Modern ecommerce is extremely complex. Thousands (or millions) of consumers take dozens of actions on big sites during each visit, interacting with products and content in lots of ways. That makes optimizing conversions across ecommerce sites a real challenge.
What conversion rate optimization tests do you run first? How do you process and implement results in a timely fashion? How do you reliably define and improve the consumer journey at scale?
If worldwide conversion rates are any indication, says AI-powered company DXi, humans aren't great at answering these questions. The company points to conversion rates of about 2-3% on average globally—nothing to write home about.
As a result, it says north of $4 trillion in merchandise will be abandoned in shopping carts this year, and 63% of that is potentially recoverable.
DXi has developed an AI-powered solution that uses machine learning to boost conversions across both ecommerce and brick and mortar businesses. We talked with founder and CEO Srinivas Kilambi to learn how DXi works.
In a single sentence or statement, describe DXi.
DXi measures, quantifies, and improves the digital experience into a single score using a proprietary machine learning based algorithm, correlates that score to conversions, and improves it using 20+ AI and machine learning algorithms.
How does your company use artificial intelligence (i.e. machine learning, natural language generation, natural language processing, deep learning, etc.)?
We have a proprietary formula to convert subjective user engagement into an objective score and then use machine learning, natural language processing (NLP), and deep learning to improve the score and, through it, conversions.
What do you see as the limitations of artificial intelligence as it exists today?
AI's effectiveness depends a lot on the quality of the training set and classification methodology. The technology is also not always easily usable or understandable for general marketing and sales executives.
What do you see as the future potential of artificial intelligence in marketing and sales?
We see the promise of AI as going from today's diagnostics to predictions—all the way to personalized prescriptions.
Who are your ideal customers in terms of company size and industries?
Our ideal customers are B2C companies. Specifically, ecommerce, both brick and mortar and online retail, and e-hospitality, with annual revenues greater than $10 million.
What are the primary use cases of your solution for marketers and sales professionals?
Use cases include: conversion improvement; win-loss analysis; relevancy targeting; engagement benchmarking; goal setting; behavior clustering; forecasting, understanding the customer journey; and more.
What makes your company different than competing or traditional solutions?
We are very unique in that we take the complete user/visitor journey map into consideration and not just the purchasing.
We measure and quantify this subjective UX into an objective score, which no one does. We then correlate this score to conversions and improve them through personalized ML insights and recommendations. We've even been able to use the same methodology for brick and mortar retail, with great success.
To the best of our knowledge, no one does this.
Any other thoughts on AI in marketing, or advice for marketers who are just starting to explore the possibilities of AI?
We see the use of artificial intelligence and machine learning as absolutely mandatory for success when it comes to customer and visitor data.
Company Spotlight: DXi
- CEO: Srinivas Kilambi
- Funding: $850,000
- Resources: Blog
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Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).