Strategic Product Line Planning Using Predictive Analytics

Predictive Strategic product line planning provides a marketing research strategy that determines the optimal set of combinations, such as colors, flavors, package sizes, and scents that minimize the dynamic market risks, etc.
By: THE MARKETING ANALYSTS
 
May 26, 2009 - PRLog -- Product Line Strategy: http://www.themarketinganalysts.com/en/pages/Strategic-Product-Line-Assortment-SKU-Management/

Minimize Your Risk When Launching New Product Lines
Product Managers and Brand Managers have many critical decisions to make when when they introduce product line additions and completely new product lines.  The costs alone can be astronomical, particularly for small manufacturers and food producers.  Not only do companies need to provide an adequate budget the R&D and marketing launch costs,  they must also pay slotting allowances to retailers that can range from $10,000 to $40,000 or more per item regardless of whether the product is a success or a failure.

Although brokers often suggest that manufacturers can simply build slotting costs into product cost, the market rarely makes this possible.  As  a result, most retail products sell with razor thin margins.  While retailers may offer limited trials, the terms of these programs require that manufacturers purchase expensive merchandising packages that include  in-store radio and newspaper advertising.

Predictive Strategic Product Line Planning
Predictive Strategic product line planning provides a marketing research strategy that determines the optimal set of combinations, such as colors, flavors, package sizes, and scents that minimize the dynamic market risks such as retail space limitations, items being out-of-stock, poor visibility due to shelf positioning and perception of item similarity.  The benefits of this type of predictive product line research is that it provides Product Managers and Brand Managers with the answers they need before their employer invests in product development and marketing launch plans.

Here’s How it Works
Johnsonville Juices is preparing to launch a new line of natural flavor, low-calorie juices.  Currently, the R&D lab and the Marketing group has developed recipes for 17 potential SKUs for this line.  From these 17-SKU’s, the Marketing group plans to offer only 4 to 6 SKU’s.  Johnsonville Juices must determine the right set of SKUs that consumers will perceived as being unique and that also offer the greatest potential for reaching sales targets and consumer appeal over the entire product line.  

Solution: Predictive Product Line Modeling
THE MARKETING ANALYSTS used a research methodology that applies a sophisticated analytical procedure and considers the economic utility of each SKU in terms of all possible combinations of SKU’s being considered for the product line.  The predictive model works by applying a form of mathematical gametheory and assigs a score to each SKU being considered with respect to all possible combinations of SKU’s.  Next, the scores are rank ordered.  The set of products offering the highest scores represent the optimal product line.

In addition to providing the brand manager with strategic decisions at the R&D stage, it also provides a roadmap for success for SKUs that can be introduced later.

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THE MARKETING ANALYSTS was founded in Dallas, Texas to provide a one-stop solution for high quality, low cost marketing services. Initially launched as a marketing research company, we now provide a variety of integrated marketing solutions including web site design, search optimization, proofing and language translation services. Our team is highly talented and consists of Marketing Ph. D’s, Marketing Managers, Mathematicians, Computer Science Engineers and Language Translators who hold advanced degrees from respected universities known around the world.
With direct access to highly skilled talent pools in eastern european, we are able to leverage all activities to effectively meet each of our client's unique objectives.

Dallas Marketing: www.themarketinganalysts.com
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