In a prior blog, I identified the dangers and consequences of the “Amazon Effect”, which has roiled the retail industry for the past decade.
Amazon’s aggressive and active pricing methods can create significant pressure on your competing categories. What should you do if they drop the price on your most popular basketball from $39.95 to $34.99? You need to guard your top and bottom lines, so it is likely a losing battle to blindly match their downward price moves. But doing nothing is a bad option.
An “adaptive pricing” approach – one that prescribes targeted responses to specific competitor actions – allows you to fight back more effectively. By leveraging analytics, you can eliminate key unknowns and level the playing field, answering questions such as:
- How do customers perceive our prices? How do they react to changes?
- Are customers more sensitive to prices on particular categories and SKUs than on others?
- How much do our exact price points impact behavior vs. our price differentials to Amazon?
- Which products should I change price on if Amazon does? By how much?
- What is Amazon likely to do if I change my prices?
- Given potential price moves, what are my predicted unit, sales and margin impacts?
Chapter one in Sun Tzu’s The Art of War calls for detailed assessment and planning. If you’re going to war, you can’t survive without a battle plan. For retailers, this has four major elements.
- Define a strategy and set parameters for creating and managing adaptive pricing.
Your merchants likely assign pricing roles to their product categories and items based on their knowledge of what influences customer perceptions and behaviors. Big-screen televisions may be established as price-sensitive traffic drivers, while gaming system accessories may be positioned as more of a less-sensitive margin enhancer. Analysis of actual purchase history can help determine those roles with greater precision. Based on those product roles, you can then set guidelines on how far, both up and down, you should change your prices when competitors do. Multiple constraints may need to be taken into account, including pricing family structures, price relationships between main and add-on items, and MAP pricing.
- Develop the capabilities to understand and codify customer pricing behavior.
It is essential to have transactional-level metrics in place which is foundational, to enable insights into the relationships between price and purchase behavior. Given that customers search and shop across multiple retailers, collecting competitive data to establish relative price spreads is critical for highly-competitive items. The next step is to create a process to analyze how consumer demand fluctuates as your prices and competitive price differentials change; this needs to be informed by detailed statistical analysis. To make things simpler, customer price sensitivities can be organized by different levels of hierarchy, like department, class or item. The final step is to combine these predictive insights with your strategy and objectives to yield prescriptive pricing recommendations.
- Deliver recommendations in a way that enables your team to make confident, precise decisions.
Without broad acceptance from your merchant and pricing teams, the new price recommendations that you generate won’t mean much. Achieving buy-in starts by getting those teams involved early in the design process, so they take ownership of the design from the onset. Then, it’s imperative to develop a solution that is intuitive, fits your business processes, and delivers recommendations that include supporting details for added transparency and buy-in. Your teams might also value the capability to model out “what-if” pricing scenarios to understand tradeoffs and to be confident that their decisions align with their strategy and financial objectives, truly blending art and science. Your teams likely have standing business reviews, and we recommend to integrate fresh pricing analyses and processes into that cadence. For categories that change prices even more often, you may need to augment the schedule with more frequent reviews.
- Build a continuous learning loop.
Finally, it’s key to refresh product roles and sensitivity factors periodically to capture current trends, adjusting the rules and tools as needed. Defining and monitoring success metrics will help bolster the organization’s confidence in the program, so be sure to assign a key resource to own this process. In your battle against Amazon, the only option is to fight, and developing adaptive pricing capabilities is a key step. Based on our experiences, retailers will encounter multiple obstacles in their journey. None of this is easy, but it is within reach.
In my final blog on the Amazon Effect, I’ll share the story of a retailer who fought and won.