Dear retailer, let’s talk about pricing.
Pricing holds immense power when it comes to driving profits. The better you wield this power, the greater your returns.
In the fiercely competitive retail landscape, it is crucial for retailers like you to assess their competition. Understanding where you stand in relation to your main rivals is key to winning over customers. In a previous article, we discussed the importance of competitor intelligence, which involves gathering and analysing publicly available information to gain valuable insights into the competitive landscape. Armed with these insights, you can make strategic decisions regarding your pricing strategies. But how exactly do you determine the right price?
First and foremost, let’s establish one fundamental truth: the cost of your product is irrelevant. The right price is simply what the customer is willing to pay. Dynamic pricing is a strategy that allows businesses to adjust prices in response to market conditions, changes in demand or negotiations between buyers and sellers. To employ this strategy effectively, retailers must closely monitor their competitors’ pricing. Artificial intelligence (AI) can be a valuable tool in understanding your rivals’ pricing strategies.
By leveraging technology to capture customer insights and consumer credit data, we can calibrate your new pricing approach. Our approach incorporates flexible web scrapers, product categorisation and matching models as well as interactive insights dashboards for validation and decision-making. This enables our clients to identify pricing opportunities, respond swiftly to competitors, detect market trends, adapt assortment and pricing, and analyse long-term competitor strategies.
Let’s illustrate our approach with an example. One of our clients operates a vehicle maintenance and servicing auto centre business. Like other service providers, the client could not provide customers with a fixed service price upfront, relying instead on estimates. However, this lack of transparency can lead to negative customer experiences when the final price exceeds the estimate and hinder accurate revenue forecasting for auto centre managers.
To address this, our analytics practice designed and implemented a multi-algorithm solution. This solution employs statistical, predictive and machine learning models to predict the most suitable fixed price that a customer will pay upfront. It calculates a ‘price corridor’ using statistical methods — a safe range within which a price can be quoted based on actual historical prices paid for services specific to the customer’s vehicle make and model. Furthermore, the solution leverages machine learning to predict the workload for a specific auto centre on a given day. This workload prediction determines where the final price falls within the ‘price corridor’. As a result, our client experienced greater sales conversion due to transparent and predictable pricing, increased customer retention, and accurate revenue forecasting at regional and national levels.
Contact us today to get an offer on how we can help you set your dynamic pricing strategy.
Dr. Danilo Zatta, Partner
+49 172 6937532
Anders Worsøe Gantzhorn, Partner
+45 2022 5337