By 2023 Chatbots could drive sales of…

Sales From Chatbots Could Reach $112B By 2023

  • “Juniper Research estimates that retail sales stemming from interactions with chatbots are set to reach $112 billion by 2023.
  • The firm also noted that chatbot interactions are set to skyrocket from a forecasted 2.6 billion in 2019 to 22 billion in the same time frame, Retail Dive reported.
  • The report indicated that retailers can foresee cutting costs of $439 billion per year in 2023, up from just $7 million in 2019.
  • In a press release highlighting the research in July of last year, Juniper said the cost savings from chatbots would hit $6 billion in 2018″

https://www.google.com/amp/s/www.pymnts.com/news/retail/2019/chatbots-sales-artificial-intelligence-juniper-research/amp/


https://www.forbes.com/sites/blakemorgan/2017/03/21/how-chatbots-will-transform-customer-experience-an-infographic/#6029dc667fb4

The state of the chatbot market in 2019

  • The global chatbot market is expected to surpass $994 million by 2024, a compound annual growth rate of 27%.
  • In 2016, Gartner predicted that chatbots would power 85% of all customer service interactions by 2020.
  • A HubSpot survey found that 40% of consumers don’t care if they’re being helped by a person or an AI tool to resolve simple requests such as changing a billing address — as long as they get help quickly and easily.

What are the most common uses for chatbots in 2019?

1. Ecommerce

2. Instant messaging

3. Customer service

Most common types of chatbots in 2019

1. Scripted chatbots

2. AI chatbots

3. Customer service chatbots

4. Voice-enabled and contextual chatbots

https://www.clickz.com/the-state-of-the-chatbot-market-in-2019/233171/

Artificial Intelligence in Retail Banking – Current Applications

  • “One AI company offering fraud detection to retail banks is Threatmetrix, a subsidiary of LexisNexis. Their Dynamic Decision Platform purportedly improves account authentication and identity verification.
  • SAS offers a predictive analytics software called Credit Scoring for SAS Enterprise Miner. The solution is an added capability of their larger Enterprise Miner solution. The software’s machine learning algorithm sifts through a client bank’s enterprise data for all relevant information regarding the customer’s financial history. The software then uses predictive analytics to determine a customer’s credit score based on that data.
  • Chatbots can also be developed to field questions in more than one language. Finn AI offers NLP software that they claim can help banks develop and train accurate chatbots. They claim their software also features sentiment analysis, which allows the chatbot to determine whether the sentiment behind a message is positive or negative.”

https://emerj.com/ai-sector-overviews/artificial-intelligence-retail-banking/

What AI Can Teach Banks About Their Customers

Image: Getty

“Harnessing advanced analytics techniques like artificial intelligence (AI) and machine learning (ML) is fast becoming business as usual for the banking sector, with those that don’t adapt risking being left behind.

Here’s how three frontiers of AI are transforming the bank-customer relationship.

1. Machine Learning: Preventing Customer Churn

2. Natural Language Processing: Chatbots Everywhere

3. Robotic Process Automation: Reducing Inefficiencies”

https://www.google.com/amp/s/www.forbes.com/sites/crowe/2019/04/29/what-ai-can-teach-banks-about-their-customers/amp/

Why Personalization is the Natural Evolution of eCommerce

  • “Another fun fact: nearly half of US consumers say they’re more likely to make purchases with companies that personalize experiences, according to Accenture.
  • It’s estimated that by 2020, eCommerce businesses who use a smart personalization software will see as much as a 15% increase in their profits, according to Gartner.
  • Following a recent 3-month long in-home delivery pilot program launched by smart lock maker August, 90% of clients who participated later said that if the service of in-house deliveries from merchants would continue to be available, they were happy enough with it to want to continue using the service.
  • With 42% of B2C customers being influenced to purchase following a good customer service experience, according to Zendesk, it’s no surprise that eCommerce is looking to AI bots to help convert users.
  • Gartner predicted that by 2020, over 85% of all customer support communications for online businesses will be done using AI, not customer service representatives.
  • ECommerce marketers can use AI and CRM to identify and create uber-accurate personas of your users.

https://www.google.com/amp/s/www.business2community.com/ecommerce/why-personalization-is-the-natural-evolution-of-ecommerce-02193947/amp