Optimized Pricing

Your costs have increased substantially over the past year. Raw materials are up 12%, labor costs have climbed 8%, and those ?!?!? tariffs we discussed in issue #6 have added another layer of complexity. And don't forget about inflation...

You know you need to adjust your prices, but how much? Push too high, and you'll lose customers. Too low, and you're leaving money on the table - or worse, operating at a loss. And what about those competitors who seem to be absorbing cost increases? Can you afford to do the same?

Pricing decisions used to be gut instinct mixed with basic math. But in today's rapidly changing environment, that approach won't cut it. Fortunately, generative AI can transform pricing from an occasional, anxiety-inducing event into a strategic capability that consistently captures your true value.

Here's how.

Step 1:
Identify Your Pricing Strategy

Businesses typically fall into one of four categories when it comes to pricing strategy, based on whether you offer products or services, and whether you compete primarily on cost or differentiation. In some cases, larger businesses may have products or services spread across these strategies. 

Take a moment to identify which quadrant best describes your business in this simple 2x2 of "products / services" and "low cost / differentiated":

• Low-Cost Products: You sell physical goods and compete primarily on price (e.g., discount retailers, commodity manufacturers, generic products)
• Differentiated Products: You sell physical goods with unique features or brand value that command premium prices (e.g., luxury goods, specialized equipment, patented innovations)
• Low-Cost Services: You provide services where efficiency and competitive pricing are key selling points (e.g., basic accounting, standard legal services, routine maintenance)
• Differentiated Services: You offer specialized expertise or exceptional experiences that justify premium rates (e.g., strategic consulting, high-end design, concierge services)

Each quadrant faces unique pricing challenges:

• Low-Cost Products: How do you compete on price while maintaining margins?
• Differentiated Products: How do you quantify and capture value beyond cost?
• Low-Cost Services: How do you balance efficiency with human-delivered value?
• Differentiated Services: How do you command and maintian premium pricing?

AI transforms pricing strategy in all four quadrants, but the approach varies significantly based on where your business fits. Throughout this guide, I'll outline strategies for each quadrant so you can find what's most relevant to your situation.

Start a chat and start by asking your AI assistant to help you clarify your position:

Based on our business model, products/services, and competitive positioning, which pricing quadrant do we primarily operate in? Analyze:
1. Our current pricing relative to competitors
2. Whether we emphasize cost advantages or unique value
3. If our offerings are primarily products or services
4. How our customers perceive our value proposition

Help me determine if we are primarily a Low-Cost Products, Differentiated Products, Low-Cost Services, or Differentiated Services business, and what that means for our pricing strategy.

Step 2:
Analyze Your Current Pricing

Once you've identified which quadrant your business primarily operates in, the next step is understanding exactly where you stand today. Time to build a Pricing Analyst jig.

Create a new GPT (ChatGPT), Project (Claude), or Gem (Gemini) with custom instructions like:

You are my AI Pricing Analyst. Your purpose is to help me evaluate our current pricing strategy and identify opportunities for optimization based on market conditions, competitive positioning, and internal data.

Analysis Areas:
- Analyze our price points relative to competitors and our positioning
- Identify products/services with pricing misalignment (too high or too low)
- Calculate price elasticity across our offerings
- Detect hidden price leaks (excessive discounts, inconsistent negotiations, etc.)
- Recognize where we're leaving money on the table or pricing ourselves out of competition

When analyzing data, consider:
- Our position in the market (cost leader vs. differentiated)
- The perceived value of our offerings
- Customer purchasing behavior and price sensitivity
- Competitive landscape and pricing trends
- Internal costs and margin requirements

Format your analysis as:
1. Current State Assessment: Overview of our pricing effectiveness
2. Key Opportunities: Specific areas where pricing could be improved
3. Risk Areas: Products/services with problematic pricing
4. Strategic Options: Potential approaches to optimize pricing

Tone: Data-driven, practical, and focused on actionable insights rather than theoretical pricing models.

Upload relevant pricing information to your jig's knowledge:

• Your current price lists
• Recent sales data (including any discounting)
• Cost structures for products/services
• Any customer feedback related to pricing
• Market research you've conducted

Deep Competitive Research

Understanding your competitors' pricing is crucial, but many businesses make this harder than it needs to be. The days of sending employees to take photos of shelf prices or calling for quotes under false pretenses are over. The recent(ish) generative AI "deep research" capabilities can compile comprehensive competitive pricing data in minutes.

Turn on "deep research" in ChatGPT or Gemini, turn on "web search" and "extended thinking" in Claude and try this prompt in just a regular chat, not in your jig:

I need a competitive pricing analysis for [your product/service category]. Please research current pricing for the top competitors in this space, including:

1. [Competitor 1]
2. [Competitor 2]
3. [Competitor 3]

For each competitor, identify:
- Base price points for comparable offerings
- Pricing structure (flat fee, tiered, usage-based, etc.)
- Current promotions or discounts
- Any premium or enterprise options
- How they communicate their value proposition

Present the results in a table for easy comparison, with additional analysis of how our pricing compares to the market average. Include columns for Competitor, Base Price, Structure, Current Promotions, Premium Options , and Value Proposition.

This kind of a structured comparison is invaluable for positioning your offerings effectively. But don't stop there. Dig deeper with follow-up questions (just make sure to turn off the "deep research" setting before you ask follow-ups, otherwise it will start new research reports; with Gemini you get unlimited deep research queries, with ChatGPT you have a limited number each month dependent on your plan):

Based on this competitive analysis, which of our offerings appear to be:
1. Underpriced relative to competitors (leaving money on the table)
2. Overpriced without sufficient value differentiation (at risk of losing sales)
3. Aligned with the market but missing opportunities to differentiate

For each quadrant in our matrix, AI can uncover specific competitive insights:

Low-Cost Products: "Which competitors are using loss-leaders? What volume thresholds trigger their discounts?"

Differentiated Products: "What premium features do competitors highlight to justify higher prices? How do they quantify value?"

Low-Cost Services: "How do competitors maintain efficiency? What services have they automated or standardized?"

Differentiated Services: "What intangible benefits do competitors emphasize? How do they structure tiered service packages?"

The goal isn't just to understand current prices, but to decode the pricing strategy behind them. AI can identify patterns across dozens of competitors in a fraction of the time it would take manually.

Step 3:
AI-Powered Price Optimization

With a clear understanding of your position in the pricing matrix and your current pricing effectiveness, it's time to develop optimized pricing strategies tailored to your specific quadrant.

Low-Cost Products

For businesses competing primarily on price with physical goods, the challenge is maintaining margins while remaining competitive. Your "Pricing Analyst" jig can help with prompts like:

Based on our cost structure and competitive analysis, help me develop a dynamic pricing strategy for our product line that:
1. Maintains our position as a value leader
2. Protects margins against rising supply costs
3. Creates strategic price differentiation from key competitors
4. Optimizes for overall profit rather than unit margins

For each product category, recommend specific price points and positioning strategies.
This approach helps you move beyond simple cost-plus pricing to strategic pricing that considers competitor positioning, customer psychology, and market dynamics.

For low-cost products, consider AI-generated "price fencing" strategies—creating conditions under which price-sensitive customers get lower prices while others pay full price. These might include volume discounts, loyalty programs, or limited-time promotions that minimize margin impact.

Differentiated Products

For premium product businesses, the key is quantifying and communicating value rather than competing on price. Try prompts like:

Analyze our product features compared to competitors and identify:
1. Which unique features deliver the highest perceived value to customers
2. How we should quantify the ROI or benefit of these features
3. How to structure our pricing to highlight our differentiation
4. Specific market segments that would value our differentiators enough to pay a premium

Develop a value-based pricing strategy that focuses on our unique strengths.

For differentiated products, also explore price anchoring strategies—where higher-priced premium options make your standard offerings seem more reasonable. AI can help design optimal "good-better-best" pricing tiers that maximize overall revenue.

Low-Cost Services

Service businesses competing on price face unique challenges in balancing efficiency with quality. Your jig can help with prompts like:

Based on our service delivery costs and competitive landscape, help me:
1. Identify which service components could be unbundled to create a lower entry price point
2. Develop a tiered service model that allows customers to self-select based on needs
3. Design optional add-ons that increase average transaction value
4. Optimize our service process to reduce delivery costs without impacting quality

Create a pricing structure that attracts price-sensitive clients while encouraging upgrades.

For low-cost services, AI can also help design subscription or retainer models that smooth revenue while providing clients with predictable pricing—creating a win-win that differentiates you from purely transactional competitors.

Differentiated Services

Premium service providers need strategies that capture the full value of their expertise and results. Try prompts like:

Examine our service outcomes and client results to:
1. Quantify the tangible and intangible value we provide
2. Identify opportunities for outcome-based or value-share pricing models
3. Develop premium service tiers that appeal to different client segments
4. Create a compelling narrative that justifies our premium positioning

Design a pricing approach that reflects the true value we deliver rather than just the time spent.

For differentiated services, consider AI-generated proposals for "results-based" pricing models where appropriate—sharing in the upside when you deliver exceptional outcomes. This aligns your incentives with clients while potentially increasing overall revenue.

If you want to dig deeper into strategy fundamentals, check out this excellent article by Roger Martin, which provides an excellent foundation for thinking about how pricing connects to your overall competitive positioning.

Step 4:
Test and Iterate

After developing optimized pricing strategies for your specific quadrant, the next step is testing them in the real world. Many businesses skip this crucial phase, implementing company-wide price changes without validating them first.

Design Controlled Price Experiments

For businesses that can run pricing experiments (particularly e-commerce, SaaS, or high-volume services), AI can help design rigorous tests:

Help me design a controlled pricing experiment to test our new strategy for [product/service]. The experiment should:
1. Test specific price points against our current baseline
2. Include a clear methodology for measuring results
3. Control for external factors that could skew the data
4. Define success metrics and minimum sample sizes
5. Specify the duration needed for statistically valid results

Create a complete experiment plan that my team can implement immediately.

For businesses that can't easily run pricing experiments (professional services, B2B with few clients, etc.), there are alternatives. One powerful approach is willingness-to-pay research, where you pay participants to give brutally honest feedback about pricing. I'm particularly fond of a methodology from the excellent (if a bit dry) book Monetizing Innovation. 

AI can help design these sessions:

Create a willingness-to-pay research protocol for our [service/product] using the methodology from Moneitizing Innovation by Ramanumam and Tacke that includes:
1. Screening criteria to find relevant participants
2. A discussion guide with non-leading questions about value perception
3. Various pricing scenarios to test reactions
4. Methods for encouraging honest rather than socially acceptable responses
5. Analysis framework to translate findings into actionable insights

Include specific compensation amounts to encourage participation and honest feedback.

The key is paying participants enough to unlock the brutal truth—I recommend $100-400+ for B2B contexts and $50-75 for consumer research; pay people what they think their time is worth if you want to get better participation. Make it clear that you're compensating them for their honesty, not their approval. When someone is paid well to be brutally honest, they often will be.

Analyze Results and Refine

Once you've gathered experimental data or research insights, AI can help extract meaningful patterns:

Based on our pricing experiment results, please:
1. Identify which customer segments responded positively/negatively to changes
2. Calculate the overall revenue and profit impact of each test pricing model
3. Highlight unexpected findings or anomalies in the data
4. Recommend refinements to our pricing strategy based on these results

What patterns should guide our pricing decisions going forward?

This iterative approach transforms pricing from a one-time decision to a continuous optimization process, allowing you to adapt to changing market conditions and customer preferences in real-time.

Step 5:
Communication and Implementation

Even the best pricing strategy fails if poorly implemented. This is where many businesses stumble—developing solid strategies but executing them ineffectively.

Internal Change Management

Start by ensuring your team understands and supports the new pricing approach. Create training materials using prompts like:

Create internal training materials to help our sales team understand and communicate our new pricing strategy. Include:
1. The key value drivers that justify our pricing
2. Specific language to use when discussing price with customers
3. Responses to common objections or questions
4. Guidelines for when/how to apply discretionary discounts (if applicable)

Format this as a concise playbook our team can reference during customer conversations.

This internal alignment is crucial—if your team doesn't believe in your pricing, customers certainly won't.

Customer Communication

For existing customers facing price increases, thoughtful communication is essential. Your jig can help craft messages like:

Draft a customer communication plan for our upcoming price adjustment that:
1. Explains the value we've delivered and will continue to provide
2. Transparently addresses the factors necessitating the change
3. Emphasizes the investments we're making to improve their experience
4. Provides clear timing and details about the changes
5. Offers options or alternatives where appropriate

Create versions tailored to different customer segments based on their relationship with us.

Personalization is key here—mass emails announcing price increases often backfire. AI can help segment your customer base and tailor messages to each group's specific concerns and value perception. Don't forget about the strategies we discussed in #7 about on-brand content. 

Implementation Rollout

Finally, develop a phased implementation plan:

Create a 90-day implementation plan for our new pricing strategy that includes:
1. Timeline for rolling out changes to different customer segments
2. Key metrics to track during implementation
3. Trigger points for possible adjustments if results differ from expectations
4. Communication checkpoints with customers and internal teams
5. Contingency plans for various market reactions

Design this as a flexible roadmap that balances speed with risk management.

This structured approach minimizes disruption while giving you visibility into results as they emerge, allowing for timely course correction if needed.

The Bottom Line

Pricing is perhaps the most powerful lever you can pull to improve profitability. A 1% price improvement typically flows directly to your bottom line, generating an 8-12% increase in operating profit for most businesses. Even small optimizations compound dramatically over time.

The approaches outlined here transforms pricing from an occasional, reactive event into a strategic capability that consistently captures your true value. Whether you're selling products or services, competing on cost or differentiation, AI-powered pricing strategies give you the tools to make confident decisions based on data rather than gut feeling.

Most importantly, this approach helps you break free from the false binary of "raise prices or absorb costs." The businesses that thrive in volatile markets are those that find creative pricing structures that align with customer needs while protecting their own viability.

In a world where costs and competitive landscapes change weekly, your pricing strategy must evolve from static to dynamic, from reactive to proactive, from guesswork to insight-driven. Generative AI makes this evolution accessible to businesses of any size—giving you the pricing intelligence that was once available only to the largest enterprises with dedicated pricing teams.

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