Your search visitor is not in a funnel or a purchase journey, at least not from their perspective.

If they’ve arrived on your money page (from organic search or not…) it’s because they have a problem they’re in the midst of solving… And most importantly for you to understand: they visit your page as a member of a stakeholder committee.

Both your rankings AND your link campaigns will benefit from less SQUEEZE and more EEAT elements that enable efficient and effective purchase decisions for ALL the stakeholders.

And yes, you can use ChatGPT (4.0) for EEAT discovery!

EEAT on Money Pages = Enabling Purchase Decision Efficiencies for Stakeholders

Establishing and demonstrating EEAT on your money pages means enabling the visitor to make – and guide others – towards the best-possible decision for themselves and their committee of purchase decision stakeholders.

Money Page EEAT content must create efficiencies in the purchase decision process, for as many of the purchase decision stakeholders as time, space on the page and conversion rate will allow.

Here’s the good news about supporting stakeholders in the purchase decision process:

  • Very few marketers are providing the information to do this, extensively or well, especially at the money page level
  • You can use generative AI prompts below to figure out the helpful information “blanks” (for your experts or your expert-sourced data to fill in…)
  • EEAT on your money pages supports link campaigns
  • EEAT on your money pages is difficult to scale and will create a sustainable advantage
  • You get a chance to demonstrate your brand’s expertise (your organization’s perspective on generating practical efficiencies)
  • You’ll exhibit sympathy for and understanding of the visitor’s role within a stakeholder committee
  • Your engaging money-page user experience contributes positive engagement signals
  • You can inform your overall content strategy with new audiences, topic areas and data to gather

Let’s dive in!

Hi There! Allow Us to Introduce You to the Purchase Decision Committee…

You know that your search visitor has their own information needs that drove them to search in the first place (their intent).

Meet these needs and you’re more likely to get the sale, right? Sure! 


Often, your searcher is but one member of a larger purchase decision committee (which we’ve explained how to discover using AI previously though not as extensively). You must meet this initial emissary’s intent while supporting THEIR role in meeting the information needs of their full stakeholding committee. Enable them to take the role of CHAMPION, in which they’re willing to stake their reputation on your solution.

It’s by discovering your searcher’s stakeholders, and the information they’ll ALL require as they consider their purchase decision, that you can devise your expertise-supported content elements. These expertise-supported elements (which we call citable elements) will enable your initial searcher to serve as an informed champion with all of their participating stakeholders.

So let’s dig into this committee of purchase decision participants, of which your searcher is a contributing member. 

The Purchase Decision Committee

In this paper, Bonoma describes this committee as a “Buying Center.” And though his paper focused on B2B purchasing, the roles he discovered function for modeling out B2C decision stakeholders as well (or even an individual’s internal stakeholding parts). We use the phrase “initiating searcher” in places further on in this article, in reference to Bonoma’s model. 

Each role, from Initiator to Users, has a key perspective on the purchase and its potential benefit (or… detriment).

Each role has a varying degree of “veto power” over the decision as well. Internal hierarchies and prescribed titles may not align with Bonoma’s model, either.

He suggests for example that a close friend of a CEO might have an unusually high gate-keeping ability.

In Bonoma’s era, the early 80s, the Initiator of a sale didn’t have search engines, social media or the endless-content-containing potential of the internet. Nor, from our era’s perspective, had Bonoma thought through these stakeholders fully enough to fully inform a product page on a website. He certainly didn’t have AI available to help him brainstorm stakeholder perspectives for each and every product page…

Your duty, as a marketer, is to use your organization’s expertise to enable your market’s committees to make the best-possible decision (by challenging assumptions, filling in unrecognized infogaps and enabling an easy yes OR no from each stakeholder).

In other words:

“Chase What People Like”

(and we of course are making the assumption that people like making efficient and effective purchase decisions)

Source: Andy Simpson.

BrightonSEO SD, Nov 10, 2023

Enabling Money Page Visitors to Become Champions (Now With Even More EEAT!)

You may not be able to predict the initiator’s role within their organization, or ultimately who may become your offering’s internal purchase champion. 

Keyword demand does provide clues about the purchase committee roles who ARE using search engines to investigate their problems and the “Solutionscape…” but we still need to empower their role as potential champions of our offering. 

This means understanding and explaining “Benefit” from the perspectives of all stakeholders so that this self-appointed champion can clearly and effectively convince their fellow participants of the inherent correctness of the purchase decision.

Enabling a champion means educating them, from your money page, about things such as:

  • Purchase Decision Stakeholder Perspectives
  • Benefit to What, Felt by Whom?: Stakeholder Perspectives on “Objects of Benefit”
  • Wait, Is This Really the Right Solution?: Prompts for Diagnostic Accuracy, Resistance and Category-Level Alternatives
  • Empowering the Champion: Assessing and Addressing Cost Concerns of Fellow Stakeholders

Here are prompts you can use for researching each of these facets and uncovering opportunities for providing more expertise and data-supported decision assistance. Where it says <Your Offering> you can input either a category-level offering or a very specific “unit” of what you sell.

ChatGPT Prompt: Who are the Purchase Decision Stakeholders?

Within a Purchase Decision for <Your Offering>, there are often multiple participants, each with different perspectives on the value of the offering’s benefit. Some participants pay into the decision with financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion costs. Some participants pay into the decision with financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion costs.
* Some participants receive outcomes from the decision - some outcomes are wanted and some unwanted. These outcomes (positive or negative) include financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion costs.Please provide a list of purchase decision stakeholders for the offering. Beside each stakeholder please first predict their purchase decision veto power. Beside each stakeholder please predict their costs, or stake, as well as the outcomes or earnings, wanted and unwanted, they may receive from the offering once implemented.Lastly, provide a bulleted list of the stakeholders, with their title only, in order of their purchase decision veto power. No description.

Here’s the first of 7 stakeholders generated by input of “Inventory Management Software”:

Bulleted List of Stakeholders (Ordered by Veto Power):

  • CEO/Business Owner
  • Chief Financial Officer (CFO)
  • Chief Information Officer (CIO)/IT Manager
  • Operations Manager
  • Warehouse Manager
  • Purchasing Manager
  • End Users (Warehouse Staff, Inventory Clerks)

For some offerings, this prompt could be enough to discover user-valued EEAT topics that could enable and enhance the purchase decision.

Given the CEO’s high-level of veto power, we predict that this is a perspective we’ll need to address as we brainstorm and evaluate expertise and data-supported on-page elements to include:

CEO/Business Owner

  • Veto Power: High
  • Costs/Stake: Financial investment, reputational/status risks, strategic alignment.
  • Outcomes:
    • Wanted: Improved business efficiency, cost savings, enhanced reputation.
    • Unwanted: Financial loss if the software fails, potential disruption during implementation.

The “potential disruption during implementation” portion is especially important, from an EEAT perspective. Any stakeholder who’s convinced that your Inventory Management Software is the right choice will need to be prepared and capable of addressing this concern amongst their fellow stakeholders. 

In fact, there are multiple stakeholders who’d be concerned about potential disruptions during or due to implementation… so your champion will need to understand and answer this concern from multiple perspectives in order to be heard:

4. Operations Manager

  • Veto Power: Moderate
  • Costs/Stake: Operational adjustments, staff training.
  • Outcomes:
    • Wanted: Increased operational efficiency, better inventory control.
    • Unwanted: Operational disruption during transition, resistance from staff.

5. Warehouse Manager

  • Veto Power: Moderate
  • Costs/Stake: Changes in warehouse processes, staff retraining.
  • Outcomes:
    • Wanted: Improved inventory accuracy, space optimization.
    • Unwanted: Workflow disruption, initial decrease in productivity.

6. Purchasing Manager

  • Veto Power: Low to Moderate
  • Costs/Stake: Supplier coordination, process adjustment.
  • Outcomes:
    • Wanted: Streamlined purchasing processes, better data for decision-making.
    • Unwanted: Complexity in adapting to new systems, potential supplier issues.

Let’s assume this notion of “operational, day-to-day disruption during implementation” is our most-frequent area of concern amongst the purchase decision stakeholders. How do we address this concern with data and expertise that will make their purchase decision more efficient and effective?

Here’s a prompt you can use for this:

ChatGPT Prompt: operational, day-to-day disruption during implementation

Below is a list of purchase decision participants and their primary concerns regarding <your offering>:
* <input Your Offering's Stakeholders + Unwanted Outcomes. For example:
    * Business Owner: Potential disruption during implementation.
    * Operations Manager: Concerns: Operational disruption during transition, resistance from staff.
    * Warehouse Manager: Concerns: Workflow disruption, initial decrease in productivity.
    * Purchasing Manager: Concerns. Process adjustment, complexity in adapting to new systems.>
* For each stakeholder please describe 3 outside domains of expertise from which they could alleviate or address these concerns.
* For each stakeholder please draw from the domains of expertise to describe specific data points, key metrics, and specific examples that could help alleviate or prescribe action regarding their concern.
* For each stakeholder please draw from their 3 domains of expertise to describe best practices, approaches or general recommendations whose implementation could help to minimize the material impact of their concerns.
* For each stakeholder please describe case studies that could help them see a viable solution to their concerns.

For the first of our Stakeholders, the CEO, here’s what we get back:

1. Business Owner

Primary Concern: Potential disruption during implementation.

Domains of Expertise:

  • Change Management: Strategies to manage change effectively within an organization.
  • Project Management: Techniques for planning, executing, and monitoring projects.
  • Risk Management: Identifying, assessing, and controlling threats to an organization’s capital and earnings.

Data Points and Metrics:

  • Employee readiness surveys.
  • Project timelines and milestones.
  • Risk assessment reports.

Best Practices:

  • Develop a comprehensive change management plan.
  • Use project management tools to track progress.
  • Conduct a thorough risk analysis and develop mitigation strategies.

Based on ChatGPT’s predictions, you will need CEO-targeted advice and guidance from Change, Project and Risk Management experts. 

Space on the sales page is limited, precious and rightfully devoted to conversions from visitors, so you’ll have to do your research/studies and then present the highest-level best practices as snippets on the page. And it’s very likely you’ll need to place these snippets lower down on the page.

Additionally, notice that the best practices (change management plan, tracking progress with tools, risk analysis and mitigation strategy creation) all lend themselves nicely to the development of frameworks and blueprints that your visitors or users can download and review, to get a sense of the work required in the implementation. Training, videos, checklists and other transition support could be very helpful as well.

So, if you have enough new ideas, you could stop your exploration here and get started rounding up experts (who are published authors or established in their fields) as contributors for our creation of content (survey/research, video, webinar, longform content, frameworks/blueprints), for our audience of CEOs. 

You’d be wise to focus on issues of change, project and risk management from the other concerned stakeholders in your audience as well – because the implementation process framework will look very differently from the CEO’s desk vs. the Warehouse Manager! Audience matters, especially when this audience is part of a larger purchase decision committee.

Perhaps we haven’t fully understood the benefit of the offering though – how would our content change if we grasped the impact of our offering from the perspective of ALL of our stakeholders?

Your Offering’s Primary Benefits (for What Problems? for What “Objects”? for Which Stakeholders?)

We must first disentangle the concept of “Benefit” in order to enable AI to help us find useful content elements to add to the page. Our work on this model predates ChatGPT, as well as our discovery of the JTBD model, but both have greatly accelerated our process (as have G/C’s thoughts on Pain Point SEO).

Here’s our formal take on the marketing concept of “benefit,” an unmeshing that enables us to build out highly-effective prompts:

What you sell, your offering, has benefits that could potentially affect an “Object.” As an example, our offering at Citation Labs is links that we build to client URLs. The “object” that we affect are the search engine rankings of our clients’ URLs.

In our model we think of Your Offering as contributing in some way to the change from an “object state A” to an “object state B.” So the “State A” of our client rankings (the object) is “low” and the “State B,” after building links, is rankings for a target URL that are “high” (which we demonstrate in a report that goes along with our list of links acquired).

Expertise, on a money page, must create purchase-decision efficiencies for your visitors. Your brand’s expertise must enable a searcher (and the entire committee) to make the best possible choice regarding their pursuit of “State B” in the “Object.” Whether the best possible choice means a conversion or not… 

Good news if the above “benefit disentanglement” made little sense… You can use the following prompt to enable AI to disentangle it for you! Note that the prompts must educate ChatGPT on our model of benefit expression.

ChatGPT Prompt: Stakeholder Perspectives on “Objects of Benefit”:

* Below is a list of purchase decision stakeholders who may be involved in the purchase of , because of its potential Benefit.
    * <input some or all of the bulleted list of stakeholders from the above prompt>
* Please help us to make an addition to our understanding of each of these stakeholders by unpacking the Offering’s “Benefit,” from each stakeholder perspective.
* In our model of benefit we think of an “Offering” - the product or service for sale - as contributing in some way to the change of an “Object’s State”  from an unwanted array of conditions in “State A” to a desired array of conditions in “State B.”
* The object itself can’t be a person. For example if the offering is “food” then the Objects of Benefit would be things like: the person’s “pangs of hunger,” “blood sugar levels,” “the ability to exert cognitive energy,” “caloric deficit” or even “ability to sustain life”
* For each of the provided stakeholders in our list above, please predict their perspective-specific objects of benefit (please predict 3 objects per stakeholder) - that is, that which actually “receives” the benefit of the Offering. 
* For each object, please specify the observable, unwanted condition array of “State A” from the stakeholder’s immediate, day to day experience. Emphasize units of measurement and address costs or earnings that are financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion.
* For each unwanted condition of “State A,” please list the stakeholders who are most impacted.
* For each “Object,” please describe its “State B” from the stakeholder’s immediate, day to day experience. Emphasize units of measurement and address costs or earnings that are financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion.
* For each “Object of Benefit,” please describe the positive benefits - in the best case scenario - for the stakeholder if “State B” is reached in full.

For this exercise, it’s largely the observable, day-to-day unwanted conditions, prior to the implementation of your offering, that we’re seeking to capture as we discover our audiences’ needs for real-world, data-supported guidance and expertise. 

We examined the CEO perspective in our previous prompt, so let’s get a look at inventory management software from a completely different perspective, the Warehouse Manager:

5. Warehouse Manager

Objects of Benefit:

  1. Space Utilization
    • State A: Poor utilization of warehouse space.
    • State B: Optimized space utilization.
    • Benefits: More efficient use of space, cost savings.
  2. Inventory Turnover
    • State A: Slow inventory turnover.
    • State B: Faster, more efficient inventory turnover.
    • Benefits: Reduced holding costs, increased sales opportunities.
  3. Worker Safety
    • State A: Safety risks due to disorganized inventory.
    • State B: Improved safety standards.
    • Benefits: Fewer accidents, better compliance with safety regulations.

When we explore multiple perspectives on benefit we begin to recognize exactly how complicated the notion of EEAT really is!

Expertise, sure, but… Expertise for whom, from what perspective, and impacting what specific factors?

Useful, purchase-decision-assisting on-page expertise for a Warehouse Manager would look very different than that which would serve the CEO (whose objects of benefit were “Overall Business Efficiency,” “Market Reputation” and “Strategic Decision Making”).

ChatGPT Prompt: identifying stakeholder information/expertise needs – as they relate to the benefit of your offering. This prompt needs to be updated with the outputs from previous prompts.

We’d like to expand our understanding of a key stakeholder, <Input Stakeholder> in the purchase decision committee for <your offering>.
* We’ve already identified the offering’s Objects of Benefit from the stakeholder’s unique perspective, as well as the problems these benefits address (State A) and the ideal outcomes (State B) as exhibited in the following breakdown:
    * <Input the Stakeholder’s Perspective on Object of Benefit>
* Here’s the additional information we require, Per Object of Benefit:
    * Key “Governable” Metrics (or KPIs) that indicate that this Object of Benefit is improving or worsening
    * Domains of Expertise relevant to improving KPIs for each Object of Benefit
    * Trusted Outside Expert Types - fields of expertise, who could speak to improving this Object of Benefit
    * Information this Stakeholder Would Require as it relates to the Offering exerting efficiencies in the improvement of this Object of Benefit
    * What Questions Might This Stakeholder Not Know or Think to Ask About this Offering, as it relates to the object of benefit?

AI can really help in predicting how to meet these audience-specific expertise needs. Here are some of the questions predicted in relation to Warehouse Manager information needs for Space Utilization, Inventory Turnover and Worker Safety.

Space Utilization:

Warehouse Managers could certainly benefit from guidance around predicting warehouse space needs in relation to observable trends in the data! This is an area that you could illustrate with images pulled from the software itself, with expert-supported metrics and thresholds that help users connect what the software “sees” and upcoming spatial needs. Include quotes from actual warehouse managers on how and what they implemented in their physical warehouse based on software-enabled insights.

Unasked Questions:

  • How does the software adapt to changes in inventory types and volumes?
  • Can the software predict future space requirements based on trends?
  • How does the software handle multi-warehouse environments?

Inventory Turnover:

While the money page may not be the best place to write about inventory reduction practices, having some guidance on utilizing the tool for effective decision making – especially where to look, what specific numbers to examine – makes sense and should have some representation on the money page.

Unasked Questions:

  • How does the software assist in identifying slow-moving stock?
  • Can the software provide recommendations for inventory reduction?
  • How does the software facilitate just-in-time inventory practices?

Worker Safety:

In a warehouse, disorganization leads to worker injury (aisles cluttered by boxes and other materials). Your workplace cares about preventing injuries. And besides, these injuries contribute to compliance audits. These audits could have existential impact on the warehouse itself.

Unasked Questions:

  • Does the software integrate with health and safety compliance tools?
  • How can the software be used to train staff on safety practices?
  • Can the software generate safety performance reports for regulatory purposes?

The initial copywriter for the inventory management software page may not have recognized or realized these areas of impact that the software could have. Knowing this enables you to explore where and how in the tool you could identify or predict “clutter” or “unsafe warehouse aisles” and ultimately reduce injury. 

Does the safety/software connection belong on your money page? Certainly – especially if you’re able to conduct or cite/adapt existing research and expertise to demonstrate the connection and best practices enabled by the offering.

Purchase Decision Efficiency: Finding and Challenging Stakeholder Assumptions

We’ve covered prompts so far that can predict a potential array of purchase decision stakeholders, and explored each of these stakeholders’ perspectives on the actual benefit of your offering. 

From a purchase decision efficiency perspective, you, the seller of things, should be doing your utmost to enable people to DISQUALIFY any one of your offerings, particularly by rooting out and challenging their assumptions as well as the assumptions of their stakeholders. That’s not to say you won’t up or cross-sell them of course, but enabling efficient purchase decisions means providing enough information to know for sure that a given offering is not a fit.

Here are prompt pairings you can build, with output from the prompts you already ran, that can help you identify DISQUALIFIERS you can address or even add to your page. 

Your champions – the people who are convinced your offering is the right choice – will value these when they ultimately plead your (more expensive) offering’s case to their fellow members of the purchase decision stakeholder committee!

ChatGPT Prompt: Is This Really the Right Solution? Prompts for Challenging Diagnostic Accuracy, Resistance and Category-Level Alternatives from Stakeholder Perspectives

Below is a profile of a stakeholder - the solution search initiating stakeholder - involved in the purchase decision of <Your Offering>. Within the profile you’ll find a description of the “Objects” that the stakeholder cares about affecting with a potential purchase, along with the object’s pre-offering-implementation, or problematic, state (State A, with specific and concerning conditions) and it’s solution or post-offering-implementation state (State B, with alterations or changes in the conditions).
    * <input your selected/assumed Primary Stakeholder + Stakeholder Details from the 2nd prompt above, on “Stakeholder Objects of Benefit”>
    * <input one or more of the prompts below, as needed>
* For each Object of Benefit, please predict any difficulties that may exist in accurately diagnosing “State A.”
    * What assumptions or biases could exist that might cloud diagnosis?
    * What outside disciplines, experts and areas of expertise could assist in this diagnosis?
    * Could there be things causing “State A” that this stakeholder is overlooking or currently incapable of knowing?
    * List any useful units of measurement and estimates of material impact.
    * What kinds of questions would <High Veto-Power Stakeholder> ask to challenge assumptions made by the stakeholder?
* For each Object of Benefit, assume there is concern that the Offering may only treat a Symptom as opposed to a Root Cause of “State A.”
    * How “knowable” are Root Causes of “State A”?
    * What are other possible Root Causes of “State A”?
    * What other Root Cause assumptions might other stakeholders be more likely to make?
    * What are the sciences or disciplines behind making a definitive “State A” Root Cause diagnosis?
    * What kinds of questions would <High Veto-Power Stakeholder> ask to challenge cause/symptom assumptions made by the stakeholder?
* For each Object of Benefit assume a high-veto-power stakeholder is resistant to accepting that “State A” exists.
    * What might be the causes for this resistance?
    * What evidence should or could be provided by the other stakeholders? 
    * What outside experts, expertise and domain of practice could help in demonstrating that “State A” actually exists?  
    * List any useful units of measurement and estimates of material impact.
* Assume a high veto-power stakeholder is reluctant to accept that “State A” necessitates the purchase of the Offering.
    * What evidence from other stakeholders could help with this acceptance? 
    * What evidence or expertise could demonstrate a purchase is necessary at this time? 
    * List any useful units of measurement and estimates of material impact.
    * What are the viable alternatives to spending money on a solution at this time?
* Assume a high-veto power Stakeholder is concerned about potential unwanted outcomes, costs or side effects of the Offering and/or its Implementation.
    * What specifically might these unwanted outcomes, costs or side effects be?
    * To what degree, in what ways, would these concerns outweigh the benefits of “State B?”
    * How likely are these unwanted outcomes, costs or side effects?
* Assume a high-veto power Stakeholder would like to shop for category-level alternatives for addressing “State A” differently, with a different discipline, school-of-thought, professional modality or approach altogether.
    * What are these alternatives?
    * What criteria should be used in comparing or contrasting these alternatives?
    * What should column labels be in a comparison chart that provides insight into costs that are financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion related?
* Assume a high-veto power Stakeholder would like to understand the array of DIY solutions that could viably address “State A”.
    * How could the stakeholders viably address “State A” with their current resources?
    * Are there any common “DIY” solutions for “State A” that could enable the avoidance of costs that are financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion related?
* Assume a high-veto power Stakeholder would like to defer the decision and take a “wait and see” approach to the circumstances or conditions of “State A.”
    * How urgent, pressing or restrictive is “State A” across the stakeholders?
    * What are possible factors affecting “timeliness” of the decision, from other stakeholder perspectives?
    * Are there seasonal conditions that might have been overlooked by the initiating stakeholder?
    * How does deferring a response to “State A” affect the organization in terms of costs or earnings that are financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status, health/safety risks, education/training and/or physical/exhaustion.
    * What actual benefits might exist in adopting a “wait-and-see” position?
* For each Object, please describe the how, when and to whom the Stakeholder would report on “State B” to their manager.
    * To which stakeholders are they most likely to report?
    * What metrics would they use?
    * What are the offering’s material impact on achieving “State B,” in terms of costs or earnings that are financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational, education/training and/or physical/exhaustion?
    * What outside experts or expertise could verify that “State B” was achieved? What metrics would they use?

Enabling disqualification of an offering – think “is this offering right for you?” – provides some of the most useful possible decision outcomes.

This suggestion from ChatGPT is from the perspective of the Warehouse Manager as the initiating searcher. 

It helps illustrate that, though their issues are pressing, perhaps they could or should position the software as an aid in longer term organizational goals (ie, learn about long-term organizational goals)… Or use the “Gradual Adoption Plan” framework provided by the vendor to help the stakeholders feel comfortable in the rollout (a highly useful guide you could build based on data you gather and internal/external expertise).

Benefits of “Wait and See” Position

  • Market Development: Newer, potentially better solutions might emerge.
  • Financial Planning: Better alignment with budget cycles, preparation for the cost.
  • Strategic Alignment: Ensuring the solution aligns with long-term organizational goals.
  • Risk Mitigation: Time to assess potential risks and prepare mitigation strategies.
  • Staff Preparedness: Gradual preparation and training of staff for change.

In summary, while the “State A” presents challenges, especially from the perspective of the warehouse manager, other stakeholders might weigh these against strategic, financial, and operational considerations. The decision to deter, while potentially beneficial in some respects, could exacerbate exsting problems and lead to increased costs and risk in several areas.

Additionally, by sharing alternative solutions or methodologies you’re enabling your champions to do their due diligence and decision making assurance. 

For example, if the warehouse manager is your initiating searcher then, prior to assuming software will fix their warehouse issues they could try implementing the following concepts generated by the DIY portion above:

  1. Space Utilization:
  • Reorganize Layout: Analyze the current warehouse layout and identify areas that are underutilized or inefficient. Rearranging the storage layout to optimize space can be done without significant financial investments.
  • Vertical Storage: Utilize vertical space by installing taller shelving units. This increases storage capacity without expanding the warehouse’s footprint.
  • Declutter and Clean: Regularly declutter and organize the warehouse. Removing unnecessary items frees up space and improves operational efficiency.

They will demonstrate their capacity to appreciate other perspectives when they’re discussing objections with their fellow stakeholders, and show that they have taken or at least researched the DIY approach as far as possible for impacting their unwanted conditions.

Let’s more formally brainstorm and address objections in the final portion of this article, in which we empower a “champion” to understand every possible cost from each stakeholder perspective. 

Which stakeholder should you select as your champion? As an SEO you should think about the stakeholder most likely to be searching for your target keywords – additionally, consider adding the one who’s most likely to be an audience on other websites you’d like a link from…

Note that in this prompt we’re adding the <Target Stakeholder Role> in twice

ChatGPT Prompt: Empowering the Champion: Assessing and Addressing Concerns of Fellow Stakeholders

Please assume <Target Stakeholder Role> has decided that a “YES” decision for purchasing <Your Offering> presents the highest potential for optimal outcomes for themselves and their larger organization. They now wish to undertake the process of encouraging and enabling fellow members of the Purchase Decision Stakeholder Committee to arrive at this optimal decision, but from THEIR perspective. The intention to seek consensus amongst stakeholders - on behalf of our offering - makes them a “Champion.”
* We would like to empower, inform and educate the Champion, who has decided that a “YES” decision for purchasing <Your Offering> presents the highest potential for optimal outcomes, to enable others within the Purchase Decision Stakeholder Committee to arrive at the optimal decision from their perspective. 
* To this end we’d like your help in addressing stakeholder concerns by expressing and quantifying the “opportunity potential” from the to the following list of additional stakeholde 
    * <input list of 1 or more stakeholders>
* For each stakeholder, please enable the Champion to address the following areas of stakeholder concern: 
    * Per Stakeholder, Help the Champion Address Total Cost of Ownership Concerns 
        * Cost Concern Phases or Stages: 
            * Initial/Internal - Achieving Consensus from Stakeholders
            * Post-Purchase Implementation
            * Initial Benefit Optimization
            * Initial Detriment Minimization
            * Ongoing Usage/Optimization
            * Ongoing Maintenance
            * “End-of-Life” Transitioning to Next Solution
        * Actual “Costs” Per Phase May Include 
            * Financial
            * Time (from one or more stakeholders)
            * Human Resources
            * Materials/Ingredients
            * Tools
            * Emotional/Psychological/Trauma
            * Cognitive/Intellectual
            * Education/Training
            * Internal Reputational/Status
            * External Reputational/Status
            * Health/Safety
            * Physical/Exhaustion
            * Ecological/Social Impact
        * Per phase, what experts, expertise or specific data points would enable effective cost analysis?
        * What situational or circumstantial conditions could impact these costs?
        * In what ways could the benefits of purchasing and implementing <Your Offering> measurably outweigh the costs? For benefits focus on the occurrence of desired outcomes along the same continuum of costs.

Here’s what ChatGPT generated in terms of the CEO’s understanding of costs of ownership. These are the areas that your champion will definitely need to consider and become able to answer (after watching your videos and reading the results of your surveys):


  1. Initial/Internal – Achieving Consensus from Stakeholders:
    • Costs: Time in meetings and discussions, potential internal reputational risks.
    • Benefits: Alignment with strategic goals, improved overall efficiency, and competitiveness.
    • Expertise/Data: Financial analysts, ROI calculations, industry benchmarks.
  2. Post-Purchase Implementation:
    • Costs: Financial investment in software, human resources for implementation.
    • Benefits: Better data for strategic decision-making, improved operational efficiency.
    • Situations impacting costs: The complexity of the current system, vendor support quality.
  3. Initial Benefit Optimization:
    • Costs: Time and resources in fine-tuning the system.
    • Benefits: Increased efficiency, reduced waste, higher employee productivity
    • Expertise/Data: Operational metrics, efficiency studies.
  4. Ongoing Usage/Optimization:
    • Costs: Maintenance costs, ongoing training.
    • Benefits: Continuous improvement in operations, adaptability to market changes. Situational factors:
    • Market dynamics, technological advancements.
  5. End-of-Life Transitioning to Next Solution:
    • Costs: Financial, time, and resources in transitioning.
    • Benefits: Staying technologically up-to-date, maintaining competitive edge.
    • Expertise/Data: IT consultants, market trend analysis.

It’s possible, ok, probable, that as marketers we’ve become accustomed to obscuring some or most of these “costs of ownership” in the interest of keeping on-page conversion rates as high as possible. The benefit of being transparent about TCOs though, is vast.

For one, you increase the chance of future trust being placed in your organization by demonstrating that you place the visitors’ best interests before making money. That’s right – generating trust, real trust, from content on your sales page is actually THAT SIMPLE. 

Secondly, understanding and addressing TCOs from the perspective of all of your stakeholders will pack your sales page with EEAT in the form of citable elements that can super-charge your digital PR and other link building campaigns. 

An understanding of total costs – in relation to desired outcomes – demonstrates the apex of expertise you could share on a money page. And as a link builder, educating and empowering all the purchase stakeholder perspectives will open up vast new swathes of the internet for outreach and engagement.

Here are some further prompts for unpacking the kinds of content that could be on your money page, that would help your inciting searcher’s work in discussing TCO from the CEO perspective.

ChatGPT Prompt: Addressing cost concerns:

We’d like to address phase-specific cost concerns held by <high-veto power stakeholder>.
* The phase of ownership we’d like to address is: <enter phase of ownership, along with descriptions of cost and benefit>
* What factors should we learn from the concerned stakeholder in order to better estimate each of the costs (costs can be financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status internal, reputational/status external, health/safety risks, education/training and/or physical/exhaustion)?
* What metrics should be used in calculating the estimate?
* How could we express the calculation, mathematically?

We input the first phase of estimating TCO of inventory management software, or “Phase 1: Initial/Internal – Achieving Consensus from Stakeholders.” And while we all know meetings can be expensive, let’s unpack this aspect of cost that we’re asking the CEO to pay:

1. Time in Meetings and Discussions:

  • Duration and frequency of meetings.
  • Number of participants and their hourly rates.
  • Opportunity costs (what other tasks could participants be doing?).

This cost is material, but rarely addressed. And while we should certainly anticipate and meet information needs at these meetings, we should also help calculate costs here. Will this help us convert into a sale? Possibly not, but it could quickly help the visitor better understand what they’re asking of their stakeholding leadership.

Here’s the formula for estimating the time cost of the initial consensus-generating meetings:

Total Time Cost:

Total Time Cost = ∑(Hourly Ratei X Hoursi) + (Opportunity Costi X Hoursi)

Where i represents each participant.

To really bare down here, we could ask ChatGPT to help us hypothesize the total time spent, a hypothesis we could then test with our own research.

ChatGPT Prompt: Generate a hypothesis:

We’d like your help in estimating the total time cost of reaching a stakeholder consensus on the purchase decision of <input your Offering>

•	The stakeholders include: <input list of all previously discovered stakeholders>
•	The stakeholders must deliberate cost/benefit from the following parameters: financial, human/material resources, additional tools or tasks, maintenance, emotional/psychological, cognitive/intellectual, reputational/status internal, reputational/status external, health/safety risks, education/training and/or physical/exhaustion.
•	The stakeholders must deliberate cost/benefit from all stakeholder perspectives, as well.
•	How much time must each stakeholder spend in reaching consensus in a best and worst case?
•	How many meetings must each stakeholder attend, in a best and worst case scenario?
•	Assuming average salaries for each stakeholder, what is the hard cost estimate for best and worst cases?
•	What is the opportunity cost estimate for each stakeholder?
•	Please sum all the final hard cost estimates as well as opportunity cost estimates.

Here’s best/worst case scenario output for time spent and meeting volumes for the initial consensus-finding phase:

Time and Meeting Estimates:
Best Case Scenario:

  • Time Spent: Minimal – stakeholders are well-informed and largely agree.
  • Meetings Attended: Few – efficient, focused meetings.
    Worst Case Scenario:
  • Time Spent: Extensive – significant disagreements or lack of information.
  • Meetings Attended: Many – repeated meetings to resolve issues and reach consensus.

Based on these average costs:

Average Salaries:
We’ll use U.S. national average salaries for estimation. The figures may vary based on location and
company size.

  1. CEO/Business Owner: $160,000/year
  2. CFO: $140,000/year
  3. CIO: $150,000/year
  4. Operations Manager: $100,000/year
  5. Warehouse Manager: $85,000/year
  6. Purchasing Manager: $95,000/year
  7. Warehouse Staff: $40,000/year

ChatGPT estimates that we’re asking the stakeholders for a financial investment – for the initial consensus phase alone – of up to $4400.

The estimated hard costs for reaching a consensus on the purchase decision of Inventory Management Software are as follows:

Best Case Scenario:

  • Total Hard Cost Estimate: $740.38

Worst Case Scenario:

  • Total Hard Cost Estimate: $4,442.31

No one has ponied up for the actual offering yet – this is chatgpt-estimated costs for a group of purchase decision stakeholders to reach consensus that a purchase should or shouldn’t be made. To be fair, ChatGPT predicted different estimates each time we ran it, so perhaps you should simply build a calculator for this particular phase… here are the calculations that ChatGPT utilized, for your consideration in developing data/expertise-supported content for your sales pages:

Inputs Needed:

  1. Salaries of Each Stakeholder: Annual salaries or hourly rates.
  2. Number of Stakeholders: Total number involved in the decision process.
  3. Meeting Duration: Estimated length of each meeting (in hours).
  4. Number of Meetings (Best and Worst Case): Estimated number of meetings for best and worst-case scenarios.
  5. Decision Phases: Number of phases in the decision-making process.
  6. Opportunity Cost Rate: A percentage to calculate the value of time spent by each stakeholder (commonly 25%).


  1. Hourly Rate for Each Stakeholder:
    • If annual salaries are provided, calculate the hourly rate: Hourly Rate=Annual Salary52×40Hourly Rate=52×40Annual Salary​
  2. Total Time Spent in Meetings (for both best and worst cases):
    • Total Time Spent=Number of Meetings×Meeting DurationTotal Time Spent=Number of Meetings×Meeting Duration
    • Calculate separately for best and worst-case scenarios.
  3. Hard Cost for Each Stakeholder:
    • Hard Cost=Hourly Rate×Total Time SpentHard Cost=Hourly Rate×Total Time Spent
    • Sum the hard costs for all stakeholders for both scenarios.
  4. Opportunity Cost for Each Stakeholder:
    • Opportunity Cost=Hourly Rate×Opportunity Cost Rate×Total Time SpentOpportunity Cost=Hourly Rate×Opportunity Cost Rate×Total Time Spent
    • Sum the opportunity costs for all stakeholders for both scenarios.
  5. Total Hard Cost and Total Opportunity Cost:
    • Sum the individual hard costs and opportunity costs for all stakeholders to get the total for each scenario.

Are we suggesting that each sales page should include a cost estimator for arriving at consensus amongst the stakeholders? If consensus has a measurable cost then YES, especially if you can then enable stakeholders to reduce costs by fully preparing themselves – with data and expertise – for each other’s questions. 

EEAT On a Money Page 

Demonstrate your brand’s expertise – on the money page – by fully preparing ALL stakeholders to reach consensus on the purchase decision. You do this by expressing and exhibiting the offering’s costs/benefits across its entire lifespan, from each stakeholder perspective. 

You can’t rank for unsearched keywords, but you CAN enable highly effective purchase decisions by anticipating and answering stakeholder information needs with unique data and insights (…that also fuel link building campaigns).

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