Product Recommendation Engines to Improve Customer Relationships.

 
Businesses are always looking for the secret to success. However, the truth is that the key to success is no secret. Customer service is the answer. Given that approximately 70% of buying decisions are made based on how clients feel they are being treated, superior customer service has the power to turn any company into an industry juggernaut.

That said, there is more to providing exceptional service than just being friendly. Customers are looking for solutions, and unless a company can provide those solutions, the customer isn’t going to stick around. Additionally, many customers don’t know exactly what kind of solution they want and choose to rely on the expertise of the business itself. Businesses that can predict customer needs and supply effective solutions can ensure that their client base is always satisfied.

Unfortunately, customers are not always easy to read, particularly when there are a lot of them. For these situations, successful businesses rely on product recommendation engines.

What are product recommendation engines?

Product recommendation engines, often referred to as predictive offers or next best offers, are a method of providing personalized service to every single client. An effective product recommendation engine gives marketers the power to analyze customer data, and then use the results of that analysis to create accurate, individualized client profiles. These profiles show marketers exactly what kind of content and solutions a specific customer might be interested in.

To understand how recommendation engines work, it’s important to understand some of the key elements inherent to recommendation engines: algorithms. These sophisticated algorithms take into account massive amounts of customer data, including purchase history, preferences, and direct feedback. The algorithm employs set processes by which customer data is automatically refined into accurate recommendations. The system can then automatically deliver the correct solutions to individual clients.

Product recommendation software delivers content based on estimates of what the customer wants or needs. Simply put, it intelligently anticipates the intent of the customer, and then provides a unique recommendation based on what has been observed. Additionally, software that operates out of the cloud is more cost effective, more reliable, and easier to integrate, and is drastically changing the industry.

What can superior product recommendation do for your business?

The right product recommendation tool gives businesses the power to use client behavior to optimize their own customer service efforts, while also increasing the potential ROI of their marketing efforts. Predictive recommendations help retailers deliver the right offer at the right time to the right shopper, resulting in a likelihood of conversion and more money spent per transaction. A study by Barilliance suggests that up to 31% of ecommerce site revenue is generated from personalized product recommendations, and McKinsey reports that as much as 35% of Amazon’s revenue is generated by its recommendation engine.

This is because intelligent product recommendation also allows for natural, logical upsell and cross-sell opportunities. Clients, through their behavior and history, demonstrate interest, and the product recommendation tool automatically pairs that behavior with the right suggestions. Small transactions become larger ones, and clients who might not have been on the path to make a purchase suddenly find themselves interested in doing so.

Predictive offers take selling to the next level. By using “next best offer” or “next best action” predictive analytics to anticipate consumer spending habits, marketers can create hypertargeted campaigns that personally connect with audiences and individuals, alike.

Personalization is perhaps the most obvious advantage to companies and customers, but it’s not the only one. Recommendation engines also reduce costs associated with targeted client marketing. Harvard Business Review reports that personalization can deliver five to eight times the ROI on marketing spend and can improve sales by 10% or more. Automated recommendation also frees up marketers and sales teams to focus their time and effort on other, more critical tasks.

What is most important when selecting a product recommendation engine?

Of course, knowing how product recommendation can improve a business is only part of the issue. Companies that want to get the most out of product recommendation tools need to know what to look for. Whether the business in question is basic retail, strictly B2B, or something in between, here are five important factors to consider when selecting a recommendation engine solution:

  • Ease of integration
    Customers aren’t the only ones who deserve a personalized service. Product recommendation engines need to easily integrate with your existing systems, like ecommerce platforms.

  • Usability
    Employees need a recommendation engine they can not only depend on, but also easily operate. Easy-to-use controls, clear reporting functions, and multichannel support options help ensure that users are getting the most out of the solution.

  • Effective automation
    Automation is a key part of the whole product recommendation engine idea, but some tools employ automation better than others. Effective recommendation engines automate nearly the entire process, collecting data, analyzing it, and then delivering recommendations directly to customers, all automatically. The less often a marketer has to step in, the more time, effort, and money businesses can save.

  • Machine learning
    A predictive intelligence that is only as effective a year from now as it was on day one isn’t actually all that intelligent. Instead, reliable recommendation engines should be able to improve as they go. Machine learning allows predictive software to use the data it gathers to enhance its own effectiveness, meaning that the accuracy of its recommendations is always increasing.

  • Real-time processing
    As retail customers make purchases, browse products, and provide feedback, the recommendation tool should be constantly updating and refining. It doesn’t do much good for a predictive system to only update itself once or twice a day, if it means missing out on the right time to suggest the right offering to a client who is ready to upsell or cross-sell. Additionally, by maintaining a real-time updated database, recommendation tools ensure that all authorized users access the same accurate data.

Salesforce CRM optimizes product recommendation.

Effective suggested selling depends heavily on accurate analysis of customer data, which is why it’s so important to rely on a solution built on the best CRM available. Salesforce CRM has long been recognized as the world leader in CRM, and with the introduction of predictive intelligence across marketing, sales, commerce and service, Salesforce CRM the smartest option available for retail..

Salesforce takes into account all available customer data, including goals and important life events, to provide customers with a richly personalized journey. Automated tasks, including client tracking, analysis, and reporting help ensure that customers are always being guided along the path to brand advocacy, and marketers and sales teams are always on top of that progress.Show your customers how much they mean.

Studies have found that the click-through rate of personalized recommendations is twice as effective as the click-through rate of non-personalized recommendations. But beyond even that, the real impact of the recommendation engine tool is that it strengthens the relationships between companies and their customers. When businesses are able to show their clients just how important they are, sales are sure to follow.

After all, it’s no secret that customers want to be valued, and now, with Salesforce, customers will be.

Salesforce for Retail has the CRM solution you’ve been looking for.

Contact us to talk about the latest Salesforce retail solutions, and let us help you set up a strategy to connect with your customers like never before.