Wouldn’t it be great to have insights into your product’s future behavior? So you can decide upfront if intervention is necessary or a waste of time. That you know an extra marketing campaign will have a significant impact or that your money is better to spend somewhere else. This sounds great, doesn’t it? Well, now it is possible!
Client Case RatioForm
It started all with the challenge our client RatioForm Verpackungen gave us. Product management at RatioForm was faced with the everyday challenge to manage a high number and a diverse number of products, resulting in very complex portfolio planning.
Challenge:
- Too many and too diverse products
- No insights what products have the highest impact on future business
- Too much time spent to identify relevant products
When dealing with a large product portfolio, there are often already metrices on how products are performing based on past sales. However, it is very hard to get solid predictions for each product and the relations between them. How to identify whether actions are possible to improve the future performance of products?
Together with our partner Striped Giraffe we took on this challenge and developed a solution for RatioForm that enables them to predict the performance and development of each product in their Product portfolio.
The solution PAULA
So, what did we do? We developed PAULA. Paula is an A.I.-driven product life cycle advisor that supports product portfolio decisions by making predictions for the future.
Paula provides trustworthy predictions on performance, revenue, margin, clients and units sold and sows in a simple overview of what your top- and under-performers will be in the future. Simple, Paula helps you foresee the future!
How does Paula work?
Yes, it sounds magic. But it isn’t, it is simply using the newest Machine learning techniques for the better. With M.L algorithms we are able to predict the product life cycle of each product in the future and give suggestions to maximize the revenue of the portfolio. Just to give you some extra insights, this became our recipe to make solid predictions:
Step 1.
Group products with similar life cycle together
Step 2.
Predict the future of the product based on its place in life cycle and evolution of its peers
Step 3.
Verify predictions using time travel
(use for example past date to predict half year forward)
Step 4.
Give weight based on actual revenue or margin contribution so prediction of poor and good future performance is linked to success
(avoid wasting time on small volume products with no potential)
With the use of our Genie platform, we can build these kinds of customize Machine learning solutions and put them in a production environment fast.
To summarize
With the help of this innovation, it is possible to anticipate the supply and demand cycles and to adjust the choices regarding business operations accordingly. Paula is now totally integrated in the way of working of RatioForm, giving instant insights and saving time. RatioForm knows the products and category of products to focus on to be future-proof.
It is time to create time. How can we solve your challenge? Contact us !
More information:
Read the blog of RatioForm (German)
Read the case study of Striped Giraffe
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