In today’s dynamic landscape of customer experience (CX), where real-time personalization and data unification define the competitive advantage, enterprises increasingly depend on the strength of their customer data foundation. Few understand this interplay between data readiness, CX performance, and business agility as deeply as Steve Zisk, Senior Product Marketing Manager at Redpoint Global. With more than three decades of experience spanning software engineering and product marketing, Steve has been at the forefront of advocating precision, intelligence, and orchestration in customer engagement strategies at Redpoint Global.
At Redpoint Global, a recognized leader in customer data technology, Steve helps brands bridge the gap between disconnected data and actionable insights. Intelligent solutions from Redpoint Global ensure that customer data is clean, connected, and continuously ready for enterprise use—turning AI initiatives and CX strategies into measurable business outcomes. The company’s customer engagement platforms are redefining how organizations deliver meaningful, omnichannel experiences that drive growth and loyalty.
In this extensive conversation with CXQuest.com, Steve opens up about the evolving power of customer data, the critical role of AI in experience transformation, and how enterprises can unlock new possibilities through intelligent data-driven engagement with Redpoint Global.
Cxquest.com Welcomes Steve Zisk, Senior Product Marketing Manager at Redpoint Global
Q1. How has the role of data readiness evolved as enterprises move deeper into AI-driven CX strategies?
SZ: As AI strategies have moved from using machine learning and classical models to LLMs and AI agents, the need for high-quality, AI-ready data to deliver needed results has become obvious. A traditional, point approach to data quality and data readiness is no longer sufficient. Rather, there needs to be a broad-based availability to high-quality data for interacting with AI, creating models, and visualizing data. The expansion of AI and agentic AI use cases make it essential that enterprise companies have a clean, accurate, and timely (real time) view of a customer. While fragmented, ‘unclean’, and siloed data have always created CX friction, the age of AI makes it even more important to pay heed to data readiness.
Q2. What unique challenges do organizations face when aligning their CX goals with their data management capabilities?
SZ: One key challenge is that data management capabilities traditionally revolve around channels, products or processes. When you align your CX goals around this traditional data management viewpoint, the result tends to be an inconsistent CX where an experience received on one channel has no relevance to an experience on another channel.
Another unique challenge is ownership of the data, where ownership of CX data has evolved from departmental ownership (e.g., marketing owns marketing data, etc.) to the recognition that data is an enterprise asset and must be treated with the same care as any enterprise asset; governed, transparent, trusted, and with validated change processes.
Ensuring Data Accuracy and Agility
Q3. Could you explain how Redpoint Global helps enterprises ensure data accuracy and agility across channels?
SZ: As the data readiness company, Redpoint makes data right and fit for purpose for any CX or AI use case. We break this down into the creation of a Customer 360, or golden record, and the activation of the Customer 360. The building of the golden record – a persistently updated, real time unified customer profile – entails completing all data quality processes (cleansing, standardization, enrichment) and identity resolution steps at data ingestion. Data is complete, accurate, and timely, providing an important contextual understanding of a customer. Because the golden record is available and accessible across the enterprise, marketers and business users have a consistent understanding independent of channel.
The unified profile is always in the context of a customer journey, and always reflects the real time understanding of the customer.
The Redpoint platform brings data that are siloed within channels and make the data available across channels, a key capability for being able to deliver a consistent CX. In addition to a complete, accurate profile, the platform enables agility – the ability to meet a customer anywhere across a dynamic, real-time customer journey. Agility is driven by the incorporation of AI workflows for both CX leaders and marketers – workflows that include agents and chatbots, as well as the AI-driven production of content and offers, and the AI-driven decision support for real-time decisions.
Handling Fragmented Customer Data
Q4. Many organizations struggle with fragmented customer data. What best practices do you recommend for achieving a single customer view?
SZ: One best practice is for organizations to organize their data strategies along a use case access. That is, think about which use cases need which sets of data and group those datasets accordingly, thinking about use case priorities and commonalities. Attacking related use cases in parallel helps streamline a data readiness initiative to make data right and fit for purpose to drive the intended outcome.
An enterprise tech stack should be able to support this strategy, particularly with the following capabilities that help with unifying data across channels:
– Prioritize data cleansing, matching, merging, and identity resolution as data is ingested into a single data management or data readiness platform. (Leaving data quality or identity resolution processes until they’re needed downstream introduces inconsistency – and a lack of trust).
– Persistent key management, which provides a key longitudinal view of the customer, cementing a deep understanding of customer (or household) over time.
– Advanced identity resolution using a combination of deterministic and probabilistic matching. (As distinct from a basic match, insufficient to support successful AI-driven use cases).
Balancing Automation and Human Touch
Q5. How can businesses balance automation and human touch in delivering hyper-personalized experiences?
SZ: One way to balance automation and a human touch in the age of AI is to plan workflows that keep humans in the loop from the outset. AI needs oversight and second-level fallback, such as being ready for a “special touch” with a human for, say, loyalty customers or if AI has a hard time solving a customer problem. The last thing anyone wants is AI hallucinations that introduce CX friction, and maintaining human oversight helps keep problems in check.
Balancing automation and a human touch is also important to avoid the creep factor. To strike the right balance for each customer, it’s important to incorporate customer preferences into a Customer 360, and to always listen for customer signals, e.g., what is the customer’s desire for touch frequency? Organizing CX around the customer helps the enterprise achieve consistent relevance without being overbearing.
Trends Shaping the Next Decade
Q6. What trends do you see shaping the next decade of customer data technology and engagement platforms?
SZ: We’ve already reached the tipping point of digital engagement, and the next decade will further consumer expectations for digital-first interactions across retail, travel, healthcare, financial services, and other industries. To meet this expectation, customer data technology will largely be powered by agentic AI or evolving technologies that facilitate consumer/brand interactions driven by personalized agents, underpinned by data readiness.
Also, most organizations presently think about AI as delivering the same capabilities as humans do but in an automated fashion. That is, they think about how they can fit AI into their current workflow and/or campaigns. This will soon change to organizations thinking instead of how they can create entirely new workflows/campaigns through AI innovations. This will both be internal, i.e., for improvements within the CX organization, but also external, ie., what the customer is trying to accomplish with their own AI agents and how to align their capabilities, tasks, and CX goals with a brand’s AI agents.
Enabling Real-time Engagements
Q7. How does Redpoint’s platform enable real-time interactions powered by clean, actionable data?
SZ: The unified profile is persistently updated as new data enters the system; there is never a lag between data coming in and data being right and fit for purpose for the intended use case. The Redpoint Data Readiness Hub creates a complete, accurate and timely unified customer profile by updating the profile in milliseconds. Ingestion, cleansing, identity resolution and decisioning all run in real time – which makes the profile both accurate and actionable.
Updates are made with every new customer signal, every new event, and all up-to-date activity from the web, mobile apps and devices. The use of persistent keys provides the meaningful historical detail to infuse interactions with context.
In addition, the design of Redpoint’s real-time decision engine is to work with other common CX technologies like DSPs, model building environments, and content management systems to provide a behind-the-scenes decisioning framework to support direct interactions with customers.
Clients’ Measure Outcomes
Q8. What measurable impact have clients observed after adopting Redpoint’s data and engagement solutions?
SZ: Redpoint clients span several industries, including retail, travel and hospitality, financial services, and healthcare payers and providers. Measurable results include 79% higher conversions for a CPG company from Redpoint driving real-time product recommendations based on the complete, accurate and real-time unified customer profile. A media company used Redpoint’s real-time decision engine to drive more than 10K decisions/second – with a 20-millisecond SLA. A financial services organization used the Redpoint Data Readiness Hub to achieve a 90% reduction in cost to get data fit-for-purpose, in addition to creating dynamic audience segments 80% faster.
These and other clients have unique use cases for needing clean, accurate, and timely data. Redpoint helps them achieve their goals with data management capabilities that prioritize comprehensive data readiness across the complete data lifecycle.
Advice to Emerging CX Leaders
Q9. As a technology veteran, what advice would you give to emerging CX leaders navigating rapid digital transformation?
SZ: I have a lot of advice, but I’ll limit my answer to the intertwined concepts and need for agility and data products!
The need for CX leaders to be more agile is driven by both external forces (political and economic change, new platforms and capabilities driven by AI, rapidly changing expectations) and internal forces (the need to extract more value from data, a demand for efficiency and cost control, and a demand for the internal use of AI to accelerate change). Because of these pressures, the CX leader must have the mindset for facilitating an agile development of a CX environment that is responsive to all of these pressures. The right mindset should therefore approach data as a product, with a contract in place for any and all CX deliverables, i.e., what one desires for CX outcome, what is the timeline, how will you measure value, etc.?
Thinking of data as a product and the benefit of expressing this through data product contracts helps enterprise companies better understand and express the value of data. An important point to remember when transitioning to this approach is the recognition that CX – as a primary consumer of data products – must therefore be a primary driver of this framework, bringing the data engineering teams, CDO, and business users together for a common understanding of what a modern CX will look like, and what the business wants to accomplish. In other words, CX teams don’t operate on an island; a modern, AI-driven CX requires that these teams get what they need from the rest of the organization.
Supporting Future-ready CX Frameworks
Q10. Looking ahead, how is Redpoint Global innovating to support AI governance, responsible data use, and future-ready CX frameworks?
SZ: The Redpoint Data Readiness Hub is purpose-built to fit within an enterprise company’s desired architecture, data locality, and governance requirements.
Redpoint’s AI initiatives and classical data initiatives provide a contextual understanding of an organization’s data, making sure it is accurate, transparent, and trusted. AI must have clean, accurate data to control costs and hallucinations.
Further, you need to govern the data itself and AI agents, and that too with the proper management for cost and effectiveness. Redpoint’s agile framework makes this possible, with a data-in-place environment that meets compliance (and cost) requirements.
Data readiness initiatives should be able to handle these constraints; if your data is spread across multiple SaaS applications, for instance, it will be very difficult to achieve the results you want from the responsible use of AI. By contrast, Redpoint provides key situational details and context, both for an understanding of a customer at the end of CX, but also for a role-based understanding of all users (AI agents, models, and internal users as part of a data product contract). This makes it easy for companies to design governance from the outset to make sure that AI operates as intended, such as from the point of view of MCP servers, agent-to-agent workflows, and agent guardrails.
Closing and a Big Thanks to Steve Zisk
As enterprises embrace AI and automation, the frontrunners will be those who view customer data not as an operational byproduct but as a living, evolving asset that drives every CX decision. Steve Zisk’s insights underline a critical truth—great customer experiences begin with great data. Through organizations like Redpoint Global, the path from data chaos to connected intelligence is becoming clearer and more attainable.
For CX leaders aiming to future-proof their customer engagement strategies, Redpoint’s approach demonstrates the value of harmonizing technology, trust, and truth in every interaction. The conversation reaffirms that while AI may amplify experiences, it is the readiness and reliability of data that sustain them. Explore more about Redpoint Global’s data-driven solutions at www.redpointglobal.com.
