Pricing remains one of the most important strategic value levers a retailer can pull. And when backed with robust data-analytics, pricing is a powerful tool for driving higher profits, influencing the customer buying journey, pulling ahead of competitors, and supporting larger enterprise goals. But to truly maximize impact, retailers need to hone pricing at every stage with lifecycle price optimization.
Let’s take a look at each stage of the product lifecycle and our experts’ top strategies for how to approach optimized pricing at each stage.
Introductory pricing is often the most difficult part of lifecycle price optimization due to the fact that you have little to no sales data for the new product. Determining consumer demand and the impact on existing products without data is just a guessing game. Because of this, a common practice around introductory pricing is to simply set a price and leave it untouched for one to three months. The thought process here might be, “we don’t have the data, so why bother?” However, we would argue there is still opportunity in those first 30-90 days to capitalize on margins and price perception. The more you change prices, the more data you collect, and therefore the faster you can optimize. To make those pricing decisions, there are a few strategies you can leverage with insights from your transaction data. For example, use data from lookalike products as your starting point. You can also establish rules-based pricing parameters based on any number of factors, including competitors’ prices, margin targets, similar brands, etc. Or, introduce the product at a promotional price before bringing it back up to regular retail, then see how responsive it is to price changes.
To optimize pricing in the growth stage, your strategy needs to align with your goals. A focus on increasing market share would mean keeping prices on the product competitive to draw more sales. Whereas a margin-driver item may have you setting prices higher to balance out competitive prices elsewhere. Or this product could be filling a gap in your assortment, in which case you will need to find the optimal pricing gap in your architecture. Whatever the case, use your growth strategy to establish your pricing strategy. Then, as the product heads towards the maturity phase, competition gets fiercer. At that point, a comprehensive competitive pricing strategy informed by deep competitive pricing insights will drive additional value.
Market saturation and competitive pressures are high in the maturity phase, which usually means retailers will turn to a more competitive pricing strategy to continue to boost sales. Again, striking that right balance between outpricing competitors and maximizing profits requires acute competitive insights and data-driven prices. Retailers need a competitive pricing solution in order to find the optimal price for driving sales, capturing market share and establishing the right competitive positioning. As a product nears the end of the maturity stage, promotions can also be leveraged in the maturity stage to combat slowing sales growth. Often promotional strategies are driven by vendor relationships or last year’s playbook. But optimized promotional strategies are driven by promotional price elasticity of demand. The surest way to eliminate ineffective promotions and have more leverage at the vendor negotiation table is to use a data-science solution that models promotional price elasticity of demand and accounts for the other factors that impact promotions, like vehicles, tactics, vendor funds, cannibalization and affinity.
While introductory pricing may be the most difficult to establish, markdown pricing is perhaps the hardest to do profitably. For markdowns to be optimized they must be set by consumer demand. Yet without the analytics, that demand is hard to track and predict. Clearing out inventory quickly and profitably has just as much to do with timing as it does with price. A common problem we see is retailers waiting too long to start marking down prices, thus demand is almost gone and the retailer ends up with steeper discounts and margin-loss. The key to optimal markdown plans that maximize sales, margins and sell-through is a distinct data-driven strategy for each product built around the right cadence and aligned with your inventory and profit goals.
As you know, different products may have different lifecycles, even within the same category. This means lifecycle price optimization is most effective when strategies can be applied at a granular level, getting down to the specific SKU. A less robust data-analytics solution will result in money left on the table and less-accurate demand predictions. From short, seasonal lifecycles to long, ongoing products, Revionics’ suite of pricing solutions offers both the granularity and flexibility major retailers need to truly optimize prices for every product, at every stage, in every lifecycle, tailored by region, channel and more. Ready to start your lifecycle price optimization journey?