Niel Chaubal is a seasoned finance and pricing executive with over a decade of leadership experience across Fortune 500 companies and private equity-backed businesses. He specializes in strategic pricing, revenue management, and business intelligence, with a proven record of driving multimillion-dollar growth and profitability. Niel has led pricing and analytics teams at organizations including Cardinal Health, Covetrus, Party City, and Sears, where he built best-in-class pricing frameworks, revenue optimization strategies, and analytics capabilities. Today, as Managing Partner at ProfitQI, he advises industrial and mid-market firms on pricing transformation, revenue management, and AI-enabled analytics.
PART II: This is an excerpt from a long-form discussion between Niel Chaubal & Tim Ouimet. Click here to read Part I.
TO: That’s a powerful illustration of how pricing isn’t just math—it’s perception. And yet, even with the right framing or psychological tactics, things can still go sideways if the pricing team isn’t in sync with the rest of the business. What other skills do you think a pricing leader needs to be effective?
ALIGNING PRICING STRATEGY WITH BUSINESS STRATEGY
NC: Thanks for the question, a lot of pricing professionals today miss the need for business acumen and critical thinking.
As a pricing leader, you really need to understand the business (what makes it tick), the product attributes, what do the categories stand for that you’re pricing. In my experience, in many cases pricing strategy and business strategy are often misaligned. Business has one direction; pricing is pulling in another. Pricing team are optimizing prices without understanding what the category wants to achieve or what the business objectives are. This disconnect is a major business problem.
Next, critical thinking is an essential qualification. The market is constantly changing. Customer mindset, expectations, purchasing behaviors — they are all evolving rapidly. Pricing professionals need to stay on top of these shifts and adapt. That might mean changing pricing models or even rethinking how the business communicates value.
The third and most important skill, in my opinion, is communication and influence. A lot of pricing professionals, including me, come from analytical backgrounds. We’re very comfortable with data, numbers, models. But if you can’t communicate effectively or get stakeholders aligned, then even the best pricing strategy will fail.
I’ve seen this happen first-hand. If key stakeholders don’t trust or understand what you’re doing, they won’t support your initiatives. That’s why everyone in sales, marketing, and product have to be aligned on the value of a product or service. In the past, when we aligned on the definition of value for a product category, we’d make sure that the marketing team positioned the product line clearly, the sales team was trained and equipped to articulate that value to customers, and the product pricing reflected the said value.
In my past roles, I have actually created cheat sheets for each product or category specifically for the commercial teams that lay out the value proposition: how the product adds value, how the sales team should articulate the value, how pricing supports that value prop, and how marketing reinforces it in all its communication and collateral. This alignment is extremely critical. If everyone’s not on the same page, the business and pricing strategy falls apart.
TO: That kind of cross-functional clarity sounds rare—but vital. Where does that process usually hit friction? Where do opposing viewpoints show up, and how do you deal with them?
NC: In my experience, the biggest challenge tends to be with the product development or product marketing teams. They engineer and develop the product and view it as a breakthrough product, packed with features they believe are highly valuable to the intended customer segment. But then sales might say, “This isn’t actually a game changer,” or pricing may say “The customer isn’t willing to pay what you think they will for these features.”
For the product development team, this can be very hard to digest, we’ve done studies where attributes that the internal product team thought were compelling didn’t resonate with customers at all. And such misalignment can lead to difficult conversations and necessary compromises.
Ideally, both sales and pricing should be involved from day one. The right way is to set a target price upfront: “Here’s what the market is willing to pay for this kind of product.” Then the product development can work backwards and figure out how to build something that delivers that value at a viable cost.
But what usually happens, is that the product team brings something forward and says, “It costs us $45 to make. Price it.” And I have to say, “But the market will only pay $50. So, this is not going to work.” So, the process ends up being reactive instead of being strategic.
TO: When pricing is integrated from the start, it becomes a tool to guide development—not just respond to it.
NC: That’s right. When pricing leads with data and market research, they can help steer the product development direction early, so that the final offer value is aligned with what the customer values—and what they’re willing to pay!
TO: That seems like the sweet spot—when product, marketing, and pricing are all aligned around the same value story.
NC: That’s exactly right. As I indicated earlier, as long as you price below the customer’s perceived value, you will sell and be successful. But if you get that equation wrong—if your product doesn’t offer enough value or your pricing overshoots, the product becomes another failed item lost in a sea of millions. You have to truly understand what your customer needs, why they’ll buy it from you, and what they are willing to pay for it.
TO: So, it’s not just about setting a price, it’s about earning it.
NC: That’s it. Until you understand why someone will buy, you won’t capture the value.
PRICING AND DATA ANALYTICS
TO: What’s getting you excited as you look ahead? We’re seeing new tools, new forms of AI, and a data foundation that’s becoming far more granular and personalized. AI is starting to tie things together in ways we couldn’t before—like connecting product attributes across an assortment to generate deeper insights. So, as this evolves, what do you find most promising?
NC: I’m very excited about the progress in AI. Two things come to mind. First, AI is going to change our world—at least my world of pricing and revenue management. But at the same time, I don’t consider that we should completely rely on AI. I do not want to use AI as a crutch, but rather as an intelligent partner. AI is a tool to help us get things done faster and augment our understanding not necessarily to replace our thinking and judgement.
In the past, I have spent weeks just collecting data, cleaning it, organizing it. Even now, when I look at a client’s data, the data is not usable – it’s often messy, unformatted, and scattered across systems. AI can drastically reduce the cleanup time. What used to take a week could happen now in a few hours or sometimes in even minutes.
TO: That kind of speed would free people up to actually use the data instead of just wrangling it.
NC: Exactly. It will help us be proactive rather than reactive. The area I see AI’s real potential is in market analysis and customer insights. LLMs are well suited to extract that kind of insight, they can analyze market trends and competitor actions, LLMs can parse customer feedback, ratings, and reviews to understand what customers really want.
You can take that customer data—purchase behavior, browsing patterns, demographics, preferences, and layer in historical data and competitive intelligence, and suddenly you have something very powerful. AI can help to extract pricing insights; help identify the key factors that influence price sensitivity.
Example, AI can help product image matching work, something that your Engage3 does: understanding product images, comparing features, identifying value differences and then matching with competitor products. We used to do this manually—listing out our features, comparing them to competitors, and figuring out where we have an edge. That work took us weeks and sometimes months.
TO: And still does, in a lot of places.
NC: Right. I’m working with a company now where they’re still matching products manually across a huge number of competitors. And then monitoring competitor prices, the process is very tedious and time consuming. AI can do wonders here.
As I said earlier, once you are able to bring in customer data, product data, market data—you can generate better demand forecasts. That, to me, is a game changer. If I can forecast demand based on customer behavior, market pricing, and product attributes, and then simulate how price changes will impact demand, I can roll that up into financial impacts. That’s what I call utopia. Push a button, and the AI model optimizes your pricing strategies based on all those inputs.
Right now, even something like A/B testing is incredibly time-consuming. You have to identify the test and control regions, cluster similar customer segments, run the test, then the team spend weeks analyzing what happened, what mattered, and what didn’t.
TO: By the time you get the answer, the moment may have passed.
NC: Exactly. AI can be of immense help here. AI can speed up this analysis and give recommendations in real time — what is working and what is not and what we should do next—that’s incredibly valuable.
A FUTURE WHERE SHOPPERS SELF SEGMENT
TO: The future I get excited about is what you just described. I think we’re moving toward a world where shoppers self-segment through their own behavior. There’s a “give to get” relationship forming—every time a shopper makes a decision, it becomes a form of feedback. With apps and digital tools, it’s getting easier to understand what each shopper values. You can show them a price-per-unit or a ranked list, and if they don’t pick the cheapest one, that tells you something meaningful.
NC: Agreed, in terms of giving customers options – always offer them a product ladder – Good, Better, Best (GBB). You should always have at least three options. I’m very clear about that, and my advice is that you have to have a good, better, best product structure. Some customers treat the best product as the anchor, some the good product—but most land on the better product. Empirical research also confirms that the middle (better) choice gets picked the most. So. you have to be extremely thoughtful about how you structure your product ladder and pricing.
TO: And when you take the time to build out those Good, Better, Best options, you’re not just creating choice—you’re creating data. In today’s world, that data is becoming an asset. Every layer of segmentation gives us feedback directly from the shopper. And if we can feed that back into our models, we can start building systems that respond dynamically in real time.
NC: That’s the real advantage of data analytics and AI. It enables real-time decision-making. In the past, I’ve tried to do this—taking in tons of customer feedback. For online, we built machine learning models that track product impressions. What’s Tim hovering over? What’s he trying to find? That’s one layer. Then you’ve got online cart analytics—are you adding something to your cart but not buying or buying? What’s the real-time competitor’s price? Does my competitor have enough inventory? Because if they don’t, that completely changes the equation.
You can also factor in things like loyalty—is this a new customer or a repeat one? You take all these data points and train your model to determine if we can price in real time, the moment someone clicks on your product? I may have a base price in the system, but whether it goes up or down depends on when, where, who’s clicking, and what’s happening around that decision.
That’s the fun of dynamic pricing—you can unlock deep insights and start playing with seasonality, price elasticity, customer segmentation and demographics … determine pricing that maximizes overall profitability considering costs, demand, inventory …all in real time with help of AI.
WHERE TO START WHEN SEGMENTING
TO: When you think about where to go first with segmentation, what dimensions do you prioritize? Do you start with geography, customer type, or timing?
NC: I’d say all of it—but I usually begin with demographics.
Demographics means trying to cluster or group customers by age, gender, income, education, occupation etc. This gives you a basic understanding of who your customers are.
Then I layer in geography. Segment customers by state, market zone, and climate. Also, try and get data on what kind of neighborhoods they live and shop. I have used this data to tailor ads, messaging and product promotions based on regional preferences. Currently, I am putting together a promotional campaign strategy based on state, weather patterns and temperature.
You can also layer in deeper customer data like lifestyle, interests, attitudes, and personality traits … you can access much of this data online today. This data can help you understand the why behind their purchasing decisions.
Once you have all this customer data, you can then layer in their actual online behavior – purchase history, loyalty, frequency of visits, buy rate, etc. and start creating clusters or customer segments.
The ideal, of course, would be fully personalized pricing, prices tailored to individual customers based on their propensity to buy and willingness to pay. This is technically feasible, but I am not sure if we are there yet.
TO: So, you’re aiming for the most granular practical segmentation, with personalization as the North Star.
NC: Exactly. Customer segmentation is not easy. You should try and get as much data as you can at a granular level based on our earlier discussion and then segment customers accordingly. Yes, as I said – personalized pricing is the goal, but right now, the best you can do is segment as deeply as technology and data allows.
Another issue with segmentation is that in today’s fast-paced world, customer behavior is also changing, so we also need dynamic segmentation that can adapt in real-time. We are not there yet, at least that is what I believe.
I know that we have been talking primarily about B2C and D2C business, but segmentation also has an important role to play in B2B businesses. Today there are so many regional players that manufacturers need to adopt a regional pricing strategy. They may have a different pricing strategy for the North and the South or even by state depending on who the local players are.
I am currently working with a client on developing pricing zones and tiers. Not just East, West, North, South—but actual pricing zones, defined by marketing areas and customer attributes. But you need to be careful here as dealers in a certain sq. mile radius should not have different pricing to account for shopper mobility.
Coming back to our discussion on segmentation, bottom line – knowing your customer is paramount. That’s why companies want your email address or tel. no. or need you to create an account so that they can track your online and browsing behavior. This way I can link your behavior to a customer profile—and that makes the data extremely useful.
TO: So, the key is having a persistent identifier to tie behavior to a specific customer.
NC: Exactly. That’s why customer login accounts and loyalty programs are so essential.
WHAT TO LOOK AT WHEN STARTING A NEW JOB IN PRICING
TO: If you were handed the keys to a brand-new pricing department at a new retailer, what are some of the first things you’d look at to understand the opportunity? Where do you start?
NC: Thanks for the question, I do have a typical approach. I use the first 15 to 20 days to absorb as much as I can – understanding the business model, the brand, its market position, in-depth researching both the company and the market. Understanding the challenges and issues, trying to understand what specific business issues we are trying to solve with pricing. Understand who the key stakeholders are and work on establishing relationships with them.
The next 15 to 20 days, are spent on analyzing product profitability, customer profitability, customer buying behavior, loyalty, tenure, demographics, market trends, competitor pricing and internal costs both COGs and cost to serve. Conduct a deep dive into the existing pricing strategy, try and identify issues, inconsistencies, and opportunities. What has worked well in the past and what did not.
Then in the final 15 to 20 days, I focus on quick wins, for example, price increases for products that haven’t had a price change in the last many years or products that are clearly overpriced vs. the competition. Start to put in place some discipline and controls for discounting, approval process – I call it pricing governance and compliance. Focus on putting some key metrics like tracking ASP, quote to win | loss, discounts vs. sales, benchmark pricing against competitors … primarily to help build the pricing team’s credibility.
Next, I use two typical frameworks to start working on a structure for the pricing strategy.
One is – Product | Service Value vs. Customer Willingness or Expectation-to-Pay. This framework helps the team understand the intersection of value and pay – which products customers expect to pay for possible high value destination products and also identify products that are considered valuable but not something customers are really willing to pay extra for.
The second is the Product role-and-intent framework that we briefly talked about earlier. This framework helps to classify products – e.g., which products are considered destination or are they me-too or are they considered convenience or impulse? Alignment of this product classification across pricing, merchandising, product development, and marketing is critical.
As a pricing leader, if you do not have a strong understanding of the products, and the category strategy, any pricing strategy you put in place is likely to fail. Not because the pricing strategy was not thoughtful, but because the business objectives and its supporting pricing strategy wasn’t clear to begin with.
Remember, the end-goal is to align pricing with the overall business objectives, market conditions, and customer value.
TO: That’s been my observation too. I really appreciate the conversation—especially how much ground we’ve covered on revenue management. It’s an important connection for people to make that this isn’t just pricing. It’s part of a much bigger picture.
If you’re a revenue management or pricing professional, you really need to understand a lot more than just analytics. People tend to assume it’s all numbers—that if you’re good with data and quantitative analysis, that’s enough. But it’s not.
DATA SCIENCE
NC: Absolutely, I believe that business acumen, critical thinking, and communication skills are actually much more important than just analytics.
With that said, let’s also talk about the role that data science plays in revenue management and pricing. Data scientists engaged in advanced analytics are also key to a pricing team’s success. A data science team can dig deeper than a typical pricing team and help push the envelope for the pricing team in terms of data analytics. In the past the data science team has helped me with putting in place granular customer segmentation, customer and product affinity analysis, attribution modeling, and so on.
The only issue I have with some data scientists is that they are often so hyper-focused on advanced analytics and modeling that they sometimes miss the big-picture, many unfortunately lack business intuition and critical thinking. Example, based on extensive optimization modeling – they will come up with an optimal product price range that may not make business sense in the real world. It’s not that the math is wrong, but the answer doesn’t hold up when you actually try to apply it. I always say that you cannot use models to run a business. You have to run it based on your business acumen and intuition informed by data analytics.
TO: That argues for embedding data science within the pricing team—bringing in people who not only understand models but can apply them with business acumen.
NC: Absolutely.
TO: It reminds me of how data science was originally described—someone with domain knowledge, scientific training, and platform expertise. That was a real hybrid skill set. But that definition feels diluted now.
NC: Yeah, I agree. But nowadays, I don’t hear “data science” as much anymore. It’s all advanced analytics and AI. And that’s fine, as I commented earlier, AI has great potential in pricing and revenue management. Using AI for predictive analytics is becoming a real game changer. As I mentioned earlier, if you can build an AI pricing model that can leverage all the various inputs, learn and iterate based on human feedback and actual test results, the model can start making pricing adjustments on its own in real time. That would be amazing.
So, when I think about AI applications in pricing – I am not thinking just price optimization, but rather how can I use AI across the spectrum of revenue management. How can AI help answer key strategic questions – given the business parameters and constraints, how can I improve business profitability? How can I grow revenues without diluting profitability?
Strategic pricing or revenue management is not just about setting product costs; it’s about the entire business strategy – product presentation, promotional strategy, rebates, messaging – there are so many levers that you can influence that are not necessarily setting pricing for an item.
TO: Right. You can even work upstream—talk to your vendors, negotiate terms. There are so many dimensions to the business model.
PRICING IS THE TANGIBLE MANIFESTATION OF THE INTANGIBLE VALUE
NC: Exactly. Pricing is just one of the levers. One thing that every business professional needs to understand is that Pricing is the tangible manifestation of the intangible value you bring to your customers. If your products or services are able to get paid for what they deserve in terms of value, that is “Pricing Power”
TO: I like that. That’s a great North Star.
NC: Yeah.
My advice to the upcoming pricing talent of tomorrow is that if you really want to be successful in pricing, you truly need to be passionate about the Art and Science of Pricing.
I am on a personal mission to educate organizations on the benefits and necessity of analytics-based (Quantitative) management. And my measure of personal success is if I am able to influence key stakeholders to accept pricing as a strategic lever for growth and profitability, and not just a transactional function.
It is tragic that though pricing is a very powerful lever for boosting profitability, pricing and pricing teams often receive insufficient attention and strategic focus within most organizations and in many cases get blamed without reason.
In one of my engagements, the commercial team was blaming the pricing team for non-competitive pricing. When I dug deeper, I found out that the product costs and customer cost to serve assumptions were messed up. And as the business was using cost-plus pricing, they needed to first fix costing for the product pricing to make sense.
Similarly, in many cases, the sub-par category performance has nothing to do with pricing; sometimes the commercial team is not able to articulate the product value correctly, or the channel strategy is misaligned. Basically, the pricing strategy is not aligned with the overall business strategy and customer value.
Typically, in B2B businesses, channel partners or dealers or distributors are very important stakeholders as they help the company increase market reach substantially. So, price parity among these channels is crucial. Your customer could buy from you directly (D2C) or through a dealer or a reseller. If there’s huge price variation among these channels, the customer won’t trust your company So, your pricing logic across channels must be consistent to avoid upsetting the end-customer. An extremely important consideration.
TO: So, there’s a lot of structure to maintain.
NC: Yes, understanding channel dynamics and maintaining relationship with your channel partners is key. The pricing team also needs to understand the pricing strategies of their channel partners and how their corporate pricing strategy impacts their channel partners’ margins and competitiveness. The pricing team is accountable to create specific pricing structures for each channel that ensures profitability for the company and fair margins for partners, while remaining competitive.
Example – in the QSR (quick service restaurant) business, I have seen channel conflicts eroding channel partner trust and profitability. For example, for the corporate QSR entity, profitability comes from franchise revenues. They get a percentage of revenues (typically 5% to 7%) from their franchisees, so their profitability objective is to increase franchise revenues as much as possible.
But for the franchisee, their profitability is dependent on net margins. They do care about top line revenues, but they need a healthy bottom line. So, as the franchisor keeps pushing national or regional promotions, discounts, and customer deals to drive sales and traffic – the franchisees start losing money.
Their incentives are conflicted. I heard a few months ago one of the biggest Pizza Hut franchisees declared bankruptcy because they made a lot of revenue for Pizza Hut but not enough profit for themselves to survive.
So, you have to be very careful with the channel partners group (CPG) and make sure that the corporate incentives align with the CPG sales channel. They must make sense for the company, the brand, and the channel partners group.
TARIFFS
TO: Lets wrap this up with tariffs. When costs change dramatically, companies have to take a sharper look at their vendor relationships, their channel partners, and all the surrounding dynamics. You mentioned earlier—sometimes the costs are simply wrong. And you have to ask: do I have the right good, better, best assortment?
Maybe it’s time to switch one of those out for a different brand to get a better cost and deliver more value.
NC: Okay, let’s talk tariffs. Yes, agreed – tariffs are a real cost and something that you have to account for in your pricing strategy. You mentioned switching to a different brand to get a better cost … yes, good idea, but you cannot just switch suppliers overnight. It’s nearly impossible. As an importer, if you want to switch suppliers from China to Malaysia or Thailand where the tariffs are a fraction of the tariffs on goods from China, it’s not something you can do immediately. In my past assignment, we tried that during Trump 1.0 administration. It took us two plus years to make a successful transition. In the current Trump 2.0 scenario , even if you start today – by the time you are done with the transition, it may take another two to three years and by then the whole political landscape could be very different. Seriously, it is a catch 22 situation.
Going a bit off-track here – I like how gas stations price fuel. They use what’s called replacement pricing strategy. They don’t price gasoline based on what they paid for and in their existing inventory, which is their current cost of goods. But they forecast and project what they’ll pay for future supply of gasoline based on expected oil barrel prices and then set the prices accordingly. So, they are always ahead of the cost curve.
That’s the kind of thinking you need when you’re dealing with fast-moving products that are levied with import duties, taxes or tariffs. If you wait to see what happens, you can get stuck. Many companies adopted the “wait and watch” approach the last time around — they imported products at prices with higher tariffs and then suddenly some of the tariffs were exempt. The market tends to adjust instantaneously, but then you’re sitting on high-cost goods. Customers don’t care. They will argue, “Why are you still charging me higher prices or tariff surcharges when there the goods are tariff exempt now?”
TO: That’s a really good point, and it brings us full circle. People have to act quickly. They have to start pushing those changes through immediately.
NC: Exactly. If you don’t get ahead of the curve, you could end up with a warehouse full of overpriced inventory. And the customer argues, “Tariffs are gone—why should I pay you extra?” At that point, you’re stuck.
TO: I can see how that’s a trap many businesses fall into.
NC: Right.
Businesses need to accurately assess the financial impact of tariffs on their operations and also understand how these tariffs might affect competitors’ cost structures. Last time around, a number of businesses in my sector hesitated to initiate price increases, awaiting other competitors to lead. Eventually no one took any pricing action, and this collective inaction resulted in widespread margin erosion across the entire sector.
With that said, in the current climate of economic uncertainty, a “wait-and-see” strategy regarding tariff-driven cost increases is a direct path to margin erosion. Businesses must take decisive pricing action to safeguard their profitability in the face of the evolving tariff landscape.
You have to stay ahead of the curve. You have to learn to operate in real time. If tariffs go down tomorrow, you should have already recovered your margin. Otherwise, you’ll always be in a reactive mode.
My advice — inaction and doing nothing is not an option. Learn to be a leader—not a lagger.
Pricing leadership requires courage and a proactive stance.
Again, that’s my personal view. I recently published an article on tariffs on LinkedIn that dives deeper into navigating the tariff landscape.
TO: I can’t wait to read it.
Niel, this has been a very insightful conversation. I really appreciate it—it makes me excited about the future.
