Harnessing AI

with Einstein Recommendation Builder

Salesforce Einstein Recommendation Builder is a powerful tool that combines the power of AI and big data to make intelligent recommendations that drive sales and improve customer experiences.

Transform your Business with Custom AI Models

Craft your recommendation models with Salesforce Einstein recommendation Builder. Even without a data scientist background, you can create custom AI models tailored to your unique business needs. Create personalized recommendation models that cater to your unique business needs and leverage the power of AI to plan and strategize more effectively.

Data-Driven Decisions Made Simple

With Salesforce Einstein Recommendation Builder, you can create personalized recommendation models and offer customized recommendations to your customers based on their behaviour and history. This empowers businesses to save time and resources while improving customer engagement and satisfaction.

Seamless Integration, Powerful Results

Next Best Action suggests personalized actions to users using flows, strategies, and recommendations. These recommendations can be displayed on different pages, such as Lightning pages in Salesforce org, Experience Cloud sites, or external sites, improving customer engagement and productivity.

Recommendations to Actionable Insights

Einstein Recommendation Builder empowers businesses to make data-driven decisions using personalized recommendation models. By analyzing customer behaviour and purchase history, businesses can offer tailored product recommendations, saving time and resources while improving customer engagement and satisfaction.

Secure & Trustworthy AI

We understand that your data is precious. Salesforce Einstein recommendation Builder is designed with robust security measures, ensuring your data remains secure and isolated from public exposure while being used to generate vital recommendations. Salesforce’s commitment to ethical AI practices ensures your AI models are influential and trustworthy.

Our AI Approach

  • We'll work closely with your team to understand your business, data, and goals. By defining clear objectives for your recommendation needs, we can shape how Einstein Recommendation Builder can best be utilized for your business.

  • Next, we'll thoroughly assess your data quality and volume. Our team will ensure the data is clean, relevant, and substantial enough for effective recommendation analysis. We'll also address any data skew or imbalance issues to ensure the accuracy of recommendations.

  • We'll design a custom solution for your business using Einstein Recommendation Builder, based on your goals and data assessment. This includes selecting the right objects, such as recommendations, recipients, and interaction objects, and ensuring their accuracy and relevance for effective predictive analysis.

  • Our team will then build and train custom AI models in Einstein Recommendation Builder. We'll ensure the models align with your business objectives and fine-tune them for optimal performance.

  • We dive into the performance evaluation and optimization of your custom AI models in Einstein Recommendation Builder. We'll use the scorecard to measure the quality of recommendations and predicted lift, which tells us how much better our recommendations are than just suggesting the most popular items. If we're not happy with the results, we'll fine-tune the segments and settings and run the build again until we achieve optimal performance. This continuous improvement approach ensures that your business is always benefiting from the most accurate and effective recommendations.

  • Once the recommendation quality meets our satisfaction, we'll integrate it with the Next Best Action Strategy to surface the recommendations for your business.

  • Finally, we understand that adopting AI-driven recommendation processes can be a significant shift for some teams. We'll provide comprehensive training to your team, ensuring they know how to use and interpret the recommendations. We'll also assist with change management, helping your organization smoothly transition to this new approach.

  • After the solution is deployed, we’ll continue to provide support and answer any questions that may arise. We aim to ensure that you're maximizing the potential of Einstein Recommendation Builder and continually driving value from your investment.

HealthCare Usecase Demo

We've created a system using Einstein that provides recommendations for patients with a fever based on their current medical condition. The system considers factors like the patient's age, medical history, and other relevant health information to make personalised recommendations.

Schema and Objects

  • There are three main Objects: Recipient, Recommendation, and Interaction Object.

  • The patient is the Recipient Object that will receive the recommendations.

  • Precaution is the recommended Object that will be recommended.

  • Precaution Undertaking is the Interaction Object between the Patient and Precaution.

Join the growing number of businesses leveraging Salesforce Einstein Recommendation Builder to drive their success. Start making smarter, more informed decisions today with the power of personalized recommendations. 

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FAQs

  • Einstein Recommendation Builder is a tool within Salesforce's AI platform, Einstein that allows businesses to create personalized product or content recommendations for their customers. Leveraging AI and machine learning helps enhance the customer experience and boost sales.

  • Einstein Recommendation Builder uses machine learning algorithms to analyze customer behaviour data, order history, web browsing data, and other factors. It then predicts and recommends the most suitable products or content for each customer.

  • To use Einstein Recommendation Builder, you need a Salesforce org with Einstein enabled and sufficient customer and transaction data to train the AI models.

  • The accuracy of Einstein Recommendation Builder largely depends on the quality and quantity of data available. The more customer interaction and transaction data it has, the better it can learn and make accurate recommendations.

  • Einstein Recommendation Builder is deeply integrated into the Salesforce ecosystem, allowing it to utilize your Salesforce data directly. Its AI models are self-learning and improve over time, making it a dynamic and robust tool for personalized recommendations.

    • Lack of data.

    • Data quality issues.

    • Incorrect configuration.

    • Lack of monitoring.

  • No, Einstein Recommendation Builder is designed to be user-friendly and does not require coding skills. However, understanding how to interpret and apply the data and recommendations might require some training or background in data analysis.

  • Einstein Recommendation Builder uses proprietary algorithms and currently does not support the use of custom algorithms. However, you can customize the factors and criteria used for recommendations.

  • Einstein Next Best Action (ENBA) and Einstein Recommendation Builder (ERB) are two Salesforce AI solutions that can be used to improve the customer experience. ENBA can identify the best actions to take with customers, while ERB can be used to recommend specific products or services to customers.

    When ENBA and ERB are used together, they can provide a more personalized and relevant customer experience. For example, ENBA can identify customers most likely to be interested in a particular product or service. ERB can then recommend that product or service to those customers.

    This combination of ENBA and ERB can help businesses to:

    • Increase customer engagement and satisfaction

    • Boost sales and revenue

    • Improve customer retention

    • Personalize the customer experience

    • Make better business decisions