Adobe Gen Studio for Performance Marketing (whew! what a mouthful) opens up meaningful possibilities: produce marketing content at scale while maintaining quality and brand consistency. Organizations that approach implementation thoughtfully are seeing real benefits; faster campaign launches, more testing capacity, and better resource allocation.
Success needs some preparation and realistic planning beyond the typical IT requirements. Martech is 90% people and 10% technology, and this holds true in a GenStudio implementation. Let me share what I’ve learned from watching teams navigate this journey.
Most marketing teams have evolved over the past decade into sophisticated orchestrators of creative work. They excel at strategic planning, agency partnerships, and stakeholder alignment. This evolution made sense; specialized agencies brought deep creative expertise while internal teams focused on strategy and coordination.
The whole selling point of GenStudio is to bring a significant portion of creative production in-house. This is a genuine shift in how work flows and where capabilities need to live. A few patterns emerge consistently:
Expectations take time to calibrate. Sales demonstrations showcase impressive capabilities, and teams wonder why their initial results look lame. This gap usually comes down to both foundational setup and technology limitations.
Templates can feel limiting at first. Ad agency culture celebrates breakthrough creativity with Hollywood-style awards, so systematic templated approaches feel constraining. Yet most successful implementations find that templates actually free up creative energy for higher-value work. It’s a mindset shift from bespoke, hand-coded assets to strategic, real-time experimentation.
Agency relationships matter. Many teams have built trusted partnerships with their agencies over years. They’re friends. Marketing managers don’t want to take work away from people they’ve worked with for years.
Technical complexity surfaces gradually. Adobe’s ecosystem is complex, and the naming conventions can be confusing. Sometimes teams discover mid-implementation that their use case needs additional SKUs not specified in the sales process in order to meet their use cases.
Many teams approach this as an IT project. Think of GenStudio implementation as building a capability alongside deploying technology.
| Foundation Element | \nWhy It Helps | \nWhat Success Looks Like | \n
|---|---|---|
| Brand Guidelines | \nGives templates clear rules to follow | \nDocumented typography, color usage, image style, layout principles—the kind of guidance that helps anyone make on-brand decisions | \n
| Asset Library | \nProvides raw materials for generation | \nOrganized, accessible, rights-cleared images and graphics that your team can actually find and use | \n
| Approval Workflows | \nKeeps quality high while maintaining speed | \nClear decision makers, documented steps, realistic timelines that work for your culture | \n
| Defined Use Cases | \nFocuses early efforts on high-value wins | \n3-5 specific scenarios with clear success metrics to guide implementation | \n
Invest upfront in compiling your brand guidelines and assets before signing paper to avoid needless and costly implementation delays. Solution integrators can’t configure the brand in GenStudio without guidelines and examples, so upfront collection pays off.
Map a few use cases in advance to ensure your salesperson will configure the system to your needs. Doing this avoids a mid-implementation scramble to buy new SKUs, forcing Legal and Accounts Payable into fire drills. Nothing good comes out of that, I assure you.
Your first use cases set the tone for everything that follows. Avoid the “Magic Ad Maker” trap, the expectation that GenStudio will produce a whole new concept on demand. Additionally, it may take some time to fine-tune your assets. Consider starting with scenarios that deliver clear value without requiring perfection:
Promising first applications:
Save for later:
Document these use cases specifically, then review them with your Adobe account team and a pre-sales engineer before finalizing contracts. This conversation helps ensure you have the right technical capabilities from day one, which keeps momentum strong during implementation.
Teams benefit from a clear mental model of how GenStudio fits into their creative ecosystem.
Consider this framework: strategic creative and systematic execution. Your agency partners create breakthrough campaigns—the work that repositions your brand, launches major products, and drives cultural conversation. GenStudio takes those successful campaigns and systematically adapts them across channels, audiences, geographies, and time periods. Think about it: Agencies can focus on truly strategic brand building. Organizations capture that below-the-line production work in-house and can be more nimble in audience targeting experiments.
This model offers several benefits:
Agency relationships evolve productively. Rather than reducing partnership, you’re focusing agency talent on high-value strategic work where their expertise matters most.
Quality expectations become clearer. GenStudio output needs to maintain brand standards and perform well, while agencies focus on the creative that breaks through and drives differentiation.
Decision points emerge naturally. Teams develop good instincts about when work benefits from AI-powered execution versus when it needs human creative direction.
Your team needs to transition from being taste makers and budget controllers to becoming workflow thinkers and experimenters. This means understanding how AI generation fits into approval processes, where to invest creative energy for maximum impact, and how to test and learn systematically at new velocity.
While Adobe Gen Studio has robust compliance features, your team benefits from understanding layout, visual hierarchy, and brand expression. They need to know what to check before content goes live—brand compliance, technical accuracy, and audience appropriateness.
Workflow thinking is key, and this requires repeated messaging: Understanding how AI generation fits into your approval processes and where human oversight adds most value.
Budget genuine time for skill development. This represents investment in long-term capability.
A few clear decisions keep work flowing smoothly:
Key decisions to document:
Creating simple decision frameworks helps teams navigate this transition. Here’s an example structure:
| Content Type | \nGeneration | \nApproval | \nAgency Role | \n
|---|---|---|---|
| Banner resizing | \nMarketing coordinator | \nMarketing manager | \nNone | \n
| Seasonal updates | \nMarketing manager | \nBrand director | \nReview | \n
| Campaign concepts | \nAgency | \nCMO + Brand | \nLead creative | \n
| Launch creative | \nAgency | \nCMO + Legal | \nLead creative | \n
Simple frameworks like this help everyone understand their role and keep projects moving.
Track the practical improvements that compound over time:
Speed improvements
Resource optimization
Capability gains
We always hear stories like “One team moved their A/B testing from monthly to weekly cycles. The faster learning loop improved campaign performance by 23% over six months”…but in my experience, that’s fiction. Most organizations can’t experiment because turnaround time is so slow. Templatizing and systematizing assets can fix that. That velocity advantage creates compound benefits as learning accumulates.
Continuous Campaign Optimization
A software company runs ongoing Meta campaigns. Previously, they briefed their agency for every size variation or messaging test, with two-week turnarounds.
Now their marketing manager adjusts copy in approved templates, generates variants, gets quick brand review, and launches same day. They’re testing three times as many variations and learning what resonates much faster.
Seasonal Adaptations
A retail brand updates campaigns for each season using consistent layouts with refreshed imagery. This work used to require agency coordination and production time.
Now their marketing team adapts seasonal elements using AI-generated backgrounds for non-product imagery, maintains proven layouts, gets brand approval, and launches on schedule. The agency focuses on genuinely differentiated seasonal concepts.
Regional Customization
A global company adapts campaigns for different markets, each with distinct cultural contexts and imagery preferences.
Regional teams now generate locally appropriate background imagery within brand-approved templates. Central brand teams review for compliance. Regions move faster while maintaining brand consistency.
Month -1: Preparation
Months 1-3: Initial Implementation
Months 4-6: Expansion
Months 7-12: Maturation
This year-long view reflects real organizational change. The timeline allows for learning, adjustment, and building genuine capability that lasts.
A few things you’re uniquely positioned to provide:
Set realistic expectations. When stakeholders see impressive demonstrations, you can frame what success looks like at different stages. Early wins look different from mature capability.
Support foundational work. Brand documentation and asset organization deserve time and resources, even though they’re less visible than AI features.
Evolve agency partnerships thoughtfully. Consider how to elevate these relationships to more strategic work rather than simply shifting tasks.
Focus on capability development. What can your team accomplish now that they couldn’t before? This matters as much as efficiency metrics.
Create space for learning. New capabilities require practice and adjustment. Teams benefit from permission to experiment and learn.
Adobe Gen Studio creates genuine opportunity when organizations invest in thoughtful implementation. The technology offers real capabilities, and success comes from building the foundation those capabilities need.
Start with achievable use cases. Allow time for learning and adjustment. Measure progress across multiple dimensions. Celebrate both quick wins and longer-term capability building.
The organizations finding success aren’t necessarily those with the largest budgets or most sophisticated technology. They’re the ones approaching this as a capability-building journey—documenting their brand, developing their team, and creating systematic processes that improve over time.
This takes patience and commitment. The results—faster time to market, better testing velocity, stronger brand consistency, and more strategic use of creative talent—build meaningfully over time.
Your organization’s creative engine can become a genuine competitive advantage. That advantage comes from combining Adobe’s technology with the foundational work that makes it effective.
Before You Begin:
Setting Up for Success:
Building Team Capability:
Measuring What Matters:
Leadership Priorities:
The Compound Advantage:
Much has been said and written lately about the need to govern the prolific output of content from GenAI systems that are intended to support business goals, but too often create as many problems as they solve.
\nAmong the chief challenges involved are ensuring that AI models are effectively trained to be free of bias and hallucinations, and that the content they produce is consistently compliant with a brand’s quality standards and policies.
\nEmbarrassing and downright dumb examples of GenAI producing cringe-worthy mistakes abound, among these Google Photo infamously categorizing people of African descent as gorillas. Or more recently, an article in Microsoft Start’s travel pages referring to the Ottawa Food Bank as a “tourist hotspot,” advising readers to visit on “an empty stomach.”
\nMoreover, when it comes to the esthetic quality of images it produces, today’s GenAI typically tends toward a schlocky plastic look, containing basic flaws that violate common sense and design principles that no human who’s a qualified designer would ever let slip past.
\nDon’t Believe the Hype
\nChallenges posed by the current AI tech revolution resemble what happened in the market 30 years ago when desktop publishing solutions first emerged, putting tools into the hands of anyone with a PC. What resulted was a flooding of the market with poorly designed, inexpensively produced, but crappy content that mostly served to cheapen brand values.
\nEventually, it dawned upon anyone responsible for building and maintaining a brand’s image that all the hype accompanying new desktop publishing tools was just that—hype. While it’s true the technology did enable a trained designer to efficiently produce quality content, without the human talent and training to operate them the tools were like typewriters to monkeys.
\nThe rapid emergence of GenAI now requires revenue growth and marketing leadership to take a step back and ask themselves not just what are the potential benefits of the technology, but also taking a close look at its costs and limits as well. This means starting with a careful strategic assessment, before adding yet another platform to their existing tech stacks.
\nDropping Back a Step
\nMarketing tech providers have traditionally offered solutions that only support specific functions like content personalization, lead management, or customer analytics. At many organizations (small and large), the situation has created a confounding mess of disconnected systems, siloed data, and ultimately a poor customer experience—all of which negatively impact a company’s revenue.
\nEven when they’re aware of the potential backlash that GenAI can produce, many chief revenue and marketing officers don’t fully grasp that success in today’s business climate—awash with tsunamis of data—won’t be achieved by simply adding an AI platform to their already bloated tech stacks.
\nInstead, achieving the holy grail of an AI strategy that produces high-quality, brand-compliant marketing content on a massive scale, using key data points and performance indicators that support a positive customer experience, requires a fundamental rethinking by company leadership.
\nMinimum Viable Data
\nPerhaps counterintuitively, one of the biggest drivers of unnecessary costs associated with deploying GenAI into an organization’s revenue chain results from an attempt to mine too much data with the system—more than required to yield useful outputs.
\nNot only can an overambitious, data-greedy approach generate inaccurate conclusions about likely customer preferences, etc., it inevitably results in excessive data storage and processing costs. Most large companies, for example, keep large quantities of data stored across various departments, including previously abandoned pet projects, which are irrelevant and should be excluded from a new GenAI model.
\nBased on my recent experience consulting with many CROs and CMOs at numerous Fortune 500 companies, I have observed the most effective leaders recognize the importance of taking a more minimalist approach when deciding which data sources to tap with a GenAI model.
\nIn this regard, allow me to offer a simple formula to keep in mind when planning and deploying a new GenAI solution into the organization’s revenue chain: Minimum Viable Data = Minimum Valuable Product (MVD = MVP).
\nStarting with People
\nEffectively applying the principle of MVD = MVP to GenAI entails leadership first bringing all the revenue chain’s stakeholders together in the planning-stage work group, with the goal of answering an initial question, “What is the MVD for this proposed solution?”
\nMy experience has led me to observe that some stakeholders typically covet certain data points they believe to be essential for success, based on their unique but limited perspective on the entire revenue chain. Often, their preferences reflect a bias of some type and their desire to emphasize this in a GenAI’s model, which leads to ill-advised outputs, not to mention unnecessary data storage and processing costs.
\nOn the other hand, the best insights in terms of essential data points for achieving revenue-chain success using GenAI naturally come from stakeholders who are working daily in the trenches. So, it’s incumbent upon the CRO or CMO—whoever’s ultimately in charge—to listen thoughtfully to all stakeholder perspectives, while maintaining a laser focus on separating wheat from chaff in defining a project’s MVD.
\nIt may sound like a cliché, and yet it’s demonstrably true: The most valuable resource in any company are its people. This holds true when it comes to leveraging GenAI to optimize an organization’s end-to-end revenue chain, from IT to product design, marketing, sales, and customer satisfaction. Investing in the people who perform these critical roles daily and valuing their practical experience and knowledge is the place to start.
\n# # #
\n", "author": { "name": "Bill Anderson" }, "tags": [ "The AI Backlash", "Revenue Orchestration Architecture", "GenAI", "Consulting thoughts", "Consulting" ], "date_published": "2026-01-10T13:20:39-05:00", "date_modified": "2026-04-16T13:30:13-04:00" }, { "id": "https://cwilliamanderson.com/getting-roi-from-fluid-revenue-systems/", "url": "https://cwilliamanderson.com/getting-roi-from-fluid-revenue-systems/", "title": "Getting ROI from Fluid Revenue systems", "summary": "Executives investing in Salesforce, particularly with Fluid Revenue Orchestration, often find the promised ROI a little elusive. It's not usually a problem with the technology itself, but rather a gap between how the system is configured and how salespeople actually behave. Simply deploying a sophisticated…", "content_html": "
Executives investing in Salesforce, particularly with Fluid Revenue Orchestration, often find the promised ROI a little elusive. It's not usually a problem with the technology itself, but rather a gap between how the system is configured and how salespeople actually behave. Simply deploying a sophisticated system doesn't guarantee accurate data or streamlined processes – you really need to get buy-in from the team. The key lies in redesigning sales compensation to explicitly reward adherence to established protocols – transforming sales representatives from simply using the system into active contributors to a clean, reliable data ecosystem.
\nHistorically, sales compensation has been almost entirely focused on closed-won revenue. While closing deals remains paramount, this singular focus can inadvertently incentivize shortcuts. A representative chasing a quarterly number might rush lead qualification, neglect detailed meeting notes (we’ve all been there!), or bypass required steps to accelerate the sales cycle. The result? A distorted pipeline, inaccurate forecasting, and a system filled with incomplete or misleading data.
\nThe solution isn’t stricter enforcement or more training sessions, though those things can help. It’s a compensation structure that recognizes and rewards the effort required to maintain data integrity. Consider elements beyond simply hitting a revenue target. A redesigned plan might incorporate these metrics:
\nThe benefit for the executive team is profound. A Salesforce instance fueled by accurate, reliable data enables:
\nUltimately, building a successful Fluid Revenue Orchestration strategy isn't about implementing a powerful tool; it’s about changing sales behavior. By aligning compensation with desired actions, executives can transform Salesforce from a data repository into a powerful engine for revenue growth. It’s about recognizing that maintaining a clean data ecosystem is just as valuable as closing a deal.
Key takeaways
• ROI Beyond the Close: Salesforce ROI isn’t just about closed-won revenue; it’s fundamentally tied to the quality of the data flowing through the system.
Adobe’s recent unveiling of GenStudio has sparked a lot of interest and some consternation among marketing executives, particularly those focused on performance marketing. The demo showcased the platform’s ability to generate tens of thousands to millions of images swiftly, a capability that will disrupt business processes and workflows within the industry.
\nThe initial release of GenStudio is explicitly designed for high-volume content generation. This focus underscores Adobe’s strategic positioning in the performance marketing sector, a use case that produces vast quantities of visually engaging content. In performance marketing, novelty is key. The GenStudio platform aims to streamline the creation process, allowing marketers to produce vast amounts of material efficiently and at scale.
\nWhile the current iteration emphasizes volume, Adobe is actively developing additional use cases and B2B tools. This expansion suggests a broader application for GenStudio in various sectors beyond consumer advertising, potentially including regulated industries like healthcare and financial services. That’s more easily said than done, however; these verticals face strict regulatory standards, and genAI hallucinations just won’t cut it here.
\nThe sheer volume of content that GenStudio can produce will upend many existing business processes. Traditional workflows may need to be rethought entirely, given the exponential increase in creative output. This disruption is particularly pronounced in areas like approval and review, which require additional resources to manage effectively.
\nAdobe’s own experience serves as a case study here. The company had to enlist outside agencies and studios to assist with reviewing and approving content due to the scale of creation. This necessity highlights the operational challenges that come with high-volume content generation, even for a tech giant like Adobe.
\nTo mitigate these challenges, GenStudio incorporates built-in tools designed to streamline the approval process. One notable feature is the brand validation tool, which employs an adversarial model trained to identify inconsistencies from a company’s fine-tuned brand imagery, style, and voice. This model flags potential issues and offers remediation suggestions, enhancing efficiency without replacing human oversight entirely.
\nThe fine-tuning aspect of this tool is an additional service offered by Adobe. It involves creating a bespoke model tailored to a company’s specific brand aesthetics and guidelines. This personalization ensures that the generated content aligns closely with the organization’s visual identity, reducing the likelihood of off-brand outputs.
\nAdobe’s decision to position GenStudio for high-volume consumer advertising is strategic. The demo outputs are characterized by bright, artificial, colorful, and playful imagery—attributes that align well with generative art models and appeal to a broad audience. This positioning makes the platform particularly suitable for sectors like e-commerce and display advertising, where visual impact and scalability are crucial.
\nThe integration timeline is ambitious but practical. Adobe aims for full value realization within approximately eight weeks of implementation, allowing companies to start seeing returns on their investment relatively quickly. Self-serve content is slated for release around December 2024, with certification tests expected by the end of 2025. This phased rollout ensures that organizations have ample time to familiarize themselves with the technology and prepare their teams accordingly.
\nBeyond its generative capabilities, GenStudio offers several other valuable tools. One such feature is automatic metadata and keyword creation, which can significantly enhance content management and searchability. The platform also integrates with Adobe Workfront and other applications for seamless approval processes, further streamlining workflows.
\nMoreover, the platform includes content performance analysis using keywords, enabling marketers to gain insights into the effectiveness of their campaigns. This analytical capability is crucial in an era where data-driven decision-making is increasingly important.
\nThe introduction of GenStudio also necessitates a reevaluation of traditional marketing roles and workflows. Brand designers, for instance, will need to consider inputs, technology, and endpoints more holistically. This shift mirrors broader trends in the industry, where digital transformation is driving new skill requirements and job descriptions.
\nIn regulated industries, the challenge extends beyond volume and quality assurance. Compliance with regulatory standards must be meticulously maintained, adding another layer of complexity to the approval process. While GenStudio’s current iteration does not explicitly address these challenges, future updates may incorporate features tailored to these sectors.
\nA recent example of successful high-volume content generation is Omnicom’s Miranda brand image campaign. Using Adobe Firefly, the agency generated 540,000 images from 200 prompts for 200 subjects in 12 art styles—a staggering total of 1.5 million images in just five days. This case study underscores the potential of generative AI in marketing and highlights the need for robust safeguards and significant resources to review and approve such volumes of content effectively.
\nAdobe GenStudio represents a significant leap forward in content generation, particularly for performance marketing. Its focus on scale and volume addresses a critical need in the industry while posing challenges that necessitate innovative solutions. As Adobe continues to develop and expand the platform’s capabilities, it will be crucial for organizations to adapt their workflows and roles to harness its full potential effectively.
", "image": "https://cwilliamanderson.com/media/posts/8/1752249367505.png", "author": { "name": "Bill Anderson" }, "tags": [ "Marketing Technology", "GenStudio", "GenAI", "Consulting" ], "date_published": "2025-07-11T12:01:00-04:00", "date_modified": "2026-04-17T15:36:13-04:00" }, { "id": "https://cwilliamanderson.com/basic-tenets-of-fluid-revenue-orchestration/", "url": "https://cwilliamanderson.com/basic-tenets-of-fluid-revenue-orchestration/", "title": "Basic tenets of Fluid Revenue Orchestration", "summary": "I've been in more than a few organizations, and I've formed an opinion of what makes a strong Revenue Orchestration Architecture. Here's my basic tenets for design: READ is powered by data. All the arguments about API-first, Composable, Headless, Gopher protocol take a back seat…", "content_html": "I've been in more than a few organizations, and I've formed an opinion of what makes a strong Revenue Orchestration Architecture. Here's my basic tenets for design:
\nREAD is powered by data. All the arguments about API-first, Composable, Headless, Gopher protocol take a back seat to identifying what is the right data, and ensuring that data is flowing smoothly. You need to focus on Minimum Viable Data (MVD)
\nMinimum Viable Data is the core data needed to flow for a Revenue Orchestration Architecture to work. Specifically, it is the data that tells where the person came from, what buy signals, what audience and what activities. Simply put, what is the least data you need to recognize a buyer? This is especially important for <s>data, flow and </s>analytics and privacy.
\nIt's not enough for an executive to give a speech and walk away. The sponsoring executive must take an active role, particularly at the beginning stages to ensure that communications are meeting the teams goals once the team gets comfortable working with one another, the executive can take a step back.
\nI have had countless clients who wanted to do multitouch attribution and fail. The single place of failure tends to be when the lead is passed from marketing to sales. Sales are goal-driven and any friction between them and a sale will be met with fantastically creative techniques to overcome the administrative bullshit and close the sale. And that means bad data for you. There was only one company that had a perfect system, and that was because compensation was linked to accurate and timely working of a lead.
\nAnalytics are looking in the rearview mirror. It's great for measuring past performance and reporting to the board, but it's the old, stuffy revenue recognition requirements pays the bills. It pays over and over again if you have royalties or renewals, so make sure all of your chain supports revrec. How can your content and processes and automation support sales and smooth that flow? Design it in the early stages, don't leave it until it's blocking a closed-won.
\nNASA's Rule 15 states: The seeds of problems are laid down early. Initial planning is the most vital part of a project. The review of most failed projects or problems indicate the disasters were well planned to happen from the start. In other words, fixing project problems in later phases is expensive. Before you start designing, know what your executives are reporting to the Board. Know your MVD—Minimum Viable Data, and know what requirements are needed for revenue recognition.
\nYou also need to know when to stop. Having a written description of what a successful task, project or workflow looks like will help you accelerate the implementation process.
\nThis is often extremely uncomfortable for employees, because personalities that are attracted to a particular profession are often at odds with one another. People pleasers tend to avoid goal-driven personalities. They need help communicating and learning to collaborate and understand one another's jobs. This is where active executive sponsorship comes in.
\nIt's said that good fences make good neighbors. Clearly defined, written lead dispositioning terms (accepted, rejected, junk, not ready, etc) ease the ongoing conversation between marketing and sales when it comes to Marketing Qualified Leads (MQL). Make sure that your teams know what a good lead looks like, and have clearly defined terms so the teams can collaborate effectively to improve those MQLs.
\nDon't allow agile ceremonies to become a burden, and don't allow meetings to become edge case or solution solutioning sessions.
\nYou’ll have a wide range of personalities and departments that are designed to be check and balance to one another. This is the time to have tight control over the expectations and management of meetings and outcomes.
\nBig change is terrifying for people. They’ve spent incredible efforts creating adaptive behaviors to overcome your twisted revenue funnel. They know how to bypass a broken technology to get what they need. If you make this simple, they may lose their job.
\nTrain not just for the operation, but they why of the change. Show the new, more challenging and rewarding opportunities that will come from a strong automation. Show them what they’ll get in return for giving up maladaptive behaviors.
\nCompensation and bonus is not just for the project, but should be an integral part of your annual operations budget. Reward for consistency. Reward for improvement. Have strong written guidelines and have the stones to withhold reward if your team isn’t holding up their end.
", "author": { "name": "Bill Anderson" }, "tags": [ "Revenue Orchestration Architecture", "Marketing Technology", "Consulting" ], "date_published": "2025-06-29T12:06:00-04:00", "date_modified": "2026-04-16T13:32:39-04:00" }, { "id": "https://cwilliamanderson.com/fluid-revenue-orchestration-needs-two-things/", "url": "https://cwilliamanderson.com/fluid-revenue-orchestration-needs-two-things/", "title": "Fluid Revenue Orchestration needs two things", "summary": "Fluid revenue operations require two things to work: a good flow of data and the right data to flow. Data must flow simply this is a key problem in many systems companies maintain fragile complicated systems because they started from the wrong point. They lost…", "content_html": "Fluid revenue operations require two things to work: a good flow of data and the right data to flow. Data must flow simply this is a key problem in many systems companies maintain fragile complicated systems because they started from the wrong point. They lost their way. They forgot what matters to the board and so they shoehorn in the reporting at the end of every quarter. Many times they don't have the right data and so you wind up picking and choosing between the least bad data source. That's not going to cut it.
\nA good flow of data in this case means that the entire system flows seamlessly from platform to platform. For this to happen, the entire revenue flow needs to be examined from holistic perspective and you need to make the platforms work for you not compromise your data and flow to meet the needs of the platform. This seems obvious and it's shocking how many organizations do the opposite. I think it's because of organic growth, and I find that this is the biggest problem with early adopters. I think it's because they started early, long before best practices were established in the industry so they were making it up as they went. As they grew their needs, got more complex and so they bought more platforms. I know I did when I was marketing operations manager. Those platform seem to solve a discrete problem and they do it well. The problem comes in when you add in customizations. You start to add in too many layers. You solve for cases without actually weighing the value.
\nI would say edge cases create a significant amount of data issues. Stop and think about it. You're martech stack his own and managed by IT. Marketing is the customer. And many times when you are designing or implementing a new system, the product developers are involved. I don't know if you realize it, but developers love cases. They live for cases. As well, they should. And you know, thinking about it, IT does too because if you sell for edge cases, you eliminate a lot of problems.
\nBut in my experience, most of those edge cases are not actually worth it. They're not quantified there's no dollar value attached to it. There's no estimate of how many use cases or cases there are. So you settle for all of them. And usually when you're trying to shoehorn that edge case solution into a platform that was designed for a specific task, you wind up adding a lot of extra data points. You might wind up with a date, time stamp, a bullion checkbox may be a list of items. Sometimes there's so many of them. They have to roll that into a custom object. And custom objects take on a life of their own.
\nI've seen cases where large companies have custom data objects containing 1500 fields. And there are 400 - 1000 custom objects. All of those data fields and custom objects (we're up to 600,000 fields if you use my lower estimate) sink between your CRM and your marketing automation system. Anytime any field is updated on any leader contact, that record will sync between the two systems. As you can imagine, that creates a pretty danged noisy system. And when one script or workflow is misconfigured, it might result in millions of sync actions which leads to a sync backlog, sometimes weeks of backlog.
\nTo support this massive flow of data, cloud providers will often sell large enterprises their very own servers, maybe even the superpod or two if you need it. This is terrific business for the cloud provider, and they all throw in dedicated support engineers for a fee. As they should. Because the client has asked to support the data flow, but they didn't ask to unclog the pipes. They've asked for bigger pipes, and so the provider provides.
\nSo let's talk about how we unplug these pipes.
", "author": { "name": "Bill Anderson" }, "tags": [ "Revenue Orchestration Architecture", "Consulting thoughts", "Consulting" ], "date_published": "2025-06-25T12:09:00-04:00", "date_modified": "2026-04-16T13:34:42-04:00" }, { "id": "https://cwilliamanderson.com/mvdmvd-your-minimum-viable-data-is-your-most-valuable-data/", "url": "https://cwilliamanderson.com/mvdmvd-your-minimum-viable-data-is-your-most-valuable-data/", "title": "MVD=MVD: Your Minimum Viable Data is your Most Valuable Data", "summary": "Sure, data is seen as the lifeblood of modern business. Companies are urged to collect as much data as possible, with the belief that more information leads to better insights and decision-making. However, this approach can lead to data overload; executives leave the company but…", "content_html": "Sure, data is seen as the lifeblood of modern business. Companies are urged to collect as much data as possible, with the belief that more information leads to better insights and decision-making. However, this approach can lead to data overload; executives leave the company but their reports remain running. Products are depreciated but data collection remains. Automations and workflows may be misconfigured and trigger field updates that create a cascade effect on data flow.
\nEveryone has their pet data. Everyone has a beautiful report that they’ve built or a fantastic dashboard. They’ve persuaded IT to add new fields custom fields to the databases. They have adapted they’ve created automated workflows to sense and update changes on these fields. They run automated dashboards nightly. And then they leave the company, and these things keep flowing.
\nIt's easier than ever for businesses to collect vast amounts of data. From website analytics and customer interactions to social media metrics, the sheer volume of information available can be overwhelming. While having a wealth of data might seem advantageous, it often results in complexity and inefficiency. Sifting through terabytes of information to find actionable insights is not only time-consuming but also costly.
\nAdditionally, the more data you gather, the higher your storage and processing costs rise. Managing large datasets increases the risk of privacy violations, especially in an era where regulations like GDPR and CASL hold companies to stricter standards.
\n\n\nFrom a Revenue Orchestration standpoint, your Minimum Viable Data (MVD) is your Most Valuable Data. MVD=MVD.
\n
Simply, your salespeople know what handful of data points indicate a likely buyer, but organizations move hundreds or thousands of data points. Strip back to very basics. MVD may vary by audience or product, but there’s still only a few key indicators, the rest are less valuable for the ultimate goal; getting prospect to closed-won.
\nFocusing on MVD lowers data costs as you prioritize data flow. It helps with privacy enforcement as you’re tracking less and makes it easier to comply with GDPR and CASL.
\nMinimum Viable Data represents a paradigm shift in how businesses approach information collection and usage. The concept is simple: identify the smallest set of data points necessary to achieve your objectives, whether that’s identifying potential buyers, personalizing customer experiences, or optimizing marketing campaigns. MVD is about stripping away the noise and focusing on what truly drives value.
\nBack to your sales team. While they might have access to hundreds of data points about prospects, only a handful—such as recent purchases, engagement levels, or specific queries—are indicative of buying intent. By zeroing in on these key indicators, businesses can make more informed decisions without getting bogged down by irrelevant information.
\nFor instance, at one company, we found that are most highly-engaged audiences were students. We were delighted at their behavioral scores! They were engaged because they were researching and learning about the basics of typography, but had no intention to buy.
\nThe lowest scoring audiences? The VP who signs the contract. They log in, look at a couple of pages, sign the purchase order.
\nOur salespeople knew this, our marketers didn’t. They were focused on the wrong MVD.
\n\n\nThe lowest scoring audiences? The VP who signs the contract. They log in, look at a couple of pages, sign the purchase order. Our salespeople knew this, our marketers didn’t. They were focused on the wrong MVD.
\n
Adopting an MVD approach offers several advantages that directly impact a company’s bottom line and operational efficiency.
\nRevenue orchestration—the alignment of sales, marketing, and customer success efforts—relies heavily on data to function effectively. However, the complexity introduced by excessive data can hinder these processes. By focusing on MVD, businesses can ensure that their revenue orchestration efforts are powered by the most relevant and actionable information.
\nWhile the concept of MVD is universal, its application varies depending on your specific product, audience segmentation, and industry. What constitutes essential data for a SaaS company targeting small businesses might differ significantly from that of an e-commerce retailer catering to individual consumers.
\nTo identify your buyer’s MVD, start by asking fundamental questions:
\nMVD, like many of my fundamental tenets of good Revenue Orchestration architecture, requires investment in people over technology. Get sales and marketing and content people in a room with your product managers.
\nIt requires active executive participation to ensure that the groups will find concensous and overcome communication behavior patterns in order to have the direct conversations needed. It needs the teams to understand and respect each others’ business goals.
\nIt needs a collaborative environment for the teams to build a catalog of use case experiments that leverage that MVD. Because you need a good data flow, and the right data flowing.
\nYour Minimum Viable Data is your Most Valuable Data.
\nFind it. Funnel it.
", "author": { "name": "Bill Anderson" }, "tags": [ "Revenue Orchestration Architecture", "Marketing Technology", "Consulting" ], "date_published": "2025-06-20T12:08:00-04:00", "date_modified": "2026-04-16T13:31:10-04:00" }, { "id": "https://cwilliamanderson.com/revenue-orchestration-transformation-requires-active-executive-sponsorship/", "url": "https://cwilliamanderson.com/revenue-orchestration-transformation-requires-active-executive-sponsorship/", "title": "Revenue Orchestration transformation requires active executive sponsorship", "summary": "Executive sponsorship is critical here, because teams won't naturally work together Marketing is often comprised of people-pleasers who are uncomfortable having direct and challenging dialog with other teams Sales are hungry and action driven, often being perceived as being aggressive. Sales often doesn't fully understand…", "content_html": "Executive sponsorship is critical here, because teams won't naturally work together
\nMarketing is often comprised of people-pleasers who are uncomfortable having direct and challenging dialog with other teams
\nSales are hungry and action driven, often being perceived as being aggressive. Sales often doesn't fully understand what goes into a quality lead and often want MQLs too early, then complain about the quality of leads.
\nSales and marketing need to work together to define what is a quality lead:
\nExecutives must be involved and actively facilitate meetings as an impartial emcee at the early stages as both teams learn to speak one another's language.
\nSales and Marketing teams must maintain a regular review of lead quality in a collaborative, positive manner. These should be scheduled bi-monthly (every two weeks), or monthly at most. Quarterly is too long between sessions, and participants will fall back into their comfort roles and biases.
", "author": { "name": "Bill Anderson" }, "tags": [ ], "date_published": "2025-06-20T12:08:00-04:00", "date_modified": "2026-04-16T13:32:00-04:00" }, { "id": "https://cwilliamanderson.com/the-perfect-crm-i-once-met-a-real-unicorn-in-the-canadian-wilderness/", "url": "https://cwilliamanderson.com/the-perfect-crm-i-once-met-a-real-unicorn-in-the-canadian-wilderness/", "title": "The perfect CRM: I once met a real unicorn in the Canadian wilderness", "summary": "OK, maybe not the wilderness, wilderness. It was Toronto. I met Jamie Lee while building a Marketo instance for her. Her company was doing a ten-city tour and they wanted to use the system in six weeks, nearly half the time it takes for a…", "content_html": "OK, maybe not the wilderness, wilderness. It was Toronto. I met Jamie Lee while building a Marketo instance for her. Her company was doing a ten-city tour and they wanted to use the system in six weeks, nearly half the time it takes for a normal implementation. But Jamie Lee was supremely organized, so it worked.
\nTypically in an implementation, there comes a time when you have to connect a new marketing automation system to the Customer Relationship Manager (CRM). This is the time when the really ugly things come crawling out of the corporate gutter. Not here.
\nHer employer was a household-name investment firm renown for employing smart and thoughtful leaders. This organizational discipline came through in their CRM system. It was pristine. Sales diligently worked leads, documented all activity, and the consistency resulted in a nearly spotless database and quick, accurate reporting.
\n[Designed from ground up. Got the right people in the planning sessions. Strong executive oversight. Realized the importance of the system for profitablility and conveyed that to employees. Compensated sales on accurate and timely working within system (notes, conversion, dispositioning, etc)]
\nHow did this happen? The senior executives were actively engaged in the design and build of the project. They partnered with IT and Sales. And, most importantly, they tied the accurate and timely transitioning of leads to sales opportunities to the salespersons’ bonus. That’s right: you work the lead properly, you get your full commission.
", "author": { "name": "Bill Anderson" }, "tags": [ "Revenue Orchestration Architecture", "Marketing Technology", "Consulting" ], "date_published": "2025-06-20T12:07:00-04:00", "date_modified": "2026-04-16T13:32:24-04:00" }, { "id": "https://cwilliamanderson.com/sometimes-you-need-a-cto/", "url": "https://cwilliamanderson.com/sometimes-you-need-a-cto/", "title": "Sometimes, you need a CTO", "summary": "I once did a consultation with a national healthcare company. The tech setup: While they expected us to choose a software product for them, we ultimately advised them to hire a Chief Technology Officer.", "content_html": "I once did a consultation with a national healthcare company.
\nThe tech setup:
\nWhile they expected us to choose a software product for them, we ultimately advised them to hire a Chief Technology Officer.