Delivering a “right time” customer experience (CX) is essential to provide customers with the level of personalization that drives higher satisfaction, loyalty, and lifetime value. It is the key to relevance, reflected by a brand’s ability to recognize a customer’s needs and wants at the moment of engagement. With dynamic, omnichannel customer journeys now the norm, the “right time” to meet a customer with a next-best action is often in real time, or near real time.
Many enterprises lack the type of situational awareness that consumers are expecting in real time. That is why real-time engagement must start with data readiness, a concept and methodology for delivering a unified customer profile enriched with the contextual understanding needed to adapt every experience in the moment. This is the foundation of the Redpoint approach to real time engagement.
The Real Time Imperative
Experiences that call for a real time engagement might include a health provider’s website displaying content, imagery, and information relevant to the health condition of the website visitor – whether the individual is known or unknown. Or a call center agent who has instant access to a complete, accurate, and updated unified customer profile resolving an issue to a customer’s satisfaction without having to ask probing questions. Or a brand optimizing an abandoned shopping cart strategy with real time (and right time) triggered actions based on the behaviors of an individual consumer.
Seamless real time experiences are now integral to a brand’s ability to deliver a relevant, personalized CX, and consumers are holding brands accountable. In a Dynata survey, 80 percent of respondents said they are more likely to transact with brands that demonstrate a personal understanding.
With real-time so critical to a frictionless CX, why is it still an obstacle for many brands? A major culprit is siloed data, channels, and processes that put real time engagement beyond reach. Consider a Gartner report that shows that roughly 50 percent of large organizations will have failed to unify engagement channels by the end of this year, resulting in a disjointed and siloed CX that lacks context.
Real Time Requires Complete, Accurate & Timely Data
Data readiness is the way forward because it provides brands with an important contextual understanding of customers, patients, and households. It is also invaluable in parsing relationships, such as identifying individual customers within a business account.
Data readiness solves the traditional barriers that prevent brands from real-time engagement. One is not having a deep enough understanding of a customer to be able to engage with a relevant, personalized CX in real time across all channels. Even if a unified profile is timely, in other words, it may still be incomplete or inaccurate. When a marketer or business user has the wrong information, a real-time engagement likely just means a brand delivers the wrong message more quickly.
Not having the data available in the needed time-frame is another obstacle, which might occur if the data is siloed by channel, or if there is a lag with the source data. The longer the lag, the less of a contextual understanding for how the data relates to an ongoing customer journey.
From an operational standpoint, these barriers prevent consistently relevant real-time experiences in part because each channel or team has its own view of a customer, which is built through multiple systems. There is no uniformity.
As for data lags, consider the ramifications if a web personalization tool calls out to a CDP to attach browsing session data to an existing profile. If the CDP provides the tool with data only when a source system is updated (nightly, weekly), it may be missing important information – a recent purchase, a call center interaction – that would materially alter the real time website experience.
A Unique Approach to Real Time Engagements
Real-time engagement isn’t achieved by simply adding a faster decision engine, it’s achieved by ensuring the data feeding those decisions is always ready, accurate, complete and contextual.
A data readiness platform eliminates the problems that stem from incomplete and untimely data in several ways. The Redpoint Data Readiness Hub separates itself from other customer engagement technology solutions because of its unique understanding and approach to real time, a large part of which is making sure that data is continuously ready and fit for purpose the moment it enters the system.
Not only is all possible information and relevant data about a customer in one place, but Redpoint continuously applies full data quality processes as data is ingested. Real time data processing extends to source systems, which means that the resulting unified customer profile always reflects the most accurate and updated understanding of a customer. Identities are also resolved in real time, whether that means matching a website visit to an existing customer, matching a person to a household, etc.
With a full contextual understanding, brands have the situational awareness to make informed decisions and create the most compelling experiences for the customer at the precise moment of engagement.
Augmented Real Time with Real Time Decisioning Pipelines
Beyond delivering a full contextual understanding through a complete, accurate and timely unified profile, Redpoint’s approach to real time includes pre-decision and post-decision pipelines, which is where additional contextual information is gathered the moment preceding and following a decision.
Immediately preceding a decision, a call can be made through an API to gather additional context, whether it’s a model, a weather update, a credit card check or another piece of information that is then loaded into the customer profile to layer in real-time context. The post-decision pipeline is where a decision can be manipulated, such as being sent to multiple systems or channels. Importantly, the pipelines are stackable, meaning they enable more than one decision.
The pipelines enhance contextually relevant experiences because they’re built around dynamic rules that permit messages, offers, and/or content to be switched out up to the moment of interaction. A sudden storm warning, for instance, might impact how a hotel desk clerk interacts with a guest who is checking in. A pre-decision pipeline calls a machine learning model – Redpoint’s or a client’s – that returns real-time recommendations optimized against the decisions built into the platform. The immediate context (inclement weather) becomes part of the updated profile.
A post-decision pipeline works in the same fashion, providing an opportunity to update a decision before it is presented to a device, app, website, tablet or even in person – such as using generative AI to change the tone of an email.
The practice of engaging customers with real-time decisions that are contextually relevant at the moment of engagement builds on its own success, enabling additional context for subsequent decisions. Results of any real time decision, such as the customer making a purchase, downloading the app, signing up for a loyalty program, etc., are fed back into the platform to update an individual customer profile and to alter the pre-decision or post-decision content.
Real Time with Redpoint
Marketers chase real-time engagement, but it’s context that drives value from it – revealing exactly who the customer is, when it matters most – in the cadence of the dynamic customer journey.
For more on the Redpoint approach to real time engagement, or to see how Redpoint can help you achieve results such as a 79 percent increase in conversions through real-time product offers, click here.
