Visenze received another $20M in funding. Here’s a “Crib Sheet” post that I wrote on them in 2017.
Additionally, here are some key take-always from today’s news.
- “Artificial intelligence (AI) in retail is having a moment. Spurred by growth in automated merchandising, recommendation engines, and customer behavior tracking, spend with respect to AI-driven commerce services is expected to top $8 billion by 2024, research firm Global Market Insights reports. And according to the McKinsey Global Institute, said services will impact between 3.2 percent to 5.7 percent of global retail revenue.
- After three years of steady growth (200 percent) that saw the number of users conducting searches with its products exceed 300 million (and search volume surpass three million queries a day), ViSenze is raising venture capital
- ViSenze — which was spun out from the National University of Singapore’s Next research center in 2012 — claims its infrastructure can index and process of “billions” of images, and generate search results in less than a second for newly uploaded product images (and less than 200 milliseconds for existing images).
- That scalability — along with computer vision models trained continuously to improve recognition accuracy — are the reason its customers see 50 percent higher click-through rates and up to 5 times higher conversion rates, ViSenze contends.”
“The ability to quickly create ads is crucial for a merchant like TechStyle given that its product catalog is regularly changing. Now, roughly 30% of the retailer’s ads are created via the Smartly.io platform. That’s helped boost the retailer’s click-through rate on Facebook ads to nearly 1.0%, roughly double its previous 0.5% rate.”
“According to Gartner, artificial intelligence is the technology that will have the most impact on commerce in the future. Their analysts say AI will predict and initiate at least five percent of digital commerce orders by 2022.“
“Google’s Cloud Auto ML service, which doesn’t require any coding experience to use (it’s free to try), was trained to find Waldo by looking at dozens of pictures of the cartoon, which were all found on Google Image Search.”
Sen. Bernie Sanders. Photo: Sean Rayford/Getty
“What he said: Right at the halfway mark of the 10-minute video, Sanders took a stance on the future of work. “I’m running for president because we need to understand that artificial intelligence and robotics must benefit the needs of workers, not just corporate America and those who own that technology,” Sanders said.”
© PESHKOVA – ADOBE STOCK
- “So anyone interested in CX trends should pay close attention to the latest Customer Experience Index report from Forrester Research. The annual survey asks nearly 120,000 U.S. consumers to rank 287 brands across 19 industries, focusing on how their company-specific experiences impact brand loyalty. The alarming surprise was that the aggregate measurement of customer experiences failed to improve, with more brands than ever ranked “mediocre.” Just 37 brands rose in the rankings; the remaining 250 stagnated or declined.
- With the advent of artificial intelligence (AI), companies can now improve CX by learning more about the customer and anticipating their needs. Many CX-focused brands are deploying artificial intelligence technologies strategically at key customer touch points.
- To illustrate what that looks like in practice, we’ve assembled five examples of AI-powered CX from five different industries—showing that 5-star customer experiences can be just an algorithm away for forward-thinking companies:
1. In retail, AI-enabled personalization unlocks access to the 1% customer.
Data shows thatthe top 1% of a retailer’s customers are worth 18x more than its average customer.
2. For a global bank, AI builds trust and loyalty.
Its approach was to leverage data intelligence into entirely new forms of customer contact.
3. For one airline, new data intelligence drives CX innovation.
Seeking to better understand its customer and, ultimately, improve its mobile app experience, the company deployed an AI and machine learning data analytics system that provided insight into customer behavior across digital and offline channels.
4. In entertainment, AI battles ticket bots.
Ticketmaster turned to AI to rewrite the rules using a machine learning system called Verified Fan
5. For one luxury hotel brand, new insight required new AI.
Until the luxury hotel brand Dorchester Collection did just that, creating a custom AI analytics system that is essentially a giant focus group operating continuously in real time.”
- “2019 is the year in which automation technologies take centre stage, Forrester Research predicts.
- In addition, Forrester predicts that intelligent automation (IA) will replace one-fifth of service desk interaction, with automation eliminating 20% of all such interactions by end-2019.
- However, the automation economy is also expected to create new jobs such as that of bot masters, operational employees who handle exceptions and escalations, and who manage the performance of the bots.”
Facebook’s chief AI scientist Yann LeCun
“The International Data Corporation indicates global spending on AI systems is expected to hit $US77.6 billion in 2022, more than tripling the $US24 billion forecast for 2018.
A key element in advancing the field of artificial intelligence, particularly when it comes to deep learning, will be ensuring that there’s hardware capable of supporting it.
- Machines have to get much better at power consumption in order for AI to improve.
- We’ll continue seeing AI advancements in smartphones in the near term before improvements appear elsewhere.
- Giving machines “common sense” will be a big focus for AI research in the next decade.”
- “Dr Genevera Allen, associate professor of statistics, computer science, and electrical and computer engineering Rice University in Houston, Texas has discussed this topic
- She warned that researchers in the field of machine learning have spent so much time developing predictive models that they have not devoted enough attention to checking the accuracy of their models,
- The problem is that machine learning techniques do not have a way to say “I don’t know” or ‘It’s not clear.'”
“Banks are equally capable of using their extensive knowledge and data about customers to aggregate it in digital channels, but it needs to be made contextual.
Banking has its own success stories, but these tend to come from the disruptors. Take the example of Revolut, which doesn’t believe in branches and invites allows new customers to open an account within minutes via their mobile. Since launching in 2015, it has been particularly successful in acquiring new clients among a highly-educated younger generation, who are attracted by features such as cryptocurrency exchange and peer-to-peer (P2P) payments.
A more sophisticated segmentation method, psychographics, helps banks define them based on their personalities, lifestyles and social classes; thus providing a better understanding.
It takes time, effort and significant investment to make the changes needed, but tech companies are ready to help the banks move away from their legacy systems. If they fail to make that move, Amazon and Google are ready and able to move into their territory.”