Product 2.0 Recommendations Overview

This upgrade for Clover Club provides expanded capabilities for sales teams in the context of product recommendations during the quoting process. It details several enhancements:

• Sales teams now have increased options to substitute similar products or add complementary products during quoting.

• There is the ability to add alternative products from a specific brand, which can be used to promote private label brands.

• The use of Natural Language Processing AI has enabled new scenarios where products can be analyzed based on text, category, and numerical attributes.

• Product attributes can now be compared across 15 languages, which improves the identification of similar products.

• Sales teams can leverage improved up-sell and down-sell opportunities by recommending products with higher unit margins or lower prices.

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The ultimate goal is to ​increase quote conversion (by better matching customer needs), increase order size (by offering relevant products) and promote related products (can be manually defined).

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Enhancements for Clover Club

Main feature is including Product Similarity enabling new Product Recommendations

Supported Recommendation Types:

Already part of v1, but with new names:

• “Frequently Purchased”: bought earlier by the customer

• “Others buy”: customer segment recommendations

• “Bought together”: products usually bought together

New for v2.0:

• “Similar products” based on product similarity

• “Similar from another brand”: e.G. pushing private label brands

• “Up-sell” => product similarity + filter on higher unit margin

• “Down-sell” => product similarity + filter on lower unit price

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enhancement in Clover Club is the addition of several Product Similarity recommendation types. These new recommendation types have the ability to maximize sales opportunities by offering tailored alternatives.