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Top 5 Retail Pricing Challenges And How To Solve Them To Drive Purchases

Retail shifts that were already underway have accelerated, with no signs of slowing down. Consumers expect more from their retailers and can shop around until they find it. To stay ahead of the competition, retailers need to reassess pricing strategies to encourage purchasing now and into the future.

Top 5 Retail Pricing Challenges And How To Solve Them To Drive Purchases

Changes forced onto retailers by the pandemic will linger, and more changes will follow. Consumer demand for better value, bigger selections and increased convenience will only continue to grow, and advancements in technology will support them.

You can’t predict the future of retail, but you can prepare for it. In this article, learn how you can get in front of market shifts and stay competitive, as well as:

  • What happens when you reframe buying challenges as opportunities
  • Why value, convenience and shopper mindset matter just as much as price
  • How siloed marketing and pricing strategies are limiting your growth
  • Why technology is key to preparing for an uncertain future

Retail sales in 2021 experienced phenomenal growth. According to the NRF Annual Forecast, retail sales in the U.S. are expected to top $4.44 trillion in 2021, up at least 10.5% from 2020. This upward trend will likely continue through 2022.

With this fast-changing environment, retailers must rethink many of their business processes to keep up. One of the most immediate and strategic aspects to reexamine is pricing. Why? Because retail pricing as we knew it is broken, and these are the five main drivers:

  1. Consumer demand is changing faster than retailers are responding
  2. Competition is increasing and fragmenting across channels
  3. Broad or mass promotions are less effective
  4. Everyday pricing requires great granularity, requiring more effort than most retailers can manage
  5. Omni-channel retail is presenting new challenges, with cross-shopping and pricing causing chaos

Content Summary

Challenges of old pricing strategies in the new retail environment
Developing winning retail pricing strategies
Using data to develop product life cycle pricing strategies
Rethink your pricing strategies

Challenges of old pricing strategies in the new retail environment

Pricing has always been critical, but with shopper price sensitivity heightened during the pandemic, it became even more so, with no signs of changing even as we emerge from the pandemic. As a result, manual or gut-based pricing and promotion practices are no longer sustainable.

Consumer behavior is changing rapidly. So fast that most retailers are not able to identify and react quickly enough to keep pace. If, for example, a traffic-driving category changes roles (due to many factors), related rules, goals, and expectations must also change. If you continue to treat the category as a traffic driver category when it is not any longer in the eyes of the consumer, you will be at odds with the needs of your customers, and they will go elsewhere.

Retailers struggle with reduced basket sizes when consumers “cherry-pick” products while shopping through online marketplaces. While online basket sizes tend to be up to three times bigger when consumers buy direct from retailers, that changes when consumers shop through retail marketplaces like Instacart. These shoppers can “cherry-pick” their selections, buying from multiple stores but reducing the basket size of their purchases at individual stores. This tactic can be appealing for the price-sensitive shopper. Compounding the issue is that consumer loyalty is fleeting, and, especially amid high inflation, customers are looking for ways to stretch their incomes.

Traditional promotions are not as effective in the new shopping environment. Not so long ago, promotions could almost be on autopilot, but that has changed. Today, over 30% of shoppers don’t make it in-store, so end caps, shelf signage, and other in-store promotions go unseen. As shoppers change their buying behavior with more options to shop across channels, promotions must be more valuable, relevant, and personal to earn the share of the wallet. Retailers must be smarter than ever about choosing what promotions they will invest in and deploy. If nearly 60% of promotions don’t break even, they must figure out how to execute promotion decisions that either maximize revenue and profitability or accelerate the elimination of inventory and encourage customer spend.

Transparency in online pricing means retailers must offer more than just “good prices” to be competitive. Because consumers can easily compare prices online, retailers are challenged to create a positive price perception with consumers. Ultimately, it’s not just about price. It’s about value. How much does the product cost, but also does the retailer offer free shipping, free pickup, or free delivery, or delivery within two hours? Keep in mind that the price does not always have to be the lowest if the retailer offers other benefits consumers value, such as speed or convenience. And, with rising inflation, the wrong thing to do is to pass 100% of retail cost changes to the customer. Items with high elasticity should be scrutinized for any changes, and items with low to very low elasticity can help make up the margin mix. This approach offers an excellent opportunity to grow market share.

Siloed marketing and pricing strategies limit overall growth. Traditionally, retail marketing and pricing strategies are developed by separate departments. However, customers don’t think in category siloes – if tortilla chips are BOGO, salsa and guacamole should be nearby and priced accordingly. A siloed approach can create missed opportunities, making it harder for retailers to encourage consumers to build bigger baskets. Category managers focus on their specific area but might not consider the effect of pricing or promotions on other categories in the store. They also need to consider if products are being cannibalized or impacted from an affinity perspective. For example, if a home improvement retailer offers a deep discount on one brand of paint and paint primers, those sales numbers can be outstanding. Still, the more margin-rich competitor brand may suffer, leaving the retailer’s overall profits in decline.

Some category managers rarely consider how pricing in their area affects another, as managers are often incentivized based on their category’s performance versus the store’s overall performance. However, that effect on another category can adversely impact the business as a whole. Managers must think not just about their own categories but the entire catalog.

Disparate pricing tools make life cycle pricing strategy difficult. The silos that create challenges for retailers aren’t just organizational. They’re also related to the technology used. Retailers may use different solutions within a platform that take a siloed approach to different phases of the pricing lifecycle of a product. For example, retailers may use disparate tools in planning everyday prices versus promotions or markdowns. So merchandising may not know what marketing is doing, and vice versa. Ideally, retailers should look for a solution that allows teams to look at each category and plan all the lifecycle phases in a single place in a unified way.

Developing winning retail pricing strategies

To win in the post-Covid marketplace, retailers need to understand how their shopper’s behavior has changed. Retailers must have channel awareness, be shopper-centric, and understand localized demand patterns.

Retailers also need to look at pricing, consumer, and causal data more frequently than in the past. It used to be enough to look at pricing every week. Now, it’s imperative to look at that data daily and on-demand, enabling adjustments to be made quickly. Competitive advantage can’t be gained when you are in reactive mode. For example, a European retailer had nearly three dozen team members involved in creating manual price recommendations across various formats, from convenience outlets to hypermarkets. Manual constraints meant they could only update prices on 25% of their assortment each week, so responding to competitive price changes could take nearly three weeks from analysis to recommending and deploying new prices.

Pricing for the same item can vary by channel. Although retailers may have an ideal price for an in-store customer, it can be different online. And, since shoppers will compare offers from other competitors and marketplaces like Gopuff, retailers need to consider the total value of their offering. For example, shoppers online are more convenience-focused, so it’s not always necessary to have a one-size-fits-all approach to pricing, especially if other benefits, such as same-day delivery, are offered.

An effective and winning pricing strategy should consider not just the individual product but also affinity products. If a category manager runs an allergy season promotion on antihistamine, it is critical to consider how sales of facial tissue are impacted. Those are easy examples. There are thousands of correlated items that are very difficult to perceive and must be understood to meet customer expectations. In November, breadcrumbs, chicken broth, and cranberry sauce may be housed in separate departments, but they all come together for a Thanksgiving meal. By looking at the big picture, a promotion on one product might allow for a markup on an affinity product, for a net margin and profit gain.

Using data to develop product life cycle pricing strategies

Every product has a lifecycle, so when retailers consider pricing, it should correlate with the relevant phase. To do that, retailers need to use the wealth of data available to drive strategies. Tools like AI, machine learning, and autonomous technology can turn that data into valuable pricing insights and drive execution.

Everyday pricing

Competitive pricing is essential, particularly on the Key Value Items (KVIs) that are most critical to your price perception but is not the only aspect to consider. It’s crucial to understand the KVIs and have real-time insights into when KVIs change, and the product strategy is impacted. A product that historically was a profit driver may become a KVI and evolve into an image driver or a traffic driver. Optimization means knowing when to drive for revenue, when to drive for profit margin, drive for basket builders, and more. It also means knowing when to match or get close to competitive prices. AI-powered data science that combines competitive insights with an understanding of the product’s current role can generate optimal prices down to the store/item/channel level. Given the importance, this must be available on-demand.

Granularity is also essential in everyday pricing. Retailers may be pricing at a chain or banner level, but are they doing that at a store level? That is the optimal way to do it, but it becomes challenging when a retailer has hundreds or thousands of stores, especially if they don’t have the right technology they trust. That trust relies on retailers feeling confident in the data and science behind the technology without double-checking results. That comes back to having transparency into what the tool is doing and seeing meaningful results from that tool.

Price-sensitive products

It is critical to leverage data science that can accurately detect demand signals, including item-level and channelaware price sensitivity, especially when that can change quickly. Retailers historically tended to rely on one-off analytical services to determine sensitivities and KVIs, once every year or every other year. But the reality changes much more quickly than once a year as consumers increase their on-demand expectations. As a result, retailers must leverage systems that keep up continuously. Retailers must understand if items are still truly highly price-sensitive or if the status has changed. It is even more useful to be proactively notified if a significant change in sensitivity occurs on any given item so that the price strategy can be reevaluated.


Instead of taking a siloed approach to “winning” a promotion at the detriment of other store brands, category managers should look at the overall net gain or loss. Instead of thinking: “I’m going to run this promotion,” a more strategic approach would be: “I’m going to optimize this promotion with an offer and a price point that benefits my organization overall.” Without this thinking, the net result may be worse than if no promotion were offered.

In addition to understanding the cross-category impact, retailers should assess how effective previous promotions were, instead of automatically repeating them, as many retailers currently do. On average, only 40% of promotions are effective at driving revenue, profit, or basket size. With that in mind, running promotions that didn’t provide the intended business results or even resulted in losses creates needless margin bleed. It may even be possible to eliminate the promotion entirely and still get the same or better results. How do you know which to run and which to cut? Listening to the data is a critical step in hitting the sweet spot for creating effective promotional strategies.

The new markdown landscape

Markdowns are the optimal clearance of inventory on a localized basis. Markdowns are becoming increasingly more complex, no matter the retail vertical. Seasonal merchandise, closeouts, perishable items – the list goes on. Is the goal to maximize revenue or profit? Or merely free up working capital tied up in inventory more quickly to invest in other areas? Markdown plans must take an automated and data science-driven approach to be optimal and agile to keep up with the ever-evolving retail environment. For a North American home improvement retailer, moving to autonomous markdowns provided a weekly forecast with over 95% accuracy and reduced analyst effort by more than 50%, saving over 3,000 work hours each year.

Data science, Artificial Intelligence, and autonomous technology are essential for determining relevant pricing strategies – and the prices that bring them to life at the shelf

Developing the optimal retail pricing strategies and promotions to support them requires tools powered by the use of advanced data science, and that continues to evolve. Unfortunately, people often shop for the systems of the past rather than the right systems for the future.

But legacy systems can’t give retailers and category managers the data and insights they need to succeed in the current retail environment, much less the future. It would be impossible to look at prices for every product, in every category, across dozens or hundreds of stores every day without scalable, autonomous technology using AI-powered data science.

Retailers may use some level of data science for rules-based pricing. But appropriate advanced science can be used more powerfully to forecast and optimize pricing that considers all retailer constraints and rules, as well as shopper demand signals, competitor prices, and price elasticities. For example, data science should proactively recommend prices for that new role if a product role changes from a traffic driver to a profit driver.

Future-proofed technology should deliver a unified platform that eliminates departmental silos and is flexible and highly scalable to allow for autonomous pricing. A high degree of granularity is essential for retailers to better compete and drive positive price perception, so retailers must drill down to store-level data and accurately measure ROI. Effectively and efficiently moving to more granular pricing requires more automation and trusting the right tool to support autonomous pricing and promotions. The business impact of making that move can be significant. For Italian grocery giant Conad Nord Ovest, moving to autonomous pricing delivered a positive return on investment within 18 months and improved their competitive position by three points while increasing gross margin by about 1.5%.

While the pricing and promotions system of the future leans on automation, it doesn’t take the merchant or marketer out of the picture. In fact, it’s the opposite. Increased automation frees category managers and merchants to spend their time on strategic, high-value activities that matter most, while time-consuming, mundane tasks are taken off their plate.

Rethink your pricing strategies

Retail pricing as we know it is broken, and new approaches are required to succeed. So, how do you know when a retail pricing strategy is ineffective? Key signs are when the business is operating in silos, and an item or a category strategy isn’t working well for a department or the company overall, resulting in flat or declining financials. Retailers sometimes make the mistake of trying to compete on price, which can become a race to the bottom. Savvy retailers realize the need to reexamine their pricing strategies by understanding their true differentiators and thoughtfully building the business up with AI-based pricing and promotions instead of continuing to chase this downward spiral.

In the past, retailers made some progress with less sophisticated tools, but today is different. Retailers are in a much different tech ecosystem with shoppers’ rapidly changing expectations. With innovation enabling faster movement, retailers need advanced capabilities that leverage both human and artificial intelligence to make better decisions and gain competitive advantage.

Amid inflation and economic uncertainty, a unified approach to pricing, promotions, and markdowns is essential for retailers to gain new customers and grow customer loyalty. By looking at pricing across the product lifecycle and using autonomous technologies that quickly adapt to changing market, shopper, and competitive conditions, retailers can provide a win/win with prices that attract shoppers and accelerate profitable growth for their business.

Alex Lim is a certified book reviewer and editor with over 10 years of experience in the publishing industry. He has reviewed hundreds of books for reputable magazines and websites, such as The New York Times, The Guardian, and Goodreads. Alex has a master’s degree in comparative literature from Harvard University and a PhD in literary criticism from Oxford University. He is also the author of several acclaimed books on literary theory and analysis, such as The Art of Reading and How to Write a Book Review. Alex lives in London, England with his wife and two children. You can contact him at [email protected] or follow him on Website | Twitter | Facebook

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