For more than 60 years, artificial intelligence (AI) has been the white whale of technology promises. Dartmouth math professor John McCarthy coined the term in 1955, and ever since, one phenomenal claim after another has been tossed onto the discard pile. Finally, AI has found its niche in digital commerce. Giants like Amazon and Google have been its champions, but companies of all sizes can and should employ AI immediately.
AI’s great gift is machine learning (ML) — learning without being explicitly programmed in that process by humans. Recently, ML has improved, becoming far more accessible. This is a key improvement because the more learning that happens, the more intelligent the process.
Two major areas where AI has taken hold is in “perception and cognition.” This includes a wide array of problem-solving, and voice and image recognition that consumers use daily (e.g., Siri, Alexa, Google Assistant for voice, and Facebook for tagging faces in images). According to the Harvard Business Review, companies employ “ML to optimize inventory and improve product recommendations, [to] predict whether a user would click on a particular ad, [and] to improve customers’ search and discovery process at a Brazilian online retailer. The first system increased advertising ROI threefold, and the second resulted in a $125 million increase in annual revenue.” These are serious results that every company needs to pay attention to.
Improved searches: ML studies each new interaction to better understand what a customer is searching, delivering more relevant results.
Personalization and recommendations: By gathering data (e.g., a social media post), AI makes specific recommendations based on that content.
Improved customer interactions and relations: Rather than blasting annoying, irrelevant advertising, AI customizes what and how often customers want to hear about their preferred brands. Through voice recognition, CRM systems answer customer questions, problem solve, and report leads to sales teams.
Dynamic pricing: AI can tweak pricing in real time, depending on the market and consumer behavior.
Targeting potential customers: With 33% of marketing leads left without follow-up potential conversions are lost. With facial recognition on-site (in store), AI gathers data about an individual’s potential product interest.
Driving localization: Through AI’s natural language capabilities, businesses can drive local recommendations.
Managing fake reviews: 86% of purchases are adversely influenced by negative reviews; some of these bad reviews are planted by a company’s competition (astroturfing). ML boosts verified customer purchase reviews while giving preference to those marked as helpful by other users.
It’s easy to build the right AI engine for a company’s digital commerce needs. Making the technological investment today could make your solutions work far better tomorrow.
How to provide the best service using the requirements testing? A basic and mandatory process for all Opinov8 projects. Find out how you can achieve this in your QA team.
How to provide the best service using the requirements testing? A basic and mandatory process for all Opinov8 projects. Find out how you can achieve this in your QA team.
