Experian has recently published its latest ‘Global Insights Report’. The report is focused on how businesses are incorporating machine learning and artificial intelligence into everyday operations and investments.
Experian’s survey finds that consumers are online 25 percent more now than they were before COVID-19. Much of this activity is dedicated to online shopping. The study also shows that consumer loyalty is down 6 percent from last year (to 61%).
How are businesses reacting to this shift in consumer focus? As a result, more companies appear to be shifting their investments towards data automation, machine learning, and artificial intelligence to create a convenient and secure online experience. These technologies are also being harnessed to help to improve customer retention.
One way by which retailers attract consumers is by offering interest only deals or ‘buy now, pay later’ offers. The availability of these details rests on consumers having a good credit rating. Here the report also finds that confidence in artificial intelligence and cloud-based credit risk decisioning is trending up.
In particular, there has been an 81 percent increase in the use of advanced analytics and artificial intelligence (and this is running higher than in 2022). Furthermore, there is a similar increase with on-demand, cloud-based decisioning (which is also trending higher than with the previous year).
It is also noticeable from the findings that the adoption of artificial intelligence and machine learning continues to grow, and both are showing similar increases in application. Artificial intelligence is up 74 percent, climbing from 69 percent last year and machine learning is up 73 percent, climbing from 68 percent last year.
These technologies assist retailers with optimizing customer experiences, forecasting, and inventory management.
The survey also identifies that 7 out of 10 businesses say they are frequently discussing the use of advanced analytics and artificial intelligence in order to better determine consumer credit risk and collections.
Good interpretation of data rests of well-designed and executed data analytics: Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics. Notably 76 percent of businesses are improving or rebuilding their analytics models and 50 percent of businesses are exploring new data sources.
Data analytics confer an advantage where firms successfully use data insights to discover consumer spending and browsing trends, predict goods appeal outcomes, and to make better retail business decisions
