Prepping 2026 Strategy Planning Sessions

Question #1: We’ve held pricing steady…but how much can we realistically increase without losing customers?

This question comes from companies navigating a particularly challenging environment. 2025 saw many companies reforecasting their profitability numbers while also experiencing substantial margin pressures. After years of absorbing inflation, supply chain disruptions, and rising input costs, many organizations held pricing steady to maintain customer relationships and market share.

But now, with continued cost pressures and the need to protect profitability, business leaders are asking: how much pricing power do we actually have?

What makes this particularly tricky is that pricing isn’t just about covering costs. It’s deeply psychological. Price a product too high and customers walk away. Price too low and customers question quality, or worse, you leave significant revenue on the table.

This is where many organizations get stuck. They have hunches about what customers might tolerate, but acting on guesswork in today’s environment feels especially risky.

How To Answer This Question:

The good news is that pricing research removes the guesswork. Rather than relying on intuition or simply matching competitor pricing, research gives you objective data on what your specific customers will tolerate. We typically recommend one of three approaches:

Price Elasticity Studies (Gabor-Granger Method): This approach tests different price points with your target customers to understand exactly how demand changes as price increases. By measuring purchase intent at various price levels, you identify the optimal price that maximizes revenue without sacrificing too much volume.

Van Westendorp Price Sensitivity Meter: Sometimes the challenge isn’t just finding a single optimal price, it’s understanding the acceptable range. The Van Westendorp method reveals not just a single price point, but your strategic pricing range, showing you both your floor and ceiling, and where within that range you should position based on your brand strategy.

Conjoint Analysis with Price as an Attribute: If you’re dealing with multiple product configurations or service tiers, conjoint analysis simulates real purchase decisions. It reveals not just what people will pay, but what they’ll pay for and which features justify premium pricing.

Question #2: We’re adding AI features to our product…but where do customers actually want AI versus where don’t they?

This question comes from companies responding to the AI arms race. Every competitor seems to be launching AI-powered features, and the pressure to follow suit is intense. But here’s the uncomfortable reality: customers don’t necessarily want to see AI everywhere.

Context matters enormously, and getting it wrong damages trust. Simply slapping “AI-powered” into a product description doesn’t create value and can actually backfire. But if you avoid AI where customers actually want efficiency and speed, you fall behind competitors who get it right.

How To Answer This Question:

Product concept testing removes the guesswork about where AI adds value. Rather than building features based on what’s technically possible or what competitors are doing, research reveals where customers actually want AI and where they don’t. We typically recommend one of three approaches:

AI Feature Concept Testing: This approach tests different AI-powered features alongside their non-AI equivalents to measure relative appeal and purchase intent. By exposing customers to various implementations, you see which AI features drive excitement and which create hesitation. This is especially valuable when you have multiple AI features under consideration and need to prioritize which ones to build first.

Jobs-to-be-Done Research with AI Context: Sometimes the issue isn’t just testing features, it’s understanding the underlying customer needs and whether AI helps or hinders those needs. This research identifies what customers are truly trying to accomplish, then evaluates how AI-powered solutions compare to traditional approaches. You’ll discover which jobs customers are happy to delegate to AI and which require the human touch.

Question #3: Customers want personalization…but how much is creepy versus helpful?

This question comes from companies caught in a frustrating paradox. Many customers now expect personalized experiences, but getting personalization wrong erodes trust. Customers want you to know them well enough to serve them better, but not so well that it feels invasive.

What makes this especially tricky is that the line between helpful and creepy shifts depending on context. Consumers may be comfortable with companies using their purchase history and website visits for personalization, but likely less comfortable with companies accessing financial information and social media posts.

Too little personalization feels generic and wasteful. Too much feels intrusive and surveillance-like. The sweet spot sits somewhere in the middle, but that middle varies by industry, product category, and customer segment.

How To Answer This Question:

Personalization research reveals where customers draw the line between helpful and invasive. Rather than assuming what level of personalization customers want, or defaulting to what’s technically possible, research shows you exactly how much personalization drives engagement versus discomfort. We typically recommend one of wo approaches:

Personalization Preference Studies: This approach tests different levels of personalization with your customers to identify the optimal degree. By exposing them to low, moderate, and high personalization scenarios, you measure which level generates the most positive response and purchase intent. You’ll see exactly where helpfulness peaks and where the creep factor kicks in for your specific audience.

Data Type Comfort Assessment: Sometimes the issue isn’t the degree of personalization, it’s the type of data being used. This research evaluates customer comfort levels with different data sources like purchase history, browsing behavior, location data, or social media activity. You’ll understand which data types feel acceptable for personalization and which trigger privacy concerns, letting you build experiences within your customers’ comfort zones.

Question #4: Everyone’s talking about sustainability…but do our customers actually care enough to pay for it?

This question comes from companies navigating a frustrating paradox. Consumers say they’ll pay more for sustainable packaging yet when given the chance to do so, they default to less expensive options. The gap between stated intentions and actual behavior is real and costly.

Different customer segments have fundamentally different sustainability purchase thresholds, and treating them all the same means over-investing in features some segments won’t pay for while under-serving segments that would.

How To Answer This Question:

Sustainability research reveals which customers will actually pay for sustainable features and what premium they’ll tolerate. Rather than assuming all customers care equally or guessing at acceptable price points, research shows you exactly where sustainability creates value worth paying for. We typically recommend one of three approaches:

Willingness-to-Pay for Sustainability Features: This approach tests different sustainability attributes alongside price premiums to identify which specific features justify higher prices. By measuring purchase intent across various sustainability claims like recycled materials, carbon-neutral production, or ethical sourcing, you see which elements drive willingness to pay and which are expected table stakes. This prevents over-investing in sustainability features customers won’t pay extra for.

Customer Segmentation with Sustainability Profiling: Sometimes the issue isn’t whether customers care about sustainability, it’s identifying which customer segments care enough to act on it. This research segments your market by sustainability priorities, purchase behavior, and price sensitivity. You’ll understand which segments are true sustainability adopters versus those who express interest but won’t pay premiums, letting you target and message appropriately.

Sustainability Value Proposition Testing: This approach tests how you communicate sustainability benefits to maximize perceived value. By evaluating different messaging frames like environmental impact reduction, health benefits, or ethical production, you identify which positioning resonates most strongly and justifies premium pricing. You’ll discover whether customers respond better to quantified impact statements, certifications, or transparency about your practices.

Question #5: We have multiple customer segments…but which ones will actually drive growth in this economy?

This question comes from companies feeling the strain of economic polarization.  High earners continue spending on experiences and premium products, while lower and middle-income consumers are switching brands and trading down to private label options. What makes this especially challenging is that many consumers are already spending as if the economy is in a recession.

Here’s the uncomfortable truth: not all customer segments are created equal, especially during uncertain times. The risk is that companies continue spreading resources across segments that made sense historically but don’t make sense now. Without clarity on which segments offer the best return on investment in this environment, you’re likely over-investing in low-growth areas while under-investing in your most valuable opportunities.

How To Answer This Question:

Segmentation research gives you the clarity to make strategic resource allocation decisions. Rather than treating all customers the same or relying on outdated assumptions, research reveals which segments have the strongest growth potential given current conditions. We typically recommend one of three approaches:

Value-Based Customer Segmentation: This approach groups customers by their economic value to your business, using metrics like customer lifetime value, purchase frequency, and average order value. It reveals which segments are most profitable and resilient, helping you focus acquisition and retention efforts where they’ll yield the highest returns. Knowing who drives the most value lets you protect what matters most.

Needs-Based Segmentation with Economic Profiling: Sometimes the issue isn’t just understanding value, it’s understanding which customer needs are most recession-resistant or growth-oriented. This research identifies distinct customer groups based on their core needs, then overlays economic resilience indicators like income stability, spending patterns, and category engagement. You’ll see which needs-based segments remain strong buyers even when conditions get tough.

Growth Potential Segmentation: This forward-looking approach evaluates segments not just on current value, but on expansion potential. It assesses factors like segment size, growth trajectory, competitive saturation, and willingness to increase spending. This is especially valuable when you need to make portfolio decisions about which segments deserve incremental investment versus maintenance-level attention.

Prioritizing Your 2026 Strategy Game Plan

The list of strategic questions above is no small feat to answer. In fact, most organizations can’t explore all of these questions at any given time. They simply don’t have the resources.

How then, do you prioritize what to tackle? We always say follow the data! Consider these signals:

Gross margins are compressing quarter over quarter… It’s time to understand your pricing power. If you’re absorbing costs without testing customer tolerance, you’re likely leaving revenue on the table or heading toward unsustainable margins.

Customer acquisition costs are rising while conversion rates fall… This suggests you’re targeting the wrong segments or your value proposition isn’t landing. Start with segmentation research to identify which customers offer the best growth potential, then refine your positioning for those segments.

You’re launching AI features but adoption is lower than expected… Customers may not want AI where you’re putting it. Product concept research will reveal where AI adds genuine value versus where it creates friction or distrust.

Customer complaints about privacy or “creepy” experiences are increasing… You’ve crossed the personalization line. Research the tradeoffs customers are willing to make and recalibrate before you damage trust further.

Sustainability investments aren’t translating to sales or loyalty… You may be over-investing in features customers won’t pay for, or under-communicating value to segments that would. Test willingness-to-pay and value proposition messaging to find the right balance.

In essence, use your business data to guide your 2026 strategy planning. Let the pain points in your metrics tell you which strategic questions deserve your attention first. And if you haven’t made a point of collecting historical benchmarks to guide this process, consider making that a priority in the new year.