Applications Of Artificial Intelligence In B2B Marketing Posted on : Jan 05 - 2018

The onset of the fourth Industrial Revolution, with its technological innovations and advancement, has forced industries and businesses to review and reinvent their processes to avoid becoming obsolete. Although this has caused massive disruption, the resulting opportunities (especially those created by the software and tech industry) are well worth it.

One of the more recent developments is the increased use of AI in B2B marketing applications. Although digital marketers have already begun exploring the benefits of machine-learning algorithms, the opportunities for implementing AI in B2B marketing are yet to be exhausted. Some of the areas that still need to be explored include blockchain, predictive analysis, personalization, propensity modeling and lead scoring. Let’s take a look at how AI can be applied in these areas.

Blockchain

One of the more recent standards being developed for use in the B2B industry is the blockchain. Most supply chains involve the buyer, seller and a logistics provider; the information flow between these entities is usually point to point or one way through XML-based or EDI messages. Each party maintains its own view of the information flow, and through the use of mechanisms such as acknowledgment documents, they attempt to synchronize information flow within the supply chain. However, true synchronization does not exist since there are complex rules for all kinds of reconciliation and exception handling owing to the flow of information being one way or point to point.

Blockchain for B2B networks can be viewed as a form of distributed ledger that delivers an auditable and secure record of events for improved visibility of the information flow within supply chain networks. It allows multiple parties to view information, which is stored in a decentrally owned and immutable data store. Since individual parties aren’t able to doctor the data, multiple parties coordinating on a digital marketing campaign can reconcile third-party data obtained from the blockchain with the first-party data that is being tracked. View More