Nils Streitbürger, Founder & Managing Director
In the light of his experience running a consulting business for retailers and brands in the fashion and sports apparel industry, Nils Streitbürger witnessed firsthand the pain points that his clients faced when it came to pricing products optimally. On the one hand, there is the volatile nature of changing trends and customer preferences; on the other hand, the intense market competition raging on at both online and brick and mortar fronts. Price markdowns cost retailers between 10 to 25 per cent of their turnover, about half of it results from incorrect pricing decisions. Also, the price reduction process is time-consuming and is often a guess-game that retailers undertake, which in itself can detrimentally impact revenue immeasurably. Dynamic, proactive price optimisation is the way to go. For one, it can, in addition to improving sales and gross margins, influence smart stocking decisions. But the challenge here stems from the access to cutting edge, predictive AI technology that can enable it. Even for large retailers, kick-starting an AI initiative for price optimisation is not only a costly affair but also one that comes with a high risk of failure. Technology and in-depth industry expertise is a crucial factor for such huge undertakings. This is precisely why Streitbürger founded Panther Solutions in 2018, which brings to the table the price optimisation silver bullet, Panther Pricing, made by retailers for retailers.
“We have transformed our extensive big data analytics expertise into an easy to implement, intuitive to use, and cost-effective tool for every retailer,” mentions Streitbürger. Leveraging the prowess of AI and the cloud (for seamless implementation), Panther Pricing generates automated price recommendations that enable retailers to reduce price markdowns significantly. Working in tandem with electronic shelf labeling systems, Panther Pricing can automate and implement price reduction down to the POS levels. “By using our software, price markdowns can significantly be reduced resulting in an average margin increase of 3 full points. We bring clarity into the decision making that relates to optimal price reductions and generate profit-optimised pricing - customised for each retailer and each item,” he adds.
We answer the key questions concerning optimal price reductions and generate profit-optimised pricing - customised for each retailer and each item
For instance, Panther Pricing can suggest ways to clear current stocks for standard as well as seasonal items. The offering leverages parameters and algorithms for strategic target settings based on revenue, gross margin, or even stock levels. It also has statistics functionalities that project expected outcomes based on price recommendations and markdowns.
A key differentiator of Panther Pricing is what Streitbürger describes as the data pooling concept, which makes up for a small retailer’s lack of huge volumes of data for analysis. This, combined with the low pricing model of the offering has enabled even small and mid-sized retailers to benefit from robust data analysis capabilities, and in turn gain optimal price reduction recommendations to achieve target sales levels. Retailers can go up and running with the solution in 6-8 weeks, with monthly subscription costs starting from as low as 200€ - based on stock volume.
With an attractive go-to-market strategy and a proven technology solution, Panther Solutions has been able to partner with an impressive lot of retailers and brands, many of whom are household names across Germany and Europe. The company recently signed a deal with Australia-based data integration and solution provider Integration Wizards, who would be the exclusive Australia and New Zealand distributor of Panther Pricing; which is a significant milestone in their international expansion plan.
On the solutions side, under Streitbürger’s leadership, the company plans to augment further its solutions with value-added initiatives under a “Total Impulse Management” umbrella, which would enable retailers to influence customers’ buying impulses. The possibilities include transference of items from one store to another based on demand and stock levels, identification of products to be included in marketing campaigns (with pricing recommendations), store sales floor performance heat mapping, which at the end are considered in an overall integrated manner and finally are put in relation to the optimal price setting. The Impulse Management recommendations will be driven by fully automated AI based impulse decision engine. Evidently, the company is en-route to broadening the scope of price optimisation to newer, promising dimensions.