Published January 13-21, 2024
1
The Third Way
The enterprise software industry has historically been dominated by two primary business models. The first is the traditional method where companies charge for their software, exemplified by giants like Microsoft, Adobe, SAP, and Oracle. This approach often involves significant upfront costs for purchasing the software, followed by periodic updates or maintenance fees.
The second prevalent model is service-based, where companies do not sell software products but instead offer their expertise to work on software projects. This model is typically represented by firms like Accenture, TCS, Infosys, and Wipro, where the focus is on charging for the time and expertise of their employees rather than a tangible software product.
However, over the past decade or so, a significant shift has occurred in the enterprise software landscape. The advent of Software as a Service (SaaS) has transformed the way software is sold and consumed. Unlike the traditional model of hefty upfront costs and on-premise installations, SaaS offers cloud-based software on a subscription basis, typically with monthly or annual payments. This approach not only makes software more accessible to a broader range of businesses but also provides a steady long-term recurring revenue stream for software providers. It aligns the interests of both providers and customers towards continuous improvement and support.
Despite these advancements, there remains an opportunity for a third, innovative business model in the enterprise software domain. This is where “Profishare” comes into play. Profishare is a concept that goes beyond the existing paradigms of selling software or services. Instead, it proposes a partnership model where software companies actively participate in the success of their clients’ businesses.
Under Profishare, a software company would generate new revenue streams by contributing directly to the incremental profits of their clients. Rather than charging a fixed fee or a standard subscription, the company would take a percentage of the additional profits generated as a result of using its software. This model creates a powerful alignment of interests, ensuring that the software company is directly invested in the success of its clients.
A practical example of this model could be seen in a “Martech Progency” – a hybrid of a product-led company and an agency. In this setup, the software company acts as both a product developer and a strategic partner. It provides not only the software but also the expertise and support to ensure that their clients can fully leverage the technology to improve their business performance.
This series aims to delve into the intricacies of the Profishare model, exploring its potential benefits and challenges. It will examine how this model can foster deeper collaborations between software providers and their clients, leading to more innovative solutions and shared success. Additionally, the series will showcase how a Martech Progency could serve as a blueprint for such an entity, illustrating the practical application of the Profishare model in a real-world scenario.
2
History
The history of how software has been sold and evolved over the past 50 years is a fascinating journey that mirrors the rapid advancements in technology and shifts in business strategies. I asked ChatGPT for a summary of how the industry has evolved.
Early Years (1970s and earlier): In the earliest days of computing, software was often bundled with hardware, with no separate charge for the software itself. This was because software was seen as an add-on to make the hardware useful, rather than a product in its own right. Mainframe manufacturers like IBM provided both the hardware and the necessary software, which was custom-written for specific applications.
Rise of Software Licensing (Late 1970s to 1980s): The late 1970s and 1980s saw the birth of the personal computer (PC), which marked a turning point. Companies began to see software as a standalone product. Microsoft and Apple were among the pioneers in selling software separately from hardware. Microsoft’s MS-DOS, an operating system, became one of the first widely successful standalone software products. Software licensing emerged as a model. Users would purchase a license to use the software, but not own the software itself. This was a shift from the hardware-centric model to a software-centric approach.
Expansion and Diversification (1990s): The 1990s witnessed an explosion in the variety and complexity of software available. This period saw the rise of Windows, Office suites, and many other productivity tools. Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems became popular, with companies like SAP, Oracle, and later Salesforce leading the way. Software was sold as packaged products in physical stores, and licenses were often for perpetual use.
Advent of the Internet and E-commerce (Late 1990s to 2000s): The internet revolutionised software distribution. Downloadable software became common, reducing the need for physical distribution. The late 2000s saw the beginning of the transition to cloud-based services and the Software as a Service (SaaS) model. Salesforce, with its CRM platform, was a trailblazer in this domain.
Dominance of SaaS and Cloud Computing (2010s onwards): The 2010s marked a significant shift towards SaaS. Companies like Adobe transitioned from perpetual licenses to subscription-based models. The SaaS model offers software on a subscription basis, usually with monthly or annual fees, and is accessible over the internet. This shift has made software more affordable and accessible to a wider range of businesses. Cloud computing also allowed for more scalable and flexible software solutions, changing the way businesses think about IT infrastructure.
Bard added: “In recent years, there has been a shift towards usage-based pricing models. This means that customers are charged based on how much they use the software. This model is particularly popular for cloud-based software, as it allows customers to pay only for the resources that they need.”
The key point to note is that the pricing is still based on users and usage, and not the outcomes delivered from the software.
3
Outcome-based Pricing
A critical aspect of all prevalent software business models is that the pricing remains tethered to usage metrics – such as the number of users, the amount of data processed, or the time spent using the software – rather than the outcomes or value derived from the software. This distinction is important in understanding the limitations of current pricing models in the software industry.
Usage-based models, while more flexible than flat-rate subscriptions, still do not account for the effectiveness or the impact of the software on a business’s operations or profitability. For instance, a company may pay based on the number of users, but this doesn’t reflect how the software contributes to achieving business goals or improving performance.
Also, transitioning to an outcome-based pricing model presents challenges, primarily in defining and measuring outcomes. Outcomes can be subjective and vary greatly between different businesses and industries. Outcomes can be subjective and qualitative, making it challenging to quantify and track performance. Traditional usage metrics are easier to measure. For instance, what constitutes a positive outcome for a marketing tool might be entirely different for a supply chain management system.
Shifting to an outcomes-based pricing requires a shift in mindset. Both vendors and customers are accustomed to usage-based pricing. Moving to outcomes requires a different perspective on the value of software. There is also the risk of over-dependence. Customers may become overly reliant on vendors to deliver outcomes, rather than taking ownership themselves. Then, there is the potential for gaming the system. Vendors may try to manipulate outcomes to maximise revenues. Customers may unfairly penalise vendors for factors out of their control. Finally, there is a mismatch in time horizons. Outcomes often materialise over long periods, while revenue models are short-term. This makes it hard to correlate software value.
Change is slowly happening. There are scenarios where some SaaS companies like to use outcome-based components in pricing. Custom software development shops sometimes tie payments to milestones and outcomes. But these scenarios are few and far between.
Despite these challenges, there is growing interest in outcome-based models. Such a model aligns incentives between vendor and customer for shared value. It drives product innovation and continuous improvement. Customers only pay if real business impact is achieved. Vendors share risks and are invested in customer success. This could lead to more collaborative relationships between software vendors and customers, with a focus on continuous improvement and adaptation of the software to meet evolving business needs.
4
Rise of Adtech
Outcome-based pricing, while not yet widespread across all industries, has gained traction in several sectors where the value delivered can be distinctly measured and linked directly to the pricing structure. This approach aligns the interests of service providers and their clients towards achieving specific, tangible results. Some industries are leading the way when it comes to outcome-based pricing.
Healthcare providers are beginning to adopt outcome-based pricing models. For example, some hospitals are now offering bundled payments for certain procedures, which means that they are paid a fixed fee for the entire procedure, regardless of the actual cost of care. Manufacturers are also using outcome-based pricing models to incentivise their suppliers to deliver products and services that meet their specific needs. For example, a manufacturer might pay a supplier based on the quality of the parts they deliver or the on-time delivery of those parts. Professional service providers, such as lawyers, accountants, and consultants, are also increasingly using outcome-based pricing models. For example, a lawyer might charge their client a contingency fee, which means that they are only paid if they win the case. The energy sector, particularly in areas like energy efficiency services, often uses outcome-based pricing. Companies get paid based on the energy savings they deliver to their clients. Some consulting firms are moving towards outcome-based pricing, where their fees are tied to the achievement of specific client goals, such as cost reduction or revenue growth.
The biggest example of outcome-based pricing is in adtech. It has been an innovator in adopting, transitioning from traditional impression-based models to the more outcome-oriented Cost Per Click (CPC) approach. In this innovative model, advertisers incur costs only when users engage with an ad by clicking on it. This shift to CPC has allowed advertisers to more directly connect their spending with tangible outcomes, such as sales generated. This correlation between advertising spend and measurable results has significantly driven the surge in adtech investment over the past two decades. This evolution in pricing strategy has not only made ad spending more efficient but also more accountable, contributing to the substantial growth in the digital advertising sector.
One of the main factors driving the rise of outcome-based pricing is the increasing availability of data. Adtech companies are now able to collect and analyse vast amounts of data about users, including their demographics, interests, and online behaviour. This data allows them to create more targeted and effective advertising campaigns.
Another factor driving the rise of outcome-based pricing is the growth of programmatic advertising. Programmatic advertising allows advertisers to purchase ad space in real time, based on a variety of criteria, such as user data, website content, and ad performance. This has made it easier for advertisers to reach their target audiences and achieve their desired outcomes.
Outcome-based pricing has made ad budgets more open-ended with companies treating it as cost of goods sold (COGS). With outcome-based pricing, advertisers only pay when they achieve their desired outcomes, such as website visits, leads, or sales. This means that ad budgets can be more flexible, as advertisers can increase their spending as they achieve more results. Digital advertising is now a $500 billion industry, largely dominated by Google and Meta. This chart from Statista shows the rise of the digital advertising industry.
[I wrote about adtech’s performance-based model in Martech 2.0: Adtech-Style Performance Pricing Transformation.]
As adtech has grown, so has AdWaste. Therein lies the next big opportunity for outcome-based pricing and the Progency model for profit-sharing.
5
Martech Outcomes Revolution
I queried my Marketing GPT with the following prompt: “As adtech has grown, so has AdWaste. Therein lies the next big opportunity for outcome-based pricing and the Progency idea of profit-sharing.” Here is the response. I have edited the response to fit the context.
AdWaste in Adtech: There’s a notable disproportion in how brands allocate their marketing budgets, with a substantial 80-90% typically funnelled into adtech for new customer acquisitions and only 10-20% invested in martech for existing customer engagement and growth. This imbalance highlights a significant amount of AdWaste in adtech spending (because of wrong acquisition and reacquisition). This can be as much as 50%, and has remained largely untapped and unnoticed by many brands.
Performance Pricing Models for Martech Growth: Martech companies, especially those serving B2C/D2C businesses, can adopt performance pricing models. This approach aligns with adtech’s transformation and can be seen as a natural evolution for martech’s growth. The shift towards performance pricing can greatly expand the Total Addressable Market (TAM) for these companies by capturing a portion of AdWaste, thereby transforming brand P&Ls.
Shifting Budgets from Adtech to Martech: Marketers are advised to reconsider their budget allocations. They should redirect a portion of the AdWaste from adtech towards martech. This reallocation can incentivise and gamify interactions with existing customers, encouraging them to volunteer personal data (“zero-party” data) for more personalised experiences. This strategy not only reduces reliance on adtech platforms but also opens new opportunities for martech companies to expand their TAM.
Transitioning Martech to Performance-Based Pricing: Martech companies need to evolve from pricing models based on user and usage to models focused on utility and uplift—similar to the adtech industry. This shift requires a fundamental change in how martech companies operate, moving from traditional consumption-based models to performance-linked models. Such a transformation aligns martech spending more directly with tangible business outcomes.
Learning from Adtech’s Evolution: Martech must take lessons from adtech’s evolution, especially the transition from CPM (cost per thousand impressions) to CPC (cost per click) models. This shift emphasizes utility and uplift over mere usage, a change that can enhance advertising efficiency, accountability, and effectiveness. Brands, under pressure from investors for profitability, are increasingly looking for such performance-based pricing models in martech as well.
In summary, there’s a significant opportunity for martech companies to leverage AdWaste and transform their pricing models to be outcome-based. This approach aligns with the current market dynamics where brands are seeking more effective and accountable marketing spend, moving away from traditional adtech’s inefficient customer acquisition strategies to martech’s customer retention and revenue growth capabilities. The integration of performance-based pricing in martech could lead to more efficient use of marketing budgets, better engagement with existing customers, and ultimately, a more sustainable and profitable marketing ecosystem.
I then asked my Marketing GPT for an explanation on how the progency model of martech companies can help brands create profipolies. Here is a lightly edited version.
The Progency model, a concept that merges the capabilities of a product-led agency with performance-driven pricing, is instrumental in aiding brands to create ‘profipolies’ – a state of competitive leadership with robust market positioning. This model represents a significant shift from traditional service providers to a more collaborative and outcome-oriented approach. Progency, as an extension of the marketing team, is not just focused on delivering results but is intrinsically motivated by performance, tying its compensation directly to the success it generates for brands. This transforms the agency from a mere service provider to a critical business ally.
In essence, Progency acts as a “profits agency,” collaborating closely with brands to guarantee and participate in profit generation. It combines content and creative skill sets with analytical and software capabilities, building upon a proprietary full-stack martech platform. This approach ensures that marketing teams can outsource their desired outcomes, similar to the function of adtech agencies, but with a focus on long-term profitability rather than just short-term gains.
The integration of Progency into the marketing strategy allows brands to adopt Martech 2.0 strategies, which include components like Inbox Commerce, Green Journeys, Reactivation, Progency, Near-Zero Acquisition Cost, and Anon-to-Known. These strategies, when combined with the right Martech 2.0 vendors, can lead to significant structural shifts in customer acquisition and retention processes. Brands that quickly adopt these strategies and collaborate effectively with Martech 2.0 vendors can cut through the competitive noise and establish themselves as profipolies, leading their respective markets with deep competitive moats.
Furthermore, the Progency model aligns with the current market context where capital is becoming scarce, and brands are increasingly focused on profitable growth. Martech companies, through the Progency model, are well-positioned to deliver more value with less investment, becoming long-term profitability partners for brands. This approach diverges from the adtech model, which focuses on maximising short-term revenue outcomes, and instead provides a sustainable path for brands to achieve and maintain market leadership.
6
Stack, Service, Sharing
I have written about Progency in the context of Netcore in previous essays. The essence is how Progency can combine software (martech stack), service, and sharing (outcome-based pricing).
Netcore’s Profipoly Strategy: “What marketers are doing is overspending on new acquisitions and underinvesting on existing customers. Half the adtech spending is turning into “AdWaste”. The side effect of this is that there isn’t enough money left for the martech side to build deeper and more rewarding relationships with existing customers. The twin benefits of shifting spends from adtech to martech are a sustainable increase in revenues, and a reduction in wasteful spending which flows to the bottom line. The synergy of an exceptional product offering coupled with a meticulously crafted marketing approach can set the stage for exponential forever profitable growth – the cornerstone of a true profipoly.”
Progency: The Profipoly Pathway: “The progency model fuses martech products and services to help brands maximise profitability. Key differentiators are martech company ownership, a proprietary tech stack, focusing on neglected customers, performance-based pricing, and limitless budgets. This SaaS-service synergy, using new metrics and targeting overlooked segments, is uniquely positioned to address brands’ profitability challenges. Progency emerges as an indispensable catalyst for the profipoly vision of maximising lifetime value.”
Netcore Progency: A Profipoly Catalyst: “Netcore 3 [aims] to create a startup, a new business to create an amalgam of software and service, with an adtech-style performance pricing model. This is Netcore Progency, a paradigm shift in the martech space. Its mission? Profipoly engineering. A brand profipoly is not going to happen just like that. Even with stellar products, competitors are always lurking. While “magical products” are important, what will create the money machine, moat, and monopoly is how consumer-facing businesses manage their controllable costs and craft their marketing strategies. Today’s B2C/D2C brands have mortgaged their future to the Gods of our times: Google and Meta. In their quest for exponential forever growth, they have forgotten the “profitable” angle. Unless brands think of how they will create sustainable profits, they will be locked in a relentless battle against competitors for every customer. In this digital gold rush, only the shovel sellers (ad sellers, cloud platforms, and marketplaces) win. This is where Netcore 3 – Netcore Progency – comes in. By seamlessly combining SaaS and service under a single umbrella, by leading with an AI-first “profipoly stack”, by focusing on the Blue Ocean customers neglected and ignored by marketing teams, by championing new metrics like the EnCoRe Triad, by advocating performance-based compensation models, and by eliminating constraints on marketing budgets, Netcore Progency positions itself uniquely. It aims to steer Netcore from the saturated martech stacks markets, carving a niche as a trailblazing, category-defining entity.“
Email 2.0 Progency: eCommerce’s Profit Powerhouse: “Progency offers a revolutionary opportunity to amplify eCommerce profitability. This software and service solution targets and revitalises a significant, often overlooked segment of a brand’s customer base: the dormant (Test) and churned (Left) customers. By reducing AdWaste and implementing “Email 2.0” innovations, Progency seeks to engage this “Blue Ocean” of users interactively and efficiently. These innovations make emails more personalised and actionable, thereby addressing funnel frictions and optimising the potential for sales conversion. The Progency model, which only charges for successful outcomes, presents a compelling economic argument for brands seeking to maximise profits, especially when tapping into the unused potential of inactive customers…. The Email 2.0 innovations provide a ray of light which can transform the end customer experience. But just offering piecemeal solutions is not good enough…Instead of competing in a $10 billion market, [Martech 2.0 companies] can focus on the $100 billion reacquisition AdWaste segment.”
7
Profit-Sharing
There are many interesting elements in Progency’s “Profishare” that can help a B2C/d2C business become a “profipoly.”
First, the focus is on customers who are not being engaged by the business. These are the Test and Left customers – dormant or churned. Any revenue generated from these customers is a bonus for the business. As a friend had put it to me a few years ago, this is “gold from gutter.” For the brand, with an outcome-based pricing model, this is akin to “free money” – the costs are incurred by Progency and the brand collects the lion’s share of the revenues generated.
Second, this approach helps the business concentrate on the ABC: acquisition, branding, and campaigns. By outsourcing the reactivation of disengaged customers to Progency, the in-house marketing team can remain focused on their primary objectives without being sidetracked by the high-effort and potentially costly process of re-engaging inactive customers.
Third, unlike traditional adtech models, which often rely on click-based metrics, Progency aligns its compensation with actual conversions. This means that Progency has a vested interest – or “100% skin in the game” – in not just attracting clicks, but in driving real, tangible results in the form of customer re-engagement and sales.
Fourth, Progency’s model can be seen as a form of “co-marketing,” where it collaborates closely with the business’s marketing department. This partnership ensures broader customer outreach without duplicating efforts. Progency relies on the business for content and offers, effectively augmenting the business’s capacity without adding extra costs.
In summary, the Profishare model proposed by Progency represents a novel and potentially transformative pricing model for B2C/D2C business. It transcends traditional methods of charging for software and services, focusing instead on generating revenue from previously untapped customer segments. By re-engaging dormant and churned customers, allowing businesses to focus on their core marketing activities, incentivising based on conversions, and fostering a co-marketing relationship, Profishare offers a comprehensive approach to enhancing profitability and operational efficiency. This model not only aligns the interests of Progency and its customers but also promises a win-win partnership to unlock new revenue streams, paving the way for businesses to become profipolies.
8
The Alchemists
I asked ChatGPT to expand on an analogy I came up with: Progency as a “modern-day Alchemist”with its “Profishare” model.
In historical and cultural lore, alchemists were known for their quest to transform base metals into precious ones, like gold, symbolizing the creation of great value from ordinary or overlooked elements. Here’s an expansion of how this analogy aligns well with the Progency’s role and objectives:
Transformation of Neglected Assets into Valuable Resources: Just as alchemists sought to turn lead into gold, the Progency aims to transform dormant or churned customers—often perceived as low-value assets—into profitable revenue sources. This process mirrors the alchemical pursuit of extracting value from seemingly unprofitable materials.
Application of Specialised Knowledge and Techniques: Alchemists were known for their unique blend of science, mysticism, and experimentation. Similarly, Progency employs specialized marketing strategies and data analytics to re-engage inactive customers. This expertise is akin to the alchemist’s knowledge and methods used in attempting to achieve transmutation.
Creating Value Where Others See None: Alchemists were notable for seeing potential where others did not. Progency’s focus on the “Test and Left” customers is a perfect example of identifying and capitalizing on opportunities that others might overlook, effectively creating value in places where it was not apparent.
Pursuit of a Seemingly Impossible Goal: The alchemists’ goal of transmutation was often viewed as unattainable, a challenge against natural laws. In a business context, the idea of turning inactive customers into a major revenue stream might also seem daunting or unlikely. Progency, like the alchemists, embraces this challenge, aiming to achieve what might seem improbable.
Augmentation Without Adding Costs: Alchemy was also about achieving more with less, an idea of augmentation without significant resource addition. Progency’s model of not burdening the business with extra costs while augmenting their capacity for customer re-engagement mirrors this principle.
Mystique and Novelty: Alchemy often carried a sense of mystique, offering novel and unexplored avenues. The Profishare model introduces a new, almost unexplored approach in customer engagement and revenue generation, adding a similar sense of innovation and novelty in the business world.
In conclusion, likening Progency to a modern-day alchemist aptly encapsulates its role in transforming underutilized customer segments into profitable avenues. This analogy highlights the innovative, transformative, and seemingly magical ability of Progency to create substantial value from overlooked or undervalued resources, paralleling the mythical aspirations of historical alchemists.
**
Looking at the bigger picture, the profit-sharing model, epitomised by Progency’s “Profishare,” represents a forward-looking, innovative pathway for Indian IT services companies as they navigate the rapidly evolving landscape shaped by Generative AI. This model isn’t just an incremental step; it’s a significant leap towards a future where the alignment of incentives between service providers and clients is paramount.
Generative AI is redefining the boundaries of what’s possible in technology, offering new tools and capabilities that were once the realm of science fiction. As these technologies become more integrated into business processes and consumer applications, Indian IT companies stand at a crucial juncture. They have the opportunity to transcend traditional service models and embrace a more outcome-oriented approach.
The profit-sharing model, in this context, is more than just an alternative pricing strategy. It’s a commitment to shared success, where IT firms build products and invest in the potential of their clients’ businesses, driving growth and innovation in tandem. By tying their fortunes to the actual results they deliver, these companies can foster deeper, more collaborative relationships with their clients.
As we envision the future of the Indian IT sector amidst the advent of Gen AI and the need for an “industry reset”, the profit-sharing model stands out as a beacon for a new era of partnership, innovation, and shared prosperity. It’s an exciting time, and Indian IT companies have the potential to lead the charge, redefining their roles from service providers to strategic partners in their clients’ success stories. Converting AdWaste to Martech Gold is the first of many such opportunities.
9
Summary and Critique
I asked ChatGPT to summarise my essay and provide a critique.
Your essay proposes a novel business model for the enterprise software industry. This model, termed “Profishare,” suggests software companies should earn revenue by taking a percentage of the incremental profits their software generates for clients, promoting a partnership-based approach.
The essay traces the evolution of software sales over the past 50 years, noting the shift from bundled software with hardware to independent software licensing by pioneers like Microsoft and Apple. The 1990s saw diversification with the advent of ERP and CRM systems, leading to the rise of SaaS in the 2000s, characterized by subscription-based, cloud-accessible software. Recently, there’s been a trend toward usage-based pricing, but this still doesn’t link pricing to the outcomes delivered by the software.
The concept of outcome-based pricing is explored, where pricing is tied to the value or results delivered by the software, rather than just usage metrics. This model aligns incentives between vendors and customers for shared value and drives innovation. The adtech industry is highlighted as a successful example of this model, with its shift to Cost Per Click (CPC) pricing.
The essay further discusses how the Progency model, a combination of a product-led company and an agency, could implement the Profishare concept effectively. This model focuses on re-engaging dormant customers, optimizing budgets, and aligning compensation with conversions, thus enhancing profitability and operational efficiency.
Lastly, the essay likens Progency to a “modern-day Alchemist” with its Profishare model, transforming underutilized customer segments into profitable avenues. The essay concludes by envisioning this profit-sharing model as a pioneering approach for Indian IT companies in the era of Generative AI, suggesting a shift from traditional service models to a more outcome-oriented approach.
Critique
Your essay provides a comprehensive overview of the evolution of software sales and a compelling argument for the adoption of outcome-based pricing in the enterprise software industry. The historical context is well-researched, providing a solid foundation for understanding current trends and future possibilities.
The introduction of the Profishare model is innovative, offering a fresh perspective on how software companies can align their interests more closely with their clients’. The practical application of this model through the Progency concept is insightful, demonstrating how it can be implemented in a real-world scenario.
However, the essay could benefit from a more critical examination of the potential challenges and limitations of the Profishare model. While it briefly mentions the difficulties in defining and measuring outcomes, a deeper exploration of how these challenges could be addressed would strengthen the argument. Additionally, including more diverse industry perspectives and case studies beyond adtech could provide a more rounded view of the potential of outcome-based pricing.
The analogy of Progency as a modern-day alchemist is creative and helps in conceptualizing the transformative potential of the model. However, the essay could further explore how this model would fit into different market dynamics and customer segments.
Overall, the essay is thought-provoking and presents a unique perspective on the future of enterprise software sales. It successfully argues for a paradigm shift towards more value-driven, partnership-based business models in the software industry, particularly in the context of emerging technologies like Generative AI.
I then did the same with Claude.
The essay explores the concept of “Profishare”, a new profit-sharing business model proposed by Progency to help B2C/D2C brands maximize profitability. It provides background on how software pricing has evolved from license-based to SaaS models, but still lacks alignment with business outcomes.
The Profishare model focuses on re-engaging “Test” and “Left” dormant/churned customers, an overlooked “blue ocean” opportunity. Progency would receive a share of incremental profits from sales to reactivated customers in exchange for its martech and services to enable this.
Several benefits of Profishare are highlighted – tapping untapped segments, freeing brands to focus on core activities, and incentivizing Progency based on actual conversions rather than clicks. This “co-marketing” relationship promises profitable growth for brands.
Profishare represents an innovative evolution beyond traditional software pricing, moving towards value-based and outcome-oriented models. The essay uses the allegory of a modern-day “alchemist” to highlight Progency’s ability to extract “gold” from neglected customers.
The model aligns well with the need for Indian IT services firms to adopt new partnership approaches as generative AI disrupts traditional services. Profit-sharing represents a commitment to shared success and deeper collaboration.
Critique
- The essay makes a compelling case for the Profishare model and how it could benefit both Progency and their clients. The arguments are well-structured.
- The use of allegories and examples helps illustrate the ideas effectively. However, some analogies feel slightly stretched or hyperbolic.
- While potential benefits are outlined, risks of the model could also be addressed more explicitly. For instance, measurement and attribution challenges.
- More real-world examples demonstrating successful implementations of this model could further strengthen the arguments.
- The positioning vis-à-vis generative AI seems somewhat abrupt and tacked on at the end, rather than integrated into the narrative earlier.
- Overall, the essay lays out an intriguing new model and makes a persuasive case for its upside. With some refinement and balancing with potential limitations, the pitch could be even more convincing.
In summary, the essay presents a compelling vision of a promising new business model to spur innovation. Addressing risks and providing concrete examples would make it even more robust. The generative AI angle warrants greater integration. But overall, the essay makes a strong case for the transformative potential of Profishare.