Actionary Research

The customer service technology landscape is rapidly evolving as vendors seek to deliver more comprehensive Customer Experience (CX) solutions. Despite the promise of an enhanced service value proposition, many offerings fail to meet expectations due to their complexity, scope, and developmental immaturity. This research explores the changing dynamics within the customer service vendor market, highlights the key challenges faced by both vendors and organizations, and offers actionable strategies to implement a more integrated and future-ready approach to customer service.

As the CX landscape evolves with AI advancements and greater data integration, CCaaS vendors face growing competition from CRM and UCaaS providers. This note explores key strategies for CCaaS vendors to remain relevant, emphasizing deeper partnerships, technology innovation, and holistic solutions that deliver value across the entire customer journey.

Cloud computing hasn’t stood still in its 28-year evolution, becoming the cornerstone of AI and business innovation. Companies still relying on outdated on-premises systems risk being left behind as the cloud continues to drive rapid advancements. This research aims to equip buyers with the insights needed to accelerate Cloud adoption plans.

In the evolving landscape of machine learning, combating model drift and decay is crucial for maintaining model performance. Continuous monitoring, automated retraining pipelines, and robust data management are essential strategies. Discover how proactive measures can ensure long-term value and guide your investment in the right AI solutions.

Within the industry, vendors are scrambling to release AI features for brands to use to automate, personalize and enhance interactions. However, the leading AI companies are looking to convert their solutions to become “super-competent colleagues”. If they achieve this, the consumer will lead the way in the AI arms race, ahead of the brand.

Fine-Tuning and RAG (Retrieval-Augmented Generation) are essential AI model enhancement methods, each offering distinct advantages and challenges. This research analyzes the strengths and use cases of both, offering insights and strategic guidance for AI technology buyers and developers.

The proliferation of Artificial Intelligence (AI) in Contact Center as a Service (CCaaS) and CRM Customer Engagement Center (CEC) solutions offers features to maximize contact center agent effectiveness. However, organizations must balance leveraging AI benefits with maintaining the core principles of WEM to ensure staff remain happy and productive.

AI vendors now offer more support for typical use cases such as lead scoring and propensity to buy. However, CMOs must realize more from AI to justify investment, like improved personalization and customer journeys. The data strategy and Martech stack are causing roadblocks — a more strategic approach will enable CMOs to drive AI-powered growth.