Marketing
❯
Improve Audience targeting
❯Retail - Improved Advertisement
Large Companies
Advertising with AI
For:
Advertiser
Scope:
AI uses algorithms that analyses the existing data of the user through observing the customer on multiple platforms and advertise on the basis of the prediction of what the user might like.
Goal:
Increase Revenues
Large Companies
Computer Vision - Emotion Recognition
For:
Video content creators.
Scope:
Using Computer Vision and Deep Learning for measuring emotional responses to video advertising content.
Goal:
Increase Revenues
AI solution to automatically identify false positives from a specific check for untranslated target segments by an automated quality assurance tool
For:
Customers, translation partners, end users of the translated content.
Scope:
The scope of this use case is limited to automated linguistic quality assurance
tools, but the outcome of this use case can be applicable to other areas, such as
machine translation, automated post-editing, computer-aided translation
analysis and pre-translation.
Goal:
Improved Employee Efficiency
Large Companies
Retail - Improved Advertisement
For:
Sales and Marketing departments.
Scope:
Drive return on advertising spend through optimization and automation of creative ad content.
Goal:
Increase Revenues, Automate a Business Process
Large Companies
Retail - Improved Advertisement
For:
Sales and Marketing departments.Goal:
Increase Revenues, Automate a Business ProcessProblem addressed
Online advertising campaigns with pay-per-click (PPC) models require constant optimization in order to ensure that the correct customer segments are being targeted and return on advertising spend (ROAS) is positive. Frequent manual adjustment of budget, bidding strategies, search keywords, and creative content is a drain on overall marketing resources.
Online Marketers need automation in order to allow them to run marketing campaigns with minimal intervention. This allows them to set spend and duration with confidence that their target advertising goals in terms of reach and conversion will be met, empowering them to focus on other key tasks that require their expertise.
Scope of use case
Drive return on advertising spend through optimization and automation of creative ad content.
Description
Using Natural Language Processing (NLP) techniques, a subfield of Artificial Intelligence (AI), it is possible to automatically analyze large amounts of textual data to derive sentiment from public opinion online; furthermore, this information can be further classified into themes and topics that can inform retail decisions.
The consulting company Deloitte in collaboration with the data mining organization Brandseye applied such an approach to online consumer sentiment in South Africa1. Together they analyzed 1.7 million social media posts and other online content to gauge local consumer sentiment to national grocery chains. The outcome was 5 key themes centered around price consciousness, personalisation, convenience, sustainability and governance.
The ever increasing amount of online information coupled with the large strides in AI algorithm performance makes this an increasingly common solution for retailers seeking insights about their customer base. Many software vendors and open source software exist to enable implementation.
Raw Data
AI: Perceive
optimization
AI: Understand
Optimize System
AI: Act