Predict what your customers want in the POS
The retail industry is challenged on sales in the physical stores as a result of the digital transformation. Your store’s sales are therefore dependent on, how you manage to understand the needs of the customers and provide great customer service. With NP Recommendations you have the tools to predict the behavior of the customers and through that offer individual and relevant items directly by the counter, that will ultimately increase both revenues and customer satisfaction.
Increase the customer experience with personal recommendations
By predicting the behavior of the customer, NP Recommendations can assist the Sales Assistants by giving personal recommendations to the customers, who visit your stores. More particularly, the recommendations will be shown directly in your POS, and thereby makes it possible for the Sales Assistants to provide good customer service, by recommending items that Machine Learning has analyzed will be of the customer’s interest.
NP Recommendations offers three different types of recommendations:
- Frequently bought together-recommendations
This type of recommendation contains a suggestion of specific products, that are likely to fit and be purchased with the current or former transactions.
- Item to Item-recommendations
Here items or services that other customers have been interested in are recommended, besides the products, that is purchased.
- Personalized user-recommendations
This recommendation is the most personal, as the items or services that the customers could be interested in is emphasized on the basis of previous customer behavior.
How NP Recommendations with Machine Learning works
When a customer visits one of your stores and wishes to purchase an item, the Sales Assistant will scan the item into the POS system. The items that fit the already chosen item will be shown directly on the screen on the basis of consumer behavior research with Machine Learning. The Sales Assistant, therefore, gets the opportunity to offer an extra service by recommending an item, that actually could be of the customer’s interest.
Boost your business without hard work
Retail companies that want to increase both cross- and up-selling, can easily benefit from NP Recommendations in Microsoft Azure Machine Learning. The system does not require expertise in Artificial Intelligence, and you can easily and quickly get started with just a few lines of coding. The recommendations function is a self-driven machine, that uses filters and algorithms to predict what the customers want and thereby increase customer experience. Your items or services will, therefore, present themselves in the POS for those customers they are especially relevant to.
Integrate your recommendations
Benefit from integrating your customer recommendations in Dynamics 365 Business Central and get an overall picture of your POS system, stock, orders and statistics in the same solution. By integrating NP Recommendations in Business Central you guarantee that the items recommended to the customers are in stock. Furthermore, you can build statistics of your revenues and see the NP Recommendations’ impact on your business.
With NaviPartner’s NP Retail 2017 you receive ERP and POS in one – and as a new feature, it also contains the recommendations function, NP Recommendations. With the free implementation in NP Retail 2017, it is possible to buy NP Recommendations packages with 100,000 inquiries at a time, in order for you to easily increase sales and customer satisfaction.
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