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Setting the correct pricing and promotion strategy is no less than a battle. You will have to strike the right balance between a highly competitive price and an optimal profit margin. Pricing it too low can not only erode your margins but can also negatively impact your customers’
perception of your product quality. Price it too high and it will land your customers at your competitor’s doorstep. In the age of data, making such “big decisions” is no more a risky proposition as brands are making a beeline towards pricing analytics solutions.
Setting the correct pricing and promotion strategy is no less than a battle. You will have to strike the right balance between a highly competitive price and an optimal profit margin. Pricing it too low can not only erode your margins but can also negatively impact your customers’ perception of your product quality. Price it too high and it will land your customers at your competitor’s doorstep. In the age of data, making such “big decisions” is no more a risky proposition as brands are making a beeline towards pricing analytics solutions.
As a business owner, pricing analytics can help you make decisions about prices, promotions and discounts based on historical data. You can use the analysis to determine what price points are most effective for maximizing revenue or when deals generate new sales. This analysis helps you make strategic decisions that maximize profitability while minimizing losses.
In addition to providing insight into pricing decisions, price optimization analytics helps you identify trends in customer behaviour over time. For example, do you notice an increase in sales volume during certain times of the year? You can align your inventory with this trend by adjusting production levels or introducing new products that appeal more strongly during those periods.
A pricing analytics solution helps you to connect the dots between an optimal product price and the right time and place to promote it, thereby creating a successful promotional pricing strategy. However, the success rate is highly dependent on the availability of price sensitivity data, promotion scores, feature values, and the LTV and CAC ratio information.
Here are some of the factors that drive successful promotional pricing in marketing:
A good pricing analytics solution helps you to connect the dots between an optimal product price and the right time and place to promote it, thereby creating a successful promotional pricing strategy
Price sensitivity is the degree to which buyers react to changes in the price of a product or service. Buyers are less likely to accept a higher cost increase if price sensitivity is high. A price sensitivity score is critical in building a dynamic promotional pricing strategy.
Today, the traditional method of dividing the percentage change in product quantity by the percentage change in the price to determine the price sensitivity score does not work well. This method fails to keep up with certain factors. These factors include a change in the cost of the same product by competitors or a trend that fans the sudden popularity of the product. This drawback prompted many businesses to turn to advanced analytics to create dynamic pricing strategies in marketing.
As a real-life business pricing strategy example, retailers actively leverage pricing analytics to create a turnkey promotional pricing model. Generally, a retailer sells a sizable portion of their products at low prices to maintain a competitive advantage. These products are termed key value items that contribute little to the retailer’s profits. Therefore, the retailer must plan the pricing strategy and promotional campaigns for the rest of the SKUs and market the same. However, doing so is easier said than done because this needs historical data regarding those SKUs, also termed long-tail items.
A dynamic pricing analytics solution generates price recommendations for long-tail SKUs by encompassing the
A dynamic pricing analytics solution generates price recommendations for long-tail SKUs by encompassing the ever-dynamic price sensitivity and market conditions. Its intuitive product matching algorithm recommends introductory price and promotion ideas for long-tail SKUs. The elasticity module determines the degree of impact of a product’s price change on its demand. It makes real-time price recommendations based on competitor price changes.
Pricing analytics can help generate price recommendations for longtail SKUs by considering price sensitivity and market conditions. Its intuitive product matching algorithm recommends introductory price and promotion ideas for long-tail SKUs.
ever-dynamic price sensitivity and market conditions. Its intuitive product matching algorithm recommends introductory price and promotion ideas for long-tail SKUs. The elasticity module determines the degree of impact of a product’s price change on its demand. It makes real-time price recommendations based on competitor price changes.
You know that you have an excellent product. You go all out on deciding a price based on the awesomeness. But you witness consumers developing aversion towards your product mainly because of the cost. This aversion is not necessarily entirely due to the price or your product quality. The main culprit can be incorrect value propositions in terms of product features.
You must determine the features of your product that are likely to motivate your customers to buy it. You must set your prices and promotions based on the features that increase the likelihood of consumers buying your product.
Multiple promotional pricing strategy examples failed because of a disproportionate (Life Time Value) LTV and Customer Acquisition Cost (CAC) ratio. This ratio is the basis of effective promotional pricing in marketing. CAC is the cumulative marketing and sales expenditure required to capture a customer. LTV is the total profit your customer may generate through the entire lifetime of their account with your business. Ideally, your business model must incur low CAC and high LTV.
Your pricing and promotional strategy will involve calculating each customer’s CAC and LTV values. These values will generate deep insights into each
customer’s persona. It lets you make your pricing strategies more targeted, therefore heightening the chances of your strategy striking gold in the market.
CAC is the cumulative marketing and sales expenditure required to capture a customer. LTV is the total profit your customer may generate through the entire lifetime of their account with your business.
The major takeaway from this article is that pricing decisions are critical. The key, then, isn’t to adjust your expenses so that they’re as low as possible but to do so in a way that maximizes profit margins. In other words, you want to find the perfect price for your products and then stick with it — but when you change prices next time, try not to drop them too much or spike them too much; instead, try to keep them relatively stable.
Solutions like Analytic Edge’s promotion and pricing analytics tool can help to measure price elasticity, threshold prices and gaps, and price gap elasticity. The solution can accurately predict the impact of promotional campaigns on your sales prospects. Such an accurate prediction enables you to refine your pricing and promotional strategies across all your channels and geographies.
Analytic Edge is a global analytics company that leverages technology and advanced analytics to help companies make data-based marketing decisions. The company’s flagship platform Analytic Edge Qube offers a suite of marketing analytics solutions with a Software as a Service (SaaS) model. The solutions include DemandDriversTM for always-on Marketing Mix Modeling (MMM), SynTestTM for AI powered Test and Learn, PriceSenseTM for pricing and promotion analytics, and PowerViewTM for analytics visualization. Analytic Edge works with clients across industry verticals such as e-commerce, mobile apps, gaming, consumer packaged goods, retail, automotive and many others. The company has offices in Singapore, India, US, Mexico, Brazil, UK, China, Japan, South Korea, UAE and Australia.
