Defining In this section we will have a look at the overall benefits of an optimization strategy and why you should consider having one.
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Benefits
Lets explore some of the benefits of an effective price optimization strategy, we can clarify them into several different categories:
Financial
A primary benefit is that our solutions for retail price optimization will provide an opportunity to concentrate on different and subtle details in our marketplace. For example: after implementation of our new price optimization strategy, the overall sales in a given product category can be lower, but the gross margin as a whole goes up. This improvement will allow us to focus on refining other important aspects of our products like product packaging, branding, improving product descriptions by giving lots of details. All of these will n encourage your customers to keep shopping.
Category Management
Thanks to price optimization software you can use some rules to particular categories from your store. Price strategies can be activated automatically, semi-automatically or manually – it all depends on specification of a given industry or products, which you sell.
Notice also that this system can be very helpful and useful to the category manager (PM), who will simplify a complicated work with all categories. Thanks to that support, the worker can be more effective.
Process Automation
The migration to a Price optimization solution will help to to eliminate manual operations and can effectively minimize the problems related to common human factors (i.e. transpositions, typos, inaccuracies, etc.). The automation that arrives with optimization will eliminate that random sales forecast and allow organizations to adjust and optimize prices when warranted. Most importantly, these optimized price changes can be relayed to all sales channels at exactly the same time.
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EXAMPLE: Take any large multi-layer organization (i.e. Amazon, Exxon, Walmart, etc) and think about how they have become such a giant retail operation. Imagine all of the price changes they must be making every single day and then imagine trying to accomplish those price updates manually! |
Cohesive Pricing
One of our biggest challenges can be the cohesiveness of our prices to customers across many different sales channels. When price optimization is integrated into your sales channels, the worry about cohesion of your offer will be eliminated through the use of established business rules that will provide the necessary boundaries to ensure your offers will be cohesive. This will eliminate customer confusion since your prices will always be correct, accurate and profitable.
Faster Decisions
One of the attributes of pricing optimization applications is to increase the overall speed of decisions as our prices are based on historical and factual data and not intuition or best guesses. With automation we will be able to identify and react to emerging trends impacting our price drivers (cost, transportation, regulation, etc) and respond faster than our competition.
Types of Optimization
When thinking about optimization there are several different paths to choose from:
Traditional
In a traditional price optimization application, the use of sophisticated mathematical analysis is used as a means to predict customer behavior based on historical transaction data. As an example, we might use a regression analysis, which is the measuring of impact of one variable on others, to determine the overall impact of competitor price changes on your company’s sales.
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REGRESSION: In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable and one or more independent variables. Its definition comes from Latin term of regressus - to go back (to something). In that sense, regression is the technique that allows us "to go back" from messy, hard to interpret data, to a clearer and more meaningful model. |
This analysis can be tailored to different customer segments by simulating how targeted customers will respond to price changes. Working in this way can provide multiple data-driven scenarios that provide in-depth forecasting through different channels.
Cost-based
Manufacturers most commonly use this method of pricing, since it generally will require the least amount of information about customers and consumers. Overall, this is a simpler method that will consist of using the cost of creating the product plus the percent markup that is necessary.
Competitive pricing
The competitive model is most often used in online retail scenarios, in this situation companies monitoring their competitor’s prices and then will generate their own price setting using all of the information gathered. Typically, this pricing method uses various pricing rules to ensure that the company’s price for a certain product reaches a certain position in the market (e.g. being the cheapest available).
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Optimization Example As an example, a traditional rule-based optimization strategy would a set of predetermined pricing rules. These pricing rules for a grocery store may include: mark up on all products in the “produce” category by 10%; reducing cereal brands in a marketing campaign by 15%; employing a 12% reduction in key-value items to equal the prices of a competitor; and adjusting all prices to end with 0.99. |
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