discover | Wednesday - 25 / 09 / 2024 - 1:12 pm
After publishing our blog post “Let Your Customer Set the Pricing Strategy Themselves!”, we received numerous messages asking the same question: “How do I set the right price?” This is when we realized the shortcomings of our old system (Logix ERP). Here we may remember that, Arabs say “to admit/acknowledge fault is a virtue”.
Before we delve into the topic, let’s agree that pricing isn’t merely a function; it’s a strategic lever that drives profitability and competitiveness in the market. For this reason, it’s crucial to have an advanced and reliable tool that can handle product and service pricing optimally.
No one can doubt the proficiency of Logix ERP system in managing internal operations, but the system fell short in the realm of pricing… and it needed some improvement (which is exactly what we did).
– Our previous system worked on the principle of a fixed product/service price, based on static rules and historical data, which didn’t reflect real-time market dynamics or competitor behavior.
– Our Logix ERP system wasn’t equipped to collect and analyze external market data, competitor prices, and customer behavior (which limited users’ ability to set competitive prices).
– Even if a user wanted to implement an effective pricing strategy, customizing the Logix ERP could be quite complex!
Such shortcomings prevent organizations from progressing in the market. With suboptimal profit margins, expansion becomes challenging. Therefore, we had to develop a more intelligent solution to address the emerging challenges of pricing services and products.
AI-based pricing algorithms have changed how businesses determine their pricing strategies. These algorithms leverage machine learning to analyze vast amounts of data, identifying patterns, correlations, and trends that human analysts may overlook. Here’s how they work:
– Data Collection: Pricing algorithms gather historical sales data, competitor prices and offers, customer behavior, and current market conditions to enhance pricing recommendations.
– Data Preprocessing: Raw data is cleaned, transformed for analysis by handling outliers, missing data, and normalizing it.
– Feature Extraction: Relevant features affecting pricing like demand volume, seasonality, competitor prices are selected for analysis.
– Machine Learning Models: Algorithms use machine learning models such as neural networks or decision trees to analyze features and establish relationships for pricing decisions.
– Model Training: Models are trained on historical data to learn relationships and make predictions by recognizing patterns between different factors and pricing decisions.
– Price Prediction: Trained models predict optimal prices for products or services in real-time considering key aspects like region, market conditions, seasonality, demand for accurate pricing recommendations.
– Real-Time Adjustments: AI-based pricing algorithms continuously monitor data and market changes to adjust prices in real-time based on demand fluctuations, competitor price changes, or other relevant factors.
– Feedback Loop: Many AI-based pricing algorithms have a feedback loop to continually improve the model with new data ensuring adaptation to changing market conditions over time.
– Deployment: The algorithm is integrated into the business’s pricing system to automatically set product/service prices based on its recommendations.
– Monitoring & Evaluation: Close monitoring ensures these algorithms achieve desired results. Regular evaluations and adjustments are made to enhance accuracy and effectiveness.
Now, we are ready to answer our customers’ question “How do I set the right price?” The concept of the right price varies depending on several factors:
– Profitability: The ability to cover costs and make a profit.
– Competitiveness: Meaning that the product’s price is competitive, or equal to similar products/services.
A measure of how willing customers are to buy a particular good or service when the price changes.
Typically, we might assume that demand is price elastic. When the price of something increases, customers’ willingness to pay decreases. But this is not always the case. Some goods are inelastic [meaning customers continue to buy regardless of price, even when it increases], such as prescription drugs, baby formula, and other essential goods.
Price elasticity is an important concept that any company should understand. If one of your products does not have elastic demand, you can adjust (raise) prices and keep most of your customer base. But with elastic products/services, you may want to keep your prices low to maximize sales.
Simply put, you are supposed to set “different prices,” starting from an initial price (based on production costs, marketing, and industry research, including consumer insights), then adding different price tiers:
– Discounted price: Discounted pricing is a powerful way to attract new customers, increase sales during downturns, or get rid of aging inventory. Discounted prices are usually offered for an indefinite period of time.
– Promotional price: Promotional pricing is a price reduction but for a limited time. It is usually tied to events such as White Friday and seasonal holidays. While discounts are generally designed to attract additional (much-needed) business or attract new customers, promotional pricing aims to create a sense of urgency or scarcity or to test new products or services. Even luxury brands may reduce prices or launch promotional offers from time to time. Although they may avoid “buy one, get one free” offers or price tags ending in 0.99 riyals – which may weaken the value of their brand – there are other tactics they may use, such as free gifts with purchase, low-cost gifts with purchase, and free shipping. Achieving the right balance between initial prices, discounted prices, and promotional offers requires a high degree of precision. Smart performance indicators that combine customer data, consumer behavior, and competitor prices can help you achieve the right balance.
– Break-even analysis: As the term suggests, break-even analysis is a model that determines at what price point your company can break even. It identifies the exact price needed to cover all production, distribution, marketing, and overhead costs of retail sales.
– Target return pricing: This is a more complex model that helps your company set prices with numbers that enable you to achieve a target return on your investment. This model takes into account the calculation of all costs in break-even analysis and also considers the desired profit return.
– Marginal cost pricing: This model sets prices so that production costs and overhead costs are less than the total revenue generated by the selling price. While target return pricing is concerned with achieving specific business objectives, marginal cost pricing sets the price equal to the marginal cost of production (= cost of producing an additional unit of the product).
– Psychological pricing: This strategy takes into account the consumer’s mindset (perceptions) when making a purchase decision. Pricing improvement techniques here may include creating a sense of scarcity, a sense of urgency, or a sense of value.
– Dynamic pricing: In this model, prices change dynamically over time in response to market demand, competition, or other factors. This model is commonly used for online products and services.
These were just a few examples of pricing optimization. There are other ways to set or adjust prices, and many pricing strategies can be a hybrid approach.
The right pricing strategy depends on many factors, including your business sector, the products or services sold, your target market, and pricing data from your competitors.
If you’re using old or inaccurate data, you’ll end up setting prices that are too high or too low. You won’t understand current market trends and consumer preferences. The accurate, up-to-date data you need should come from sales figures, market research reports, competitor intelligence, and industry publications. A logic AI system can analyze data to identify trends and patterns, including improving data visualization.
Many business owners pride themselves on having a “gut feeling” that they can rely on to make big business decisions. While some people may have these magical instincts, relying on guesswork is a big risk. It’s influenced by personal biases, which can lead to real-world disasters in the corporate world. Another problem with guesswork is that the loudest or highest-ranking person in the room often makes the decision, and they may make decisions that aren’t grounded in reality (data). Using data provides a neutral framework to work from, ensuring informed decisions.
Did you know that when you discount your prices too much, you’re actually devaluing your products and services? Customers who are always looking for a bargain want deals, and if you offer too many discounts, you’re training them to expect (and demand) them all the time. Additionally, deal-seeking customers aren’t loyal to brands; they may jump ship at a moment’s notice. Excessive discounting can also hurt your regular sales numbers, as customers will buy your goods at a discounted price when they were willing to pay full price. Finally, frequent discounting will make it difficult to raise prices in the future. Even if customers value your brand, you’ve trained them not to pay full price; you’re the “always-on-sale” business to them.
Your pricing strategy might fail or be less effective if you don’t price your products or services based on the value they provide to customers. Ask yourself these questions:
– What problem does your product or service solve for your customer?
– What impact does it have on their life? As mentioned before, you can’t set prices that are too high or too low. Set a price that’s high enough to make a profit and/ or position yourself as high-quality, but not so high that it scares customers away. That’s why understanding the value you provide and your customers’ perception of that value is crucial. It’s simply not about multiplying your costs by 2.5 to arrive at a selling price! Take prescription glasses as an example. High-quality lenses and custom-designed frames cost between 34-79 SAR (Saudi Riyal) to manufacture, but they are sold with profit margins of up to 1000% or more. Customers are willing to pay more because of the impact that prescription glasses have on their lives, and they are accustomed to the high price. In fact, customers are unlikely to trust a store that sells them for 100 SAR.
Even if you’re primarily selling to the Saudi market, the geographical expanse of the country is vast. The cost of living varies significantly across regions throughout the Kingdom. Even within the same urban areas, many retailers set prices for goods differently based on local market conditions. Certain suburbs or parts of suburbs may have different residential and economic characteristics.
Additionally, customer expectations and commercial competition may vary by location.
Using geographic-based pricing – or micro-pricing – helps you optimize prices and maximize profits. You’ll also maintain customer satisfaction by meeting the specific expectations of “narrow” market segments.
What Makes Logix AI System Indispensable for Setting the Right Pricing Strategy?
Pricing the products and services you offer is somewhat like searching in the dark. You may eventually find what you’re looking for, but no one enjoys blindly searching while stumbling around in the dark. Improving prices, without data, can be similarly frustrating.
Many companies set their prices based on the prices charged by their competitors, which may be true, but for most companies, this approach is not ideal. A correct pricing strategy should consider production and distribution costs, changing customer demand, competitor prices, business objectives, and the “prevailing” market price that customers are willing (or accustomed) to pay.
This process remains arduous and time-consuming because doing it correctly is crucial, but artificial intelligence can help you automate large parts of the process through specialized analysis and actionable data visualization.
This is what makes Logix AI system indispensable for setting the right pricing strategy