data/AI (beyond the model and product development), and most importantly, sell that vision to their data teams and downstream stakeholders. Otherwise, organizations will be hard-pressed to keep up.

Any large companies created "Digital" Teams and often they were not under the CIO org.  We saw the emergence of Chief Digital Officer (CDO not the Chief Data Officer) in some of the companies, to identify the new Digital revenue opportunities leveraging the emerging technologies like AI, IoT, Digital Twins, especially in the companies that have physical operations and are not purely services companies.  Such Digital teams, have the culture of experimentation and often looked at use of Digital Platforms as the building blocks for these new capabilities with monetization of data and insights in mind.

For me those organisations that are using the EXO2 methods are making strides in sustainable growth with the 6 D&#39;s.  
Digitisation: This refers to the process of converting analog information into digital format. It allows for easier storage, manipulation, and distribution of data. For example, the digitisation of music transformed the industry from physical CDs to digital streaming platforms like Spotify.


Deception: Deception occurs when exponential technologies are in their early stages and may not seem significant or disruptive. However, their impact grows exponentially over time. An example of deception is the early stages of electric vehicles, which were initially seen as inferior to traditional gasoline-powered cars but are now becoming more popular and disruptive.


Disruption: Disruption happens when exponential technologies reach a tipping point and fundamentally change an industry or market. Examples include the disruption of the taxi industry by ride-sharing platforms like Uber, or the disruption of the hotel industry by Airbnb.


Demonetisation: Demonetisation refers to the reduction or elimination of the cost of goods and services due to exponential technologies. This can make products or services more accessible and affordable. For instance, the cost of genome sequencing has dramatically decreased over time, enabling personalized medicine and healthcare.


Dematerialisation: Dematerialisation is the process of replacing physical products with digital or virtual alternatives. This allows for greater efficiency and reduces resource consumption. An example is the dematerialization of books into e-books, reducing the need for physical paper and printing.


Democratisation: Democratisation involves making resources, knowledge, and opportunities accessible to a broader audience. This allows for greater participation and empowerment. Examples include the democratization of education through online platforms like Khan Academy, or the democratisation of finance through crowdfunding platforms like Kickstarter.

What are the fundamental leadership capabilities that are needed for an era of exponential technology and AI innovation?

The highlight of my career was when I was made redundant a few years ago with a very good severance package. I was able to go out and self-fund the business that I&#39;m running now. That was probably my highlight because that doesn&#39;t happen every day. The lowlight of my career was some of the incidents that I used to get involved in as a major incident manager. I&#39;d be woken up at 3:00AM to deal with interbank payment issues.

What’s one highlight and one lowlight of your career so far?

Best Product-Led Revenue Applications Reviews 2024 | Gartner Peer Insights

Toplyne helps to increase product revenue by improving conversion rates based on customer behavior and actions. It enables sales and marketing to take relevant actions on each customer segment.

Toplyne

Amazing product and very easy and intuitive for us end users. It is very nice having Pocus pull all lists of users that are key focus across your book of business. 

Pocus

Calixa provides us strong capabilities to monitor and analyse product usage and anomalies. 

Product-Led Revenue Applications Reviews and Ratings

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Products In Product-Led Revenue Applications Category

Toplyne

Toplyne

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Calixa

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