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Guided Selling

Algonomy is positioned as a Visionary in Gartner’s Magic Quadrant for Personalization Engines

Our Customers

Leading brands across the globe have grown their revenue with Algonomy’s eCommerce personalization software.

Craft Highly Engaging Shopping Experiences with Interactive Quizzes that Generate Tailored Recommendations

Replicate the In-store Experience

Guide shoppers through the process of purchasing a product—such as a mattress, television, or ski equipment—just like a sales associate would in a physical store.

Streamline the Buying Journey

Craft quizzes that help shoppers understand the criteria for selecting the perfect product, accelerating their journey from awareness to consideration to purchase.

Help Your Shoppers Buy with Confidence

Your shoppers will make quick and informed purchase decisions, knowing that the products suggested by the experience align directly with their preferences.

Use a Simple, Merchandiser-Friendly Interface to Create Engaging Quizzes Without Developer Support

Create Customizable Quizzes

Map questions and answers to catalog elements, such as categories, product attributes, or price. Preview the experience on the dashboard interface of our guided selling platform before publishing the quiz.

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Deliver Consistent, On-Brand Experiences

Effortlessly modify colors, fonts, sizes, and the overall look and feel to align with your brand guidelines, without the need for developer support. Leverage our guided selling software now!

Test and Optimize

Leverage the built-in variation testing feature to assess and compare the performance of different quiz versions and identify the most effective one.

Collect and Leverage Zero-Party Data

Store shoppers’ quiz responses within their Real-time User Profiles, enhancing personalization across all eCommerce touchpoints, including recommendations, search results, category pages, and content.

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Other eCommerce Personalization Solutions

Explore other solutions from our end-to-end personalization platform, and learn how they enable individualized experiences at key shopper touchpoints.

Personalized Recommendations and Content

Craft tailored experiences that make every visit delightful and build anticipation for the next one.

Personalized Search and Product Discovery

Eliminate the hassle of endless scrolling, sorting, and filtering. Bring the joy back to shopping by ensuring quick, seamless product discovery.

Draw Inspiration From Our Personalization Resources

Explore our eCommerce personalization resources—best practices, case studies, videos, and more—to stay ahead of the curve.

Customers seek experience-driven shopping. Deliver on this need with Algonomy’s Guided Selling.

  • 160%

    Conversion Rate

  • 396%

    Revenue per Visit

Ready to see Guided Selling software in action? Let’s talk.

FAQs

There is no limit to the number of questions and answers in the quiz.
Yes. Images can be used as the background for the quiz and also to represent the answer options.
Yes. By default, questions are Sequential, which means that every shopper will follow the same path. However, you can designate a question as being Conditional. This creates a branch in the flow so that you can create different paths for the quiz.
Yes. You can create multiple variations of the quiz, and you can assign your visitor traffic to each variation.
You can test anything that is part of the experience. Some ideas:
  • Ordering of quiz questions
  • Different question paths
  • Styling of questions and answers
  • Styling of recommendations
  • Which strategy is used to generate the recommendations
There are two reports that provide complementary information about the performance of Guided Selling Platforms:
  1. Visitors who interacted with the Guided Selling quiz, including Conversion Rate and Revenue per Visit. This report also provides Click Thru Rate, which corresponds to the rate at which shoppers completed the quiz.
  2. The Site Analytics report provided by Guided Selling software will provide information about how shoppers engaged with the resulting recommendations.
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