AI in digital commerce is generally considered a success, says Gartner

By | | Deep Genius AI News
Categories: Marketing,
Editor is editor in chief of Deep Genius AI News, with a passion for how technologies influence business and several Mobile World Congress events under his belt. Editor has interviewed a variety of leading figures in his career, from former Mafia boss Michael Franzese, to Steve Wozniak, and Jean Michel Jarre. Editor can be found tweeting at @Editor_T_Bourne.

A survey by research firm Gartner found that the use of AI in digital commerce companies is usually considered a success, with 70% of the organisations claiming very, or extremely successful, implementation of the technology.

A total of 307 digital commerce organisations were surveyed for the study. These companies are currently using or piloting the technology to understand the adoption, value, success and challenges of AI in digital commerce. Organisations participated in this study were from the US, Canada, Brazil, France, Germany, the UK, Australia, New Zealand, India and China.

Among the respondents, three-quarters said that they are seeing double-digit improvements in the outcomes they measure. Customer satisfaction, revenue, and cost reduction are the most common metrics used to measure the business impact of AI. For customer satisfaction, revenue and cost reduction specifically, respondents cited improvements of 19, 15 and 15%, respectively.

Moreover, the study also reveals lack of quality training (29%) and in-house skills (27%) are the top most challenges in deployment of AI in digital commerce.

In order to overcome difficulties while implementing AI, organisations must consider following the ‘four pillars of marketing success’, according to Brian Baumgart, CEO of Conversion Logic. These are data, systems, algorithms and people:

  • Data: the organisations should be able to aggregate and normalise data into one context. This means that everything is a line probability, all the time variables are the same, and everything has generally a comparable meaning of time and place
  • Systems: Parties, such as marketers or people or vendors who support them, should have a flexible architecture. The organisation should be able to add new data sources from different places easily, quickly, and readily
  • Algorithms: The system as a whole should be modular and scalable. By this, it means that the process of plugging in different algorithms and different data sources to do different things should be easy
  • People: Having right people at hand, or expertise, is utmost important, as these are the people who are driving all of this