https://store-images.s-microsoft.com/image/apps.47651.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.ca4be590-aea3-45d2-b394-808c1959cde2
Stipra
από TEKNTRASH INC LTD
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Test drive your products and reduce customer churn
According to Harvard
Business School each year more than 30,000 new consumer products are
launched and 80% of them fail. This is confirmed by Nielsen, which
points out that more than 85% of new CPG products fail.
And why? Simply because they lack post-sales data. Instead, they depending on sales data to calculate the next batch. But this is the worst type of data for a new product!
For, the fact a product was sold to a wholesaler or even to a direct consumer channel such as a supermarket does not mean it would be sold again, as it could be that the end consumers did not like the product and will not repeat the purchase.
Thus, the next batch, depending solely on the number of products sold initially, ends up being too large.
Thus creating an unnecesary expense in a batch which will not be fully sold, unsold stock which will not be sold as sometimes it has an expiration date, return and storage costs, etc
This is one of the issues that are brilliantly solved by the Stipra ecosystem. For it allows companies to know where and when their products are being disposed and, thus, calculate the number of products to be produced for the next batches.
And it does it by rewarding users with points they can trade for perks. Thus, consumers are rewarded and companies get a tool to reduce costs in a new product launch.
And why? Simply because they lack post-sales data. Instead, they depending on sales data to calculate the next batch. But this is the worst type of data for a new product!
For, the fact a product was sold to a wholesaler or even to a direct consumer channel such as a supermarket does not mean it would be sold again, as it could be that the end consumers did not like the product and will not repeat the purchase.
Thus, the next batch, depending solely on the number of products sold initially, ends up being too large.
Thus creating an unnecesary expense in a batch which will not be fully sold, unsold stock which will not be sold as sometimes it has an expiration date, return and storage costs, etc
This is one of the issues that are brilliantly solved by the Stipra ecosystem. For it allows companies to know where and when their products are being disposed and, thus, calculate the number of products to be produced for the next batches.
And it does it by rewarding users with points they can trade for perks. Thus, consumers are rewarded and companies get a tool to reduce costs in a new product launch.
Με μια ματιά
https://store-images.s-microsoft.com/image/apps.48970.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.d811addd-173f-42af-a5a1-bef5453fb420
https://store-images.s-microsoft.com/image/apps.64745.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.33a28d8b-566f-4215-91af-c23b1eab3d91
https://store-images.s-microsoft.com/image/apps.62397.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.fa4f5f67-7702-4c04-b843-739e430b9f72
https://store-images.s-microsoft.com/image/apps.51035.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.c49576b4-e716-4671-bf2c-2cc0540b9524
https://store-images.s-microsoft.com/image/apps.17470.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.b07fc0fa-4523-4cb3-9c83-fc501e6a53ae
https://store-images.s-microsoft.com/image/apps.16231.877f3be1-d43d-4c81-9944-229dffba912e.500b366b-22b6-4172-ab0f-359502ba74cb.4850084a-5b44-49c6-876c-1f48704c7206