However, many different types of software and systems are available. Some are reactive and some are proactive. Some solely analyze the sales cycle or initial price point, while others start their analysis in the product development phase. We will explore this ever evolving landscape of price optimization software below.
Product Pricing is one of the most difficult decisions retailers and brands make on a daily basis. They ask themselves, “What are our customers willing to pay? Are we leaving money on the table, or is this a markdown waiting to happen?”
In the past, retailers relied on in-store testing, sales history for similar products, and traditional competitive analysis to determine pricing for new products. These methodologies overlooked the most essential determining factor in price optimization: The voice of their customer.
Forward thinking retailers are turning to predictive software in order to understand optimal price points and markdown strategies before their products hit the marketplace. Not only are these tools more effective, quicker, and less expensive than traditional methods at determining pricing strategies, but they can also provide recommendations for value-add features backed up by cost-benefit analysis.
Depending upon the price optimization software, a multitude of different technologies and methodologies may be employed to provide insight for users. Some software relies on historic sales data and competitive analysis. Our software leverages survey results and Voice of the Customer. Other software is reactive and requires initial test market price point testing in order to derive an optimum price.
Regardless of the methodologies, most software relies on clearly defined objectives, segmentation, and price elasticity analysis. Price optimization software segments potential customers into different categories based upon region, affinity, or other factors. Analysis tools will then measure or predict the price elasticity, providing guidance for pricing based upon the different groups or segments defined by the retailer. Depending on the software, recommendations for markdown cadences and broader sell-through strategies may also be provided.
Industry leading price optimization software platforms such as First Insight’s InsightSUITE platform are driven by a multitude of factors and technologies including those referenced above. We use a combination of predictive analytics tools, Voice of the Customer, historic sales data, machine learning, artificial intelligence, human computational modeling and Bayesian mathematical models to determine pricing strategies. This may sound complicated and time consuming to manage, but in practice, most of these processes are automated and can deliver meaningful results within 24 - 48 hours through our easy-to-use dashboards
Pricing strategies can be optimized by region or nation, affinity group, retailer type, customer purchase history, or a multitude of other factors that are used for traditional segmenting in your marketing and other efforts.
Timing can be a significant factor in pricing for initial product launch as well as optimizing markdown cadence. Optimize your pricing by season and discover optimal timing for discounts and promotions.
Experiment with adding different features to your products and perform cost benefit analysis. This is especially impactful when using predictive tools such as our InsightSUITE because you can test product concepts and variants without actually producing a product or sample.
Utilize price elasticity reporting to determine the optimum margins and production run. Avoid under-charging or over-producing products by estimating total unit sales at a particular price point and determining the perfect ratio of price to quantity.
Price optimization tools, especially those that rely on Voice of the Customer, can provide additional insight into different pricing thresholds and buyer personas at each threshold. This allows for optimized markdowns and targeted promotions.
Some price optimization tools can also help you determine which marketing messages and packaging increase perceived value the most, allowing for additional improvements in margin or a higher price point.
The U.K.-based retailer has since expanded the consumer-driven predictive analytics software platform to more than 50 departments
The Trade War between the United States and China continues as frequent tariff announcements affect billions of dollars of imported goods
Mark-Higgins discusses how Deer Stags was able to identify opportunities to increase price through First Insight testing.
A major footwear brand has completed the design phase for a new assortment of strappy sandals. There are several color and material variations that can be introduced to the design. The brand’s goal is to optimize sell-in while preserving their flagship style in the assortment.
Test the entire assortment at various target ticket prices using First Insight’s predictive price optimization tools. As the product had already passed the design phase but had not yet entered the market, a focus was placed on deriving the optimum price to maximize demand.
For the flagship style, the manufacturer found that dropping the ticket price from $99 to $79 could more than double initial demand -- from 17% to 46%. This led to the highest gross margin (73%), dollar sales and unit sales per week of all sandals tested.
A shoe buyer wanted to understand how to price and buy a new bootie they planned to offer in several colors. They wanted to optimize full-price sell-through at 60%.
The buyer tested the new bootie across all color options with First Insight’s InsightPricing to determine the optimal price point for the group based on their targeted sell-through goal.
Most colors showed full-price sell-through close to 60% at $149. They modified their buy depths per color based on value scores and % sell-through vs. the 60% target. The buy was increased by 3,300 pairs. This style was the season’s top performer with strong sell-through and no additional markdowns.
While most pricing optimization tools are reactive, First Insight offers a forward-looking price optimization solution as outlined in the case studies and use cases above. Our system can provide pricing strategies much earlier than other optimization software and is leading the charge for the next generation of pricing technologies.
Our platform collects customer feedback on new product designs through social, email, and third-party panels to gather a statistically significant sample size. Our platform then analyzes the responses—forecasting the outcomes for key product decisions within 24 to 48 hours.
The results include clear product recommendations, aggregated customer comments, and vital price sensitivity data. The pricing data features an elasticity curve for each product which includes the predicted Average Unit Retail (AUR) aligned with your business’ typical markdown cadence. Our platform allows you to easily identify winning products, and price them right from the outset.
The Voice of the Customer and AI are combined to forecast how a product should be priced—even without any sales history—for effective retail price optimization. By using First Insight to optimize their initial pricing and markdown cadence, our customers are making better pricing decisions – faster – to get to market quickly with the right products at the right price.
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