Increase conversions with recommendation engine services

Recommendation Engine

Predict what users want before they are aware of them. Use AI and data to engage and convert. Express Analytics’ best recommendation engine services are simple to set up and involve interest-specific, popular, and frequently seen and bought-together items. Use artificial intelligence for quicker data processing and customer response

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Express Analytics’ Approach

Our Expertise
Our Recommendations Engine Software works both on Content-Based Filtering & Collaborative Filtering. This allows you to recommend products based on the same category, the same price, similarly bought products & demographic-based recommendations.
What benefits can you get from Recommendation Engine Module?

  • Increase Average Order Value

    • Whether you want to sell combination products or just add a totally new product, increase the Average Order Value with our advanced recommendations.
    • Recommendation engines can rely on AOV data to dynamically recommend promotions that are impressive without ruining profitability.

  • Deliver more Engaging content

    • Deliver relevant product recommendations by analyzing the customer’s current site usage, previous browsing history and other metrics.
    • They are crucial for online stores with huge product catalogs where consumers can get flooded by the varieties of options and leave.
    • Offering suitable product recommendations relies on having authentic data that the engine can consistently inspect.

  • Improve User Experience

    • Reduce bounce ratio by recommending the right products so customers don’t have to search repeatedly and improve the user experience.
    • With our services, you can see an increase in 15% revenue and a 20% increase in productivity with suitable recommendations.

  • Drive Higher Profits

    • Smart recommendations help to upsell and cross-sell thereby increasing basket size
    • Consistently test and improve your recommendation algorithms to increase their productivity eventually, ensuring your recommendations are valid and fruitful in achieving profits.
Our Process

  • Understanding and acquisition

    We simplify the data gathered from numerous sources, such as sensors, apps, cloud servers and streamlining applications to know where, when, what, and how it can be shown, inspected, and stored in data lakes.

  • Preparation and conversion

    At the time of data preparation and transformation, we keep, curate, clean, and convert the data form when needed to identify the invisible insights and for analytical querying.

  • Modeling and analysis

    Inspect user profiles to find similarities between products or users for content-backed recommendations.

  • Reporting and visualization

    Our reporting and visualization services help you integrate, represent, and display a unified view of data in an eye-catching way.

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Recommendation engines help you to

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  • Increase revenue

  • Reduce workload

  • Predict business dynamics

  • Increase Cross-selling and Up-selling

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What Questions Does the Recommender System Resolve for Clients?

  1. Which products should we recommend to users?
  2. What type of recommendations drive the most sales?
  3. How do we personalize the user experience?
  4. What are users likely to purchase next?
  5. Which products are commonly bought together?
  6. How can we engage new users with limited data?
  7. How do we keep users engaged over time?
  8. How can we increase the average order value (AOV)?
  9. Which recommendation strategy works best?
  10. How do we improve product discovery for users?
  11. What times or channels are best for recommendations?
  12. Which users are at risk of churning?

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