Pricing strategy is a systematic model used to set the optimal prices for products. The right choice of a pricing strategy enables retailers to maximize profit and revenue while, at the same time, satisfying market requests and keeping customers loyal. Retailers apply various approaches to pricing depending primarily on their business maturity level. In this entry, we're going to focus on the main types of pricing strategies dominating across the industries:
Cost-plus pricing strategy
Competitive pricing strategy
Value-based pricing strategy
Dynamic pricing strategy
Psychological pricing strategy
Bundle pricing strategy
We’re going to specify the merits and drawbacks of each strategy so you can use the text as a practical guide while selecting a pricing strategy for your business. We’re would also outline the major factors retailers ought to consider while choosing a pricing strategy. Finally, we’re going to present how advanced pricing software helps to find the most balanced approach to pricing so retailers can reach their strategic business goals and keep the customers loyal. Let’s go right down to business!
Cost-plus pricing strategy or where it all starts
A cost-plus pricing strategy implies adding a particular markup to the product cost. What it means is that the products are priced based on only two factors: the cost and the markup. In most cases, the markup is a fixed percentage set by a retailer depending on how much profit the business would like to receive from selling a single item. The basic formula underlying cost-plus pricing goes as follows:
Here's an example of using a cost-plus pricing: imagine you're selling sunglasses and one pair costs 30$. On each sale, you would like to earn 50% of the price. 50% is, therefore, your markup which would be 15$ in the case of 30$ sunglasses. The final price would then be 45$.
A cost-based pricing strategy is a good starting point for those retailers that have just launched the business and barely know anything about the market, customer preferences or the price elasticity of demand. The strategy could sometimes be applied for the brand-new products on the market as there is no relevant historical data to find how the product should be priced. At the same time, a cost-based approach remains remarkably unsustainable and insecure, so it is given up by most retailers right after they become more mature.
Competitive pricing strategy: look around
A ccompetitive pricing strategy implies using competitors’ prices as a benchmark to set prices. That’s why this type of strategy is also often referred to as competition-based or competitor-based pricing. Very often, retailers come to a competitive pricing strategy after a cost-plus approach turns out to be no longer relevant.
The basic principle of competitive pricing entails tracking competitors’ prices and then adjusting own prices based on a retailer’s brand positioning. Eventually, the two basic approaches within the competitive pricing strategy are distinguished:
Premium pricing is used by the retailers willing to differentiate them from other players as ones selling better or unique products.
Penetration pricing is an opposite approach based on offering prices lower than other retailers.
Both premium and penetration pricing might bring significant results and, therefore, are widely applied by retailers eager to reach specific business goals. For example, penetration pricing has proven itself to be a remarkably effective means of entering new industries and gaining market share.
At the same time, a competition-driven pricing strategy also has substantial drawbacks and limitations. For example, retailers risk getting involved in the price wars which means damages to both revenue and profit margins. In addition, a competitive pricing strategy often means disregarding the crucial retail categories, like price elasticity or service level. If you follow a competitor underrating price elasticity, you are both likely to end up with financial losses and churned customers.
To mitigate these risks, retailers use advanced pricing software solutions entailing smart scrapping based on real competitors’ identification and full control over the pricing constraints.
Value-based pricing strategy or how much would you pay?
A value-based strategy implies pricing items based on customers' willingness to pay. The idea is simple: a product is worth just as much as people are ready to pay for it.
The unique products may serve as a good example to illustrate how value-based pricing works. Imagine you're selling football jerseys in your store. Suddenly, one of the players wins a Ballon d'Or award and fans are immediately willing to pay more for his jersey, even though it's quality features are the same for all jerseys in the portfolio. In this regard, applying the value-based strategy means identifying the level of customer's willingness to pay and then pricing the jerseys respectively.
One way to determine a customer’s willingness to pay is to calculate the TEV (True Economic Value). The basic equation for the TEV of a product goes as follows:
For example, a plain football club jersey is valued at $15. Another jersey with the name of a top player on it is viewed by customers $5 more valuable. In this case, $15 would be a cost of the closest alternative while $5 would be a differentiating value. What it means is that TEV is equal to $20. This example is a rather simplistic one, yet it illustrates the basic relationship between customers' willingness to pay and the final price.
In practice, it might be very difficult to take into account every single factor influencing customer willingness to pay and that's the main challenge of value-based pricing strategy. In addition, the value-based approach is effective while applying only towards a specific group of products, yet it remains one of the most effective means of maximizing the profit and revenue.
Dynamic pricing strategy: it’s all about flexibility
Dynamic pricing strategy implies setting diversified prices targeting different groups of shoppers in order to craft an optimal value offering at the junction of market trends, demand fluctuations, customer behavior, purchasing power, and other factors.
The dependency between price and demand is the core element underlying dynamic pricing strategy. With fresh and relevant data on this dependency, the revenue-optimal price could be calculated with the formula below.
P in the formula marks the price while d(p) stands for a demand function. Implementing a dynamic pricing strategy requires a substantial level of business and organizational maturity. It also depends on the pricing software retailer uses as a large number of scenarios and dependencies have to be processed and analyzed smoothly.
The dynamic software engine extends the basic formula outlined above adding a range of other pricing and non-pricing factors to be considered. Among others, these may include procurement expenses, inventory costs, demand cannibalization between particular products, competitor prices, promo activities, and other factors. The more diverse and relevant data points are processed by pricing algorithm, the more accurate results are achieved.
Here is a typical four-stage workflow of a dynamic pricing algorithm:
Historical data on price points and corresponding demand rates is consumed by the software platform
The demand function is built based on the dependencies found by the algorithm.
Sophisticated math processes dozens of pricing and non-pricing factors to craft price recommendations.
The prices are applied and then analyzed by the algorithm to make corrections and craft the next recommendations.
Psychological pricing or emotions do matter
Psychological pricing strategy is based on the idea that various types of prices have a different psychological impact on shoppers. Subsequently, the psychological effect is taken into account while pricing products to maximize revenue and profit.
Recent studies show that up to 95% of purchasing decisions are subconscious. What it means is that if retailers can understand human behavior patterns, they would be able to make their offers more attractive. Let’s use some examples to see how psychological pricing works in practice.
Anchoring is one of the most influential psychological patterns impacting shoppers. In particular, anchoring entails relying too much on the first piece of information (which is the “anchor”) while choosing between several products. Therefore, the higher anchor is, the higher is also customers’ willingness to pay. The visual below shows why a high anchor is important.
There are dozens of tricks to get a high anchor price. Here are some of the most common ones:
Consider price lining. If you want to sell an expensive item, put it next to an even more expensive one.
Avoid the same prices for similar products. The recent Yale research shows that in case two similar items have the same price, shoppers are less likely to purchase anything than if the prices are even slightly different.
Make the prices seem smaller. There are dozens of tricks to make the price seem lower than it is. The “$9.99” rule is the most illustrative example.
Use fewer syllables. The rule here is: the more simple the price appears, the better. For example, $2599 is better than $2,599.00.
Psychological pricing could bring a significant boost to a retailer’s financial results, yet it has a limited scope of practical use. That’s why psychological pricing works best as a supplementing tool in combination with more complex strategies.
Bundle pricing strategy to sell more
Bundle pricing strategy implies selling a set of products for a lower price than each of these products separately. This approach is one of the most effective means to sell the products with a relatively low demand.
The Microsoft Office software pack is one of the best examples of a bundle pricing strategy's use in practice. Most of the users purchasing Microsoft Office package need no more than 3-4 services on average even though they have access to the whole package. Special promo offers in retail may also serve as an example of a bundle pricing strategy. For example, KVI products are paired together with the low-demand products and then sold at a discount price.
The main advantages of bundle pricing strategy stem from the fact that customers like purchasing products in groups, as it usually ads value to their buying experience. In addition, shoppers tend to enjoy versatility in a single act of purchase and avoid frustration while choosing complementary products.
However, customers do not always need all the products in a bundle while paying for all of them. Besides, It is difficult for retailers to remain transparent in their pricing decisions for bundled products and find a balance between their and customers’ total value for the items. Therefore, similarly to a psychological approach, bundle pricing works best in combination with other strategies.
After we’ve outlined the merits and drawbacks of all major pricing strategies, you’re probably asking: “Ok, but how should I choose a single strategy for my business?”. Of course, the choice of particular pricing strategy depends on a plethora of internal and external factors unique for each business. However, there are two fundamental recommendations that we believe are relevant for all types of retailers regardless of industry, size or business maturity.
First of all, the combination of approaches is always better than a single strategy. What it means is that you should find the major prevailing strategy, yet it is worth being supplemented with elements of other strategies. For example, you can rely mainly on the competition-based strategy and, at the same time, use some principles of psychological pricing or bundle pricing. The visual below highlights the major pillars underlying the balanced development of a pricing strategy.
Whatever strategy you choose, it’s successful implementation is hardly possible without relying on advanced pricing software. And that’s our second recommendation. Just one example: if a manager can deal with only 3 or 4 factors while crafting a single price, the advanced pricing software, like Competera, processes 60 factors at once.
Human-centric pricing is hardly a sustainable way to cope with the growing competition in retail. We believe that the future belongs to proactive pricing and comprehensive price optimization. Competera enables businesses to manage prices on portfolio level using advanced ML/AI models. What it means is that retailers can craft optimal value offerings to maximize their revenue and profit under the framework of any strategy they choose.