Artificial Intelligence for Customer Engagement: Building a Permission-based Ecommerce Ecosystem at CXsphere

Published 20 Feb 2023
Reference 6693
Topic Marketing
Industry Market Research
Region Global
Length 21 page(s)
Summary

CXsphere, a startup in the permission-based ecommerce ecosystem space, had gained initial success with the launch of its first Artificial Intelligence (AI) driven customer engagement product. It had several clients and was generating recurring revenues. AI-driven data analytics was a new industry and CXsphere had a unique business model. It leveraged AI on the demand side, providing customer insights tomajor consumer product firms. It leveraged big data systems on the supply side, offering permission-based opportunities to individual consumers to monetize their social media, e-commerce and other digital footprints. CXsphere had raised a bridge round of funding and hoped to be cash positive and to have raised Series A funding in the coming years. To successfully raise funding at the desired price, several challenges are ahead: (1) rapidly growing its business, (2) setting CXsphere on the path to becoming a global brand, (3) maintaining a strategy of frugal innovation, (4) staying ahead of competitors by (a) getting consent from consumers to use their data and at scale, (b) providing better AI-based customer engagement / personalization services in a cheaper, faster way, and (c) growing its ecosystem and connecting more individual consumers to more brands and firms.

Teaching objectives

This case can be used in an undergraduate, MBA, EMBA or executive education course on marketing, strategy, consumer behavior, marketing research, data analytics, entrepreneurship or other related subjects. It is designed to help students understand the key issues and challenges associated with doing business in an age of data privacy, big data, artificial intelligence/machine learning, and ecosystems. It can be used to illustrate how to (1) leverage AI/ML for marketing success, (2) gain consent from individual consumers to use their data and do so at scale, (3) engage with individual consumers and leverage their data for the long term, (4) acquire corporate clients who need individual-level customer insights, (5) develop a two-side market/ecosystem from scratch, (6) create a firm and grow quickly without significant funding, and (7) approach fund-raising to support further growth.

Keywords
  • AI
  • Marketing Analytics
  • Customer Engagement
  • Customer Experience
  • B2B Marketing
  • Branding
  • Marketing Strategy
  • 2-sided Markets
  • Q12023