How Algorithm driven technology optimizes price points and boosts sales in the Retail industry

What is Retail Price Optimization

Retail Price Optimization is the use of mathematical analysis by a company to decide upon the most effective pricing for a product or service. Price optimization utilizes data analysis to predict the behavior of potential buyers showcasing distinctive prices of a product or service. Price optimization is an integral part of any business which sells goods or services. Dependent on relevant data, companies use price optimization models to determine pricing structures for initial, promotional and discount pricing. This makes your price optimization strategy incredibly important to a healthy and growing industry. Price optimization practice has been implemented in various industries, retail, e-commerce portals, and fast-moving consumer goods. Price Optimization uses mathematical analysis to determine how customers will respond to different prices. Based on that, prices are optimized to meet the company’s objectives. Machine learning technology takes the forecasting step to the next level by processing much larger data sets and also considers various influencing factors to predict the effect of price changes. They are different types of Price Optimization such as:

• Traditional Price Optimization
• Cost-Based Pricing
• Competitive Pricing or Competitor Price Matching
• Machine Learning-Based Price Optimization

In the retail sector, machine learning is quickly becoming an important tool that allows businesses to take advantage of big data and predict the results. Using the algorithms created for price optimization, companies can have more indicative insights by adapting quickly to market changes with the required price elasticity.

The algorithms can learn patterns from historical data, present data inputs and gives insights that highlight the power of machine learning. Advanced software solutions combine this with forecasting algorithms that allow businesses to predict changes in profit and revenue while, using the forecasting tool, a goal-driven, price steering approach is possible.

Price Optimization models and how to optimize prices?

Price Optimization models: Price optimization models use mathematical algorithms to analyze price changes, and customer demands at various price levels and match the results with the data on costs and inventory levels to skill optimal prices and maximize profits. These models are used by enterprises to forecast future demand for products and services, maintain efficient inventory levels, and build promotional strategies. The models enable businesses to take a more strategic approach toward maximizing revenue while keeping the customer satisfied regardless of the market situation. Data is incredibly valuable when it comes to pricing, however, it can fail if not used efficaciously. There are a couple of different approaches to price optimization models:

1. Simple Rules Engine: New rules are created to fix erroneous combinations. The result is often many layers of conflicting rules which are too complex to visualize. The simple rules engine approach is extremely difficult to manage.
2. “Clever” Math Angle: Algorithms are used to try to solve the issues that the simple rules engine creates. While the solution may work, high-level statistics, operational research, and dictates from a “black box” aren’t suitable for most organizations. The clever math angel approach often is uncertain and doesn’t deliver factual information to the business.

Smarter price optimization solutions allow developments in algorithm-driven technology to fill with the intuition of humans to deliver when it counts.

How to Optimize Prices: A successful optimization strategy will vary for different companies. The core components include a strong understanding of the customer base and access to data and real-time insights that ensure companies don’t have to rely on guesswork or hunches. All of these functionalities can be supported with high-end advanced technology which, can be achieved by following the points below:

• Prepare a Complete Business Analysis: You will need accurate comprehensive data across seasonal preferences, current economic conditions, historical data, operational costs, product availability, demand, and competitor prices. It will show you how all these factors affect demand, prices and, profitability. This will enable businesses to understand where they stand in the market
• Do Customer Analysis: This connects with the previous step because it is also about gathering data as well. It is important to know your customers and their perception of your brand. You need to look at customer reviews, customer sentiment, demand data, market trends and, supply data. This data guides you towards the major changes to be made to both prices and product features. Additionally, you can get extra details from customers through surveys or interviews
• Leverage Real-Time Insights: Many companies make the mistake of compiling data and only looking at it from time to time. You can overcome the competition by leveraging insights in real-time. Thus, you’ll put your company in a position where it can respond to any changes in demand and march toward profit
• Value Metrics: A value metric is a way to measure how your customers value your products and services. which aspect they value the most so that you can optimize prices accordingly. It is very important to align prices with customer needs
• Comprehensive Data Analysis: Once all the data is collected and value metrics have been determined, it is time to analyze the collected data. If you are using a machine learning tool, then it will reveal patterns as per customer segments. It will highlight trends and provide smart price recommendations that you can use to optimize prices accurately
• Pricing Strategy: You need to have a pricing strategy in place to start setting or altering your prices. The goal is to align with your business objectives and what you want to achieve with price optimization
• Set and Monitor Prices: Once all your previous steps are completed, it’s time to set the price for your product or service. A market change is inevitable the frequency of price monitoring and, price adjustments depend on your industry, competition, and goals. Before changing your product prices again, you should pay close attention to how your customers respond to the price change and analyze the results
• AI and Automation: Technology has so much to offer, so always keep an eye out for the latest developments in pricing optimization. Artificial Intelligence and automation can help businesses offer the best possible pricing at any given time. They can also cut down on time spent managing processes manually, and make use of the manpower to explore even more advanced optimization options

It is consequential to understand that price optimization isn’t always about lowering your prices. It is about analyzing how your brand is recognized and understood when your customers are ready to pay more and when they want low prices.

Price Optimization Machine Learning and its importance

Machine learning offers a way to simplify the collection and analysis of retail pricing data at scale. Machine learning and price optimization go together because in a dynamic market, precision is the key, and there is no scope for error. Machine learning is all about efficiency, and optimizing prices. Manually managing the data is tedious and complicated but can also lead to manual errors and delays. Factors such as historical data, marketing campaigns, and seasonal inventories can all be filtered into the algorithm as the data is collected and compared, thus providing meaningful insights to take action. Machine learning makes it all fast, easy, and accurate. Machine-learning adapts and learns which is its biggest asset.

Retail price optimization tools equipped with machine learning also make it possible to keep pace with rapidly changing consumer expectations and supply chain trends. The tools allow the ability to ‘learn’ and get more precise by evaluating the data constantly to find the optimal price point for retailers. Retailers can streamline the speed and accuracy of the process by implementing agile analytics tools boosted by machine learning algorithms. A retail giant is an excellent example because it changes the prices of millions of products every day. They couldn’t have done this manually. Artificial Intelligence made it possible. Another price optimization software– the world’s first AI-driven Autonomous Analytics platform for customer commerce. It goes beyond traditional practices to deliver a holistic solution with real-time insights into what happened, why it happened, and what can you do about it.

Retail Price Optimization software/solutions

When choosing a price optimization solution, you want to go with scalable software, that needs minimum integrations and utilizes advanced technology. A price optimization solution must be able to handle massive complexity. Sophisticated price optimization algorithms are fast becoming critical to success and while the maths may not be accessible to all, optimization solutions should be structured in such a way, that it is simple in their understanding and control.

• AI-Driven: AI-driven capabilities and machine learning-powered technologies are essential in a smart price optimization solution. With an AI-driven solution, you can also get automated price adjustments and smart price recommendations that will help you update your product prices instantly
• Offers Real-Time Monitoring & Smart Insights: An advanced price optimization software should offer you the capability of monitoring prices in real-time. Historical data or outdated data won’t suffice especially, if, you are an e-retailer. An ideal price optimization software will give you real-time insights with frequent refresh prices, so you have the latest information with you at all times. This helps in making a quick decision. Real-time pricing data will also ensure that your company is always one step ahead of your competitors
• Automated Price Updates: Smart price optimization software must allow you to automate price optimization based on predefined rules. It should be flexible to update or delete rules anytime and alter your products to track with ease. Moreover, it should have the capability to automatically update prices on your websites whenever there is any change in the price in the system based on competitor prices or any other present parameters
• Easy to Set up & User Friendly: A price optimization software that can be seamlessly integrated with your internal systems and does not require substantial size infrastructure to operate. Opt for scalable APIs and cloud-based SaaS platforms that can be set up with minimum effort and can enable data access in any preferred form. Make sure your software is easy to use and offers a unified dashboard, comprehensive reporting capabilities, and sends you alerts or notifications or any changes so you do not miss out on any price movements or price changes in the market.

Benefits of Price Optimization in Retail

Pricing optimization in retail enterprises brings a multitude of benefits, which are evident throughout the process. Below are some of the main advantages of pricing optimization strategies.

Gain ROI: With price optimization software, it is easy to see how things are improving. ROI can be closely monitored, with all changes available to view on a real-time basis. This data-driven approach enables businesses to respond to fluctuations in demand at high speed, maintaining the best possible ROI for the company. In the early stages of a new and improved price optimization strategy, retailers must focus on a few of the key factors in pricing that can make an immediate impact:

• Current Price Point
• Margin of Sales
• Inventory
• Competitor Pricing
• Promotions & Discounts

The above factors can be changed and updated in real-time, so retailers can see the impacts and adjust according to their objectives. Retailers who determine their pricing goals based on past data and analytics will be able to see the most immediate impact on their revenues.

• Forecast your Customer’s Behavior: The more data a company has, it can understand its customers better. With this understanding comes immeasurable opportunities. Predictive pricing, a feature of pricing analytics platforms for retail, allows you to track market pricing, adjust your pricing, and make data-driven pricing decisions automatically based on customer data. With the help of advanced marketing algorithms and the data you already have, you can forecast the impact of specific price changes. The potential of the advanced analytics systems allows you to get powered with data and use your insight to target customer demographics based on the optimal price point for your users
• Automate your Operations: Automation is seemingly taking its position in all industries, so there’s no reason it should not be part of your retail price optimization strategy. Manual price tracking, adjusting, and forecasting are too time-consuming and costly, as you’re losing out to competitors who are updating quicker to maximize profit margins. Automating the aspects of your pricing strategy helps to avoid common man-made errors that impact sales/revenue
• Respond to market trends on a real-time basis, maximizing potential sales/profits

To implement pricing automation, find a machine learning program that helps with a superior AI Auto MLOps price platform, which can be configured to work with all other applications you’re using.

• Act faster to market changes: Pricing Optimization software makes it possible for companies to adapt quickly to the changes in the market, outsmarting their competitors by offering goods and services at the best possible prices for any given situation.

How FutureAnalytica can help in this journey

FutureAnalytica is the only holistic automated machine-learning, no-code artificial intelligence platform providing end-to-end seamless data-science functionality with data-lake. Artificial Intelligence app-store & world-class data-science support, thus reducing time and effort in your data-science and Artificial Intelligence journey.

We at FutureAnalytica empower the large-scale AI deployment and management that unifies the release cycle for machine learning and software applications. It enhances data validations, ML model testing and integration, enabling the application of agile principles to machine learning models.

With FutureAnalytica.ai, AI-powered solutions optimize prices for products and services through different channels to increase revenue and better customer loyalty. It can provide real-time insights for quick decision-making regarding the changes in the market before the competitors take action. Enrich Customer Experiences with superior AI Auto MLOps to deliver more.

Conclusion:

To conclude, the role of price optimization may have been one we have seen since the dawn of trade, but with advanced technology, it has evolved into a sophisticated system with better analysis and results.

Thanks to machine learning, businesses can take key pricing variables which include purchase history, season, inventory, and competitors’ pricing is taken into account. Companies can ensure the best prices, even for a vast inventory of products or services, that can achieve the set KPIs. Many retailers because of the accurate insights are embracing machine learning as part of their analysis and price optimization. Price optimization enables retailers to understand how customers react to different price strategies for products and services you can set the best prices in the market.

We hope this article was insightful and helped you to understand how you can deliver more engaging and curated experiences for your customers. By mapping price points and transforming them into actionable insights, retailers can create greater loyalty and increase revenues. Transforming the shopping experiences from customer engagement, to predicting demand, discover how FutureAnalytica No-Code AI platform improves operational efficiency by automating tasks. Thank you for showing interest in our blog and if you have any questions related to Price Optimization, Machine Learning, or AI-based platforms, please send us an email at info@futureanalytica.com.