AI & ML, Personalized Recommendation Engine, Retail/CPG
Time to ‘Personalize’ your Business
Jun 05, 2020
Personalization is all the rage these days.
In a world where almost everything we do and buy can be tweaked to meet our exact specifications, most companies want to create a unique customer experience. Thus, the ability of an organization to personalize interactions for their customers creates a unique competitive advantage. It adds a classy touch to customers by providing a unique, tailor-made and enhanced user experience that extends across industries; increasing customer satisfaction and revenue exponentially.
There are several tools enterprises can use to analyze data and come up with recommendations for adding these personalization touchpoints. With the power of machine learning, organizations can leverage recommendation engines that use algorithms to filter user data and provide the most appropriate recommendations. For instance, according to a report by Mckinsey, 35 percent of what consumers purchase on Amazon and 75 percent of what they watch on Netflix come from product recommendations based on such algorithms.
At its core, personalization is based on engines that use algorithms to come up with the most appropriate recommendations, using the huge amount of customer data they are able to collect. The artificial intelligence engine then provides recommendations on the basis of popularity, classification, and collaborative filtering. Though Personalization can positively affect revenue and customer experience, getting it right is a challenge. It is cumbersome and inefficient if not done right.
That’s where we come in. By using various tools and technologies in the cloud, we can provide cutting edge recommendations and solutions to get the Personalization right.
Quantiphi, Customers & Personalization
As an organization, you may have substantial sales potential. But without a recommendation system, your customers might be unaware of your existence. This could be the reason why your customer engagement might be low and your content performance underwhelming. Our recommendation system will provide customers with opportunities to meaningfully interact with your platform. This would foster a sense of confidence in your brand and help aid in conversion.
Your company’s content cupboard might be well-stocked but if your customers can’t find what they’re looking for, it’s a futile experience. Therefore, real-time recommendations are of the essence. The ability to analyze your customers’ current intent, their search context, or their mood — with significant accuracy — is what we offer.
With such a wide array of content, you can maximize sales by recommending content matching your customer’s taste. Our models factor in this concept, which can lead to better customer conversion and increased sales. With a wide customer pool, preferences overlap and inter-user comparisons provide a better approach to recommendations. Our models recognize this congruity between user tastes & preferences and recommends content that both surprises and delights customers.
What good is a recommendation system that cannot be easily incorporated into your framework? Seamless integration and ease of use for recommendations should be top priorities while implementing a recommendation system. Quantiphi’s recommendation engine framework synchronizes smoothly with your existing environment and provides a hassle-free experience.
Quantiphi utilizes AWS Personalize, along with other tools, to better align customers and their preferred products.
Some of the advantages of using AWS Personalize include:
Machine learning. The tools ingest data in the form of historic customer activity, customer demographics, and clickstream data. This gives rise to recommendations in real-time based on current customer search context and intent.
Data loading & training. Required only once to train multiple solution versions using different predefined recipes.
Automated machine learning ability. Takes over the onus of developing machine learning models.
Custom data. It gives customers the ability to select the right model, depending on the kind of data sets available.
Easy integration. Fits into customer applications and websites with ease. Recommendations are generated via simple API calls.
We leverage our machine learning expertize in conjunction with AWS Personalize to create algorithms that are unique to your business. We deploy state-of-the-art recommendation engines across media and retail industries. This drives sales by increasing conversion, boosting revenue and engaging customers like never before.
With Quantiphi, you get the perfect combination of data insights and intelligence to leapfrog the competition and push your brand into the mainstream.
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