If you forge a strong partnership with the retailer, your brand pricing strategy will be more optimized and deliver higher profitability!
I remember back to my University classes when our business professors taught us about the classic 4P’s of Marketing: Product, Place, Promotion, and Price. After many years of experience in the consumer products industry both in Canada and Internationally, three things became obvious: the “Pricing Strategy in Marketing” was under-taught, it is by far the most important of the 4 P’s, and is the most difficult to manage.
Why is Pricing so Important?
From a CFO’s point of view, increasing pricing (that the manufacturer of consumer products can achieve from its customers) is the single biggest leverage point to improving profitability. For example, a company that is delivering a 10% EBITDA, and is able to achieve a +1.0% gain in its net pricing from their customers. Assuming it is passed through to the bottom line, the higher pricing will yield an 11% EBITDA. This change to EBITDA represents a 10% profit improvement! The profit impact from this is far greater than would a 1.0% cost savings in COGS (cost of goods sold), a 1.0% savings in fixed manufacturing overheads, or a 1.0% cost reduction of SG&A. Further, the achievement of a +1.0% pricing improvement will have significant positive impacts to the company’s cash flow and balance sheet statements.
For the sales and marketing executives, achieving higher pricing and thus higher sales revenue, (that is also the “right” pricing in the market) can provide greater functional resources. This is because most trade investment and advertising/promotion budgets are set as a “% to sales” metric.
Given the price paid by consumers at the cash register is the starting point of how much cash is generated, which funds both the manufacturers and retailers margin’s, pricing is extremely important to a CEO’s performance and how the business organization is managed.
The reverse of this is also just as important. The erosion of a brand’s pricing level will have a severe negative impact on profitability, putting spending budgets at risk for cuts, and bringing the retailer and manufacturer into conflict as they both attempt to protect their respective margins with less cash on the table.
Why is Pricing so Difficult to Manage?
There are 3 drivers that make pricing so complex and challenging:
1. The Value Chain
Setting and achieving a pricing strategy for a brand by the manufacturer is not simple. This is because pricing has to be managed through an intermediary called a “retailer”, who distributes the product to the end consumer. Diagram #1 (see below) shows that there are 5 distinct inputs to determining price. Going from bottom to top through this chain, the manufacturer has its own COGS, margin expectations and a desired pricing level for its brand at retail. The retailer also has its own margin expectations, as well as the price it wants to sell the product for in its stores. These 5 inputs points are influenced and/or decided by the manufacturer or retailer. Further, within each of these organizations, there are multiple stakeholders that have self-interests, and wish to exert their expectations into the pricing decisions. With this matrix, one can see the potential for complexity, and conflict throughout the value chain, as there are “too many cooks in the kitchen”.
2. Retailer Perspective and Power
Today, the retailer has the upper hand with pricing. Retailers can, and do, set retail shelf prices based on their own best interests. Retail pricing strategy penetration for a brand or category may have nothing to do with what consumer research suggests, what makes the highest category profitability, or common sense. The retailer may set prices in reaction to competition, make an emotional “statement in the marketplace”, or to change the price perception of their banner name in the market. In addition, retailers may want to increase store foot traffic, drive higher shopper basket sizes, or encourage shoppers to purchase more of their own private label brands. These larger retailer interests make the interest of the brand sometimes tertiary and can lead to brand pricing that is contrary to the manufacturer’s desired strategy.
3. Millions of Consumer Purchase Decisions Weekly
Within the Canadian market of +13 million households, and with most packaged goods products having purchase cycles of 4 weeks or less, millions of consumer purchase decisions are occurring every week throughout the year. Further, with over 20,000 retail stores in the country, each offering different prices that change, the challenge of knowing what the price points are, in each store, and what the consumer does, is virtually impossible.
In summary, the combination of these 3 drivers make the pricing component of the marketing mix very difficult to manage. Yet if mastered, a more optimal pricing strategy will deliver improved profitability, for both the manufacturer and retailer!
Understanding Pricing is like Understanding the Weather!
Given these complexities, challenges and innumerable data points of pricing, retail auditing Research firms have tried to simplify the reporting of pricing and the resulting impact on consumer purchases. Their pricing metrics measure 3 facts: ARP (average regular price, the average non-promoted regular shelf price), ATPR (average temporary price reduction, the average discounted price), and RASP (retail average selling price, the average selling price of all pricing combined). Metrics that measure consumer purchases at retail include unit and dollar volume sales, and market shares.
Reporting pricing data points as “averages”, simplifies but does it tell you what you need to know? Take the weather as an example. If you hear a weather report and it says the average temperature in Canada is 15 degrees Celsius, and that the country is mostly dry; this really does not tell you much. Although the Canadian average is 15C, the temperature in Vancouver is 28C, Edmonton 5C, Toronto 14C, Montreal -5C, and Halifax 21C with heavy rain. To consumers living in these cities, the average means nothing. In Vancouver, people are wearing shorts and short sleeve shirts. The people in Edmonton are wearing long clothing and a jacket, while the folks in Montreal received snow, and are in full winter attire! In Halifax, they’re wearing raincoats, and holding umbrellas. In Toronto, younger consumers may wear a light jacket, while older consumers may be wearing a warm heavy coat! The next day the weather report announces the same “average” temperature in Canada of 15C, but Vancouver has declined to 13C, Edmonton has warmed up, Montreal receives a thaw, and both Toronto and Halifax have dropped to 11C. Yet, the average of 15C in Canada remained the same. On this second day of weather, consumers in all these cities likely changed their clothing attire according to what they were actually exposed to, i.e., the good people of Halifax have put their umbrellas away!
The point is that “average temperatures”, whether it is for a country, a region, a province, or even a city, really don’t drive behaviors; just as average prices don’t either. The driver of purchase behavior, like the weather, is what the consumer experiences in their environment, at a moment in time. One day, shorts, a t-shirt, and sunscreen, the next day, long pants, a jacket, and maybe an umbrella. Pricing is very much the same. The consumer sees what the pricing is within their retail environments, and depending on who they are, act differently with their purchase decisions. So, to better understand pricing and how to optimize it, you have to understand “who” is purchasing the brand and why, where and when they purchase, and what prices they see. So understanding the 5W’s is vital to getting your pricing strategy optimized!
Retailers have the 5 W’s Data, but Manufacturers need to have the Answers
For many years, retailers, through their very sophisticated POS (point of sale) store sales data, have been able to track and measure 3 of the 5 W’s (the where, when, and what is purchased at store level). This data is vital to their supply chain replenishment systems, to manage in-stock positions, inventory, and order processing from their vendor networks. This information has been shared with retail audit research firms as well as consumer products manufacturers, to work collaboratively, and help build each other’s businesses.
The last 2 W’s (who and why) have only recently become known to the retailer via shopper loyalty programs. Large retailers have implemented loyalty programs where shoppers who sign up are given rewards for their shopping loyalty and spending levels within the retailer’s stores. While this is designed for the retailer to understand their customers better, increase loyalty, and drive additional in-store purchases, the data also offers another benefit. The data can identify the “who” and the “why” by examining historical purchasing data. The combination of data from the retailer’s shopper loyalty programs plus their POS data gives the retailer all 5 W’s for brands and categories. If understood and acted upon jointly by the manufacturer and retailer, knowledge from this information can lead to more optimized pricing strategies and enhanced profitability for both.
The Definition of Optimized Pricing Strategy Types
What does “optimized pricing strategy” mean? Some would define this as the price point that maximizes unit volume sales, while others believe that the highest possible sales revenue is the best metric. Given that businesses are in the business of maximizing shareholder value and delivering this consistently over time, optimal pricing strategy should be defined as “the sustainable price point that delivers the highest level of profitability for both the retailer and manufacturer, as measured by free cash flow.” The inclusion of sustainability is to ensure that the pricing strategy is at a level that the retailer will support (i.e., the retailer also earns its desired level of profit, and does so on a category basis), and that competitors will not attempt to significantly disrupt or destroy. Because market dynamics are always changing, arriving at the perfect pricing strategy and sustaining it is unlikely. The goal is to achieve a more optimal pricing strategy that will improve profitability. This quest is never ending and requires a mindset of continuous improvement and due diligence.
Note: For illustrative purposes, this article provides an example of how to go about and do this. The example is to communicate the logical thinking of the process. The article recognizes that in reality, there is more complexity due to things like competitive price reaction, brands that have multiple sizes/skus, the degree of pantry loading, size/variant switching and cannibalization. These need to be accounted for in a full analysis. This data is available, and therefore because the what, where, when, why and who, can be ascertained, the manufacturer can determine their brand’s optimal pricing strategy! In addition, the example going forward reflects what is required from a brand perspective. The necessity to conduct a similar evaluation from a category perspective, as the retailer “holds the cards” is needed to gain retailer support.
Optimizing Pricing Strategy – Step 1
The Retailer and Manufacturer must form a Partnership of Trust and agree to Pursue Pricing Optimization.
The manufacturer and retailer must come together and agree to taking on this project. They are mutually interdependent as the retailer holds all the data (the 5W’s), and the manufacturer understands the category better; retailers who sell 150,000 plus sku’s through a single store, representing 1,000 plus categories, are not structured or resourced to understand every category well. There must be a culture of trust in the relationship, with both partners seeing the opportunity as a win-win. There should be a written project brief, with both sides understanding, agreeing, and committing the resources needed to undertake the task. Further, getting the retailer on board is essential, as it is the retailer who controls the retail shelf price; getting them to agree up front, makes it easier to implement any price changes later. From the manufacturer perspective, using the retailer’s own data, (rather than information from a 3rd party sourced consumer diary panel) gives the outcome far more relevance to the retailer. The data and its analysis are directly about the retailers own customers, and thus generate far greater cooperation, belief, and a willingness to act.
Optimizing Pricing Strategy – Step 2
Figure-out the Who and the Why.
| Consumer User Group | Definition | Why |
| Regular/Loyal Purchasers | These consumers purchase a particular brand 7-10 times out of 10 purchase cycles. | These consumers perceive their brand of choice to be superior vs. competitive brands when all aspects of the brand bundle of benefits are considered (i.e., formulation, packaging, product claims, pricing, equity value, etc.) |
| Semi-Regular/Switcher Purchasers | These consumers purchase a particular brand 4-6 times out of 10 purchase cycles. | These consumers perceive the brand equal to other brands, and base their purchase decision usually on availability or price. With price being driven by feature price discounts, couponing, or other tactical promotional offerings. |
| Occasional/Infrequent Purchasers | These consumers purchase a brand 1-3 times out of 10 purchase cycles. | These consumers perceive the brand to be inferior to others, but acceptable to meet their basic needs. They purchase the brand when there is a great price discount, or promotional offering that is too good to turn down. |
Optimizing Pricing Strategy – Step 3
Identify the Remaining 5 W’s (What, When, Where.)
Now go back into the data, and record over the course of the last 12 months, what these shoppers (by user group) actually purchased. Include how many units were bought, and what the price points were. Graph #1 below outlines how this may look. In this illustrative example, the regular users in total purchased 3,600 units over the year. Assuming an average purchase cycle of 2 months, 600 loyal regular users bought 6 units for the year (600 x 6 = 3,600 units). During the year, the brand was priced at its regular shelf price of $3.29, while 3 times during the year the brand was priced discounted by the Retailer at $2.99, $2.49 and $1.99. At these price points, regular users would see these price points and continue to buy. The data revealed (see graph below), 1,500 units were purchased at the regular price, while 600 units each were bought at $2.99 and $2.29, and 900 units were purchased at $1.99.
Semi-regular users come into the brand when price discounts are offered at all 3 levels, with higher unit sales occurring when the price discount is deeper. At $1.99, the semi-regular users bought 150 units.
The occasional users needed a deeper discount to buy, and in this example, bought the brand at the price points of $2.49 and $1.99.
In summary, the shopper loyalty program and POS data shows that from a sample size of 1000 shoppers, 4,050 units of the brand were purchased over 12 months. The information tells us who bought the brand and why, where it was bought, when it was bought, and most importantly, at what price! You now have the 5 W’s and can move onto the next step.
Optimizing Pricing Strategy-Step 4
Build The Financial Model.
Using financial data from the value chain (as outlined above), build a pro forma brand P&L at the various price points and volumes (see Chart #1 below). In this example, at the $3.29 price point, 1,500 units were sold (from Graph #1). Assuming a retailer margin of 35%, and COGS at $1.18, the manufacturer’s margin is 44.9%. When other expenses (i.e., marketing budgets, R&D, fixed manufacturing overheads, and SG&A) are allocated, at an assumed 30.0% level, EBITDA delivered is $0.32 or 15% per unit sold.
When these financial dynamics are multiplied by the total volume sold, the retailer achieves $4,935.00 in sales and $1,727.25 in margin. The manufacturer earns strong sales and margin, but more importantly delivers $480.00 of EBITDA. Moving across the columns as pricing declines, the P&L pro forma shows eroding profitability for both the retailer and the manufacturer. At a feature price of $1.99, for example, the manufacturer achieves an EBITDA loss of -$0.14 per unit and an aggregate loss of ($161.00). For the retailer, profit erosion is driven by declining pricing and lower margin percentages. In most cases, retailers do invest some of their margin when products are featured.
Pro Forma P&L of Various Price Points
| Retail Price | $3.29 | $2.99 | $2.49 | $1.99 |
| Total Units Sold | 1,500 | 650 | 750 | 1,150 |
| Retailer Margin $ | 1.15 | 0.90 | 0.75 | 0.50 |
| % | 35.0 | 30.0 | 30.0 | 25.0 |
| MFT. Selling Price | $2.14 | $2.09 | $1.74 | $1.49 |
| MFT. COGS | $1.18 | $1.18 | $1.18 | $1.18 |
| MFT. Margin $ | 0.96 | 0.91 | 0.56 | 0.31 |
| % | 44.9 | 43.5 | 32.2 | 20.8 |
| All other Exp. $ | 0.64 | 0.62 | 0.52 | 0.45 |
| % | 30.0 | 30.0 | 30.0 | 30.0 |
| EBITDA $’s | 0.32 | 0.29 | 0.04 | (0.14) |
| % | 15.0 | 13.8 | 2.3 | (9.4) |
Financial Model of Total Sales & Profits
| Retailer Sales $ | 4,935.00 | 1,943.50 | 1,867.50 | 2,288.50 |
| Retailer Margin $ | 1,727.25 | 585.00 | 562.50 | 575.00 |
| % | 35.0 | 30.0 | 30.0 | 25.0 |
| MFT. Sales $ | 3,210.00 | 1,358.50 | 1,305.00 | 1,713.50 |
| MFT. Margin $ | 1,440.00 | 591.50 | 420.00 | 356.50 |
| % | 44.9 | 43.5 | 32.2 | 20.8 |
| MFT. EBITDA $ | 480.00 | 188.50 | 30.00 | (161.00) |
| % | 15.0 | 13.9 | 2.3 | (9.4) |
Looking at this data, it would suggest that the optimal pricing strategy would be to only run price discounts to the $2.99 level. Going lower to $2.49 does not deliver that much more volume, yet the profitability approached near zero with EBITDA at 2.3%. The $1.99 discounted price delivers almost as much unit volume sales (1,150 units, vs. 1,500 units at $3.29) but yields an EBITDA loss of ($161.00) for the manufacturer. So with this example, it is best to keep the regular price at $3.29, hold the discounted price at $2.99, and run this price point 3 times a year. The EBITDA of $188.50 at $2.99 times 3 (or +$565.50), will deliver substantially more profit than the lower pricing alternatives seen in this example. There may be a slight loss in unit volume sales form the semi-regular and occasional user groups, but the profit gain from regular users who are still going to buy their volumes at the higher discounted price of $2.99, generates far greater profitability. Understanding the “who” and “why” of consumer purchases, in this example, was vital to determining a more optimal pricing strategy, and delivering higher profitability.
Optimizing Pricing Strategy – Step 5
Now Take on The Retailer’s Category View.
Understanding the optimal pricing strategy for the brand is beneficial for the manufacturer, but understanding the category perspective is essential. Because the data resides with the retailer, and the manufacturer needs the retailer’s support to action any pricing changes, the retailer needs to be convinced that any pricing actions are best for their shoppers and the category as a whole.
To undertake this, the same thinking of Step 1 through Step 4 applies. For Step 2, for example, retailers have different shopper groups as well. They have regular shoppers who shop their store regularly, and buy the category during their shop. Retailers also have shoppers that shop the store, but sometimes buy the category, and sometimes do not. Then there are the very infrequent shoppers who occasionally shop the store and the category, who “cherry pick” aggressively promoted items. With the retailer’s shopper loyalty program and POS data, the same 4 Steps outlined above can be done. How the retailers define their shopper groups, and determining their willingness to provide purchase data (in Step 3), and financial data (in Step 4), needs to be worked out ahead of time. This is why Step 1 is so important.
The manufacturer may reject the idea of taking on this more complex analysis of the category, but I would argue that there really is no choice. To figure out what is best for your brand, you need to understand what is best for the category, with the retailer’s view in mind. Establishing this partnership with the retailer, will not only forge a stronger relationship, but also provide some extremely powerful knowledge about your competitors within the category. Further, the ability to gain Retailer support is essential to achieving the desired pricing strategies in store, and delivering higher profitability on a sustainable basis.
In summary, understanding your brand better, working with your customers to understand their needs and how to improve their business results creates the 6th “W”. With this powerful knowledge, and the ability to leverage it with customers, the manufacturer achieves great “Wisdom”. Wisdom will deliver competitive advantage, higher profitability, and a stronger relationship between the manufacturer and their customers.
