Guided selling

Guided selling is a process that helps potential buyers of products or services to choose the product best fulfilling their needs and hopefully guides the buyer to buy. It also helps vendors of products (e.g. brands, retailer) to actively guide their customers to a buying decision and thus increases their conversion rate.

Guided selling simplifies and automates the maintenance and deployment of all knowledge that is required to analyze customer needs, define the solution, and generate a proposal to fulfill those needs. A functional definition of the solution is provided to the customer, complete with commercial aspects of the proposal, such as prices, margins, texts, illustrations, and lay-outs. In addition, the technical specification of the solution (such as bills of materials and routings) is generated for manufacturing and distribution.

Process and Practice

Guided selling is put in practice with an information system that supports the central management and maintenance of knowledge; furthermore, the system supports the use of this knowledge by web services such as online product advisors, customers, dealers and sales representatives. Such knowledge is stored in semantic knowledge models; these models are interacted with by means of questionnaires and explanations to / feedback options to product recommendations. The knowledge stored is related to functional, commercial and technical aspects of the customer needs and the possible solutions. The proposal-specific functions of guided selling are recommender systems, product advisors, product configuration, technical calculations, commercial calculations and document generation.

Guided selling-solutions are applied in the following use cases:

Guided selling does not address the internal, private, offline, or behind-the-scenes decision issues that buyers must address before they are ready to make a solution choice.

Goal and Approach

The goal of Guided Selling-solutions is to bring together potential buyer's needs and products or services that fulfill his needs in order to facilitate buying decisions. The Guided Selling-system asks questions and offers answer options that help the online-shopper to learn about and define his needs, even for complex and technical solutions. At the same time, the vendor understands step by step the refined customer needs. Guided Selling-Systems increase the shopping experience and the usability of the website since they typically offer a better access to the product assortment than done by filtering systems or free text search.


Guided Selling-Process

Guided Selling-Systems put in practice the following Guided Selling-Process to advice, convince and sell (based on the need/solution-placement dynamic):


Technology Required

Guided Selling-solutions are software systems. The Guided Selling-software allows to simulate a dialog to find out the buyer's needs. A matching technology then maps the needs on technical product details and matches the buyer's profile with the available products. Guided Selling-systems are a kind of Recommender systems. Other than Collaborative filtering that calculates recommendations based on historical data (e.g. website usage data such as "users who watched this product also watched these other products"), Guided Selling-systems rather analyse the individual user's input to calculate recommendations that best fulfil his personal needs. Guided Selling-systems thus require product information (fact sheets). Goal of this approach is to calculate objective recommendations that are based on the individual user's needs.

Boundaries

Guided Selling-Systems are different from Recommender systems in the way that statistical recommenders calculate recommendations based on usage data instead of the actual user input to a questionnaire. The advantage of Guided Selling to recommender systems is an objectively calculated product proposal and a needs-based product advice that usually has a higher quality than products suggested by recommender systems. The drawback is that Guided Selling-Systems need domain-specific knowledge about the product category whereas recommender systems (at least Collaborative filtering can work across all product categories of e.g. a website.

See also

Sources

This article is issued from Wikipedia - version of the 11/11/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.