By AnnMarie Wills, CEO, and Co-founder of Leverage Lab
Even from within the tiny Hollywood Squares of an over-attended Zoom call, I recognized that look immediately. The snap of suddenly raised eyebrows as contradictory information crashes headlong into a previously held belief, followed by catastrophic energy drain slowly replaced by a crushing display of disillusionment. All this played out across the face of the senior leader at a beloved retailer.
We see this often. The dream of new technology doesn’t always match reality. It’s certainly no coincidence that in Leverage Lab’s work with enterprise organizations, personalization is prioritized by marketers over all other first-party data use cases. According to research by McKinsey, personalization matters more than ever. Consumers (71%) expect personalized experiences from companies. And, companies can expect to see an increase in sales revenue, just by personalizing key customer experiences. Granted, this is not a particularly new dream. Some level of message personalization has been hyped if not delivered by CRM and adtech vendors for more than 2 decades.
These days, CDPs, with their unified profiles and promise of federated customer data, have grabbed the mantle as the preferred technology for personalized omnichannel marketing. But, many enterprise marketers managing customer journeys filled with addressable touchpoints have found out, personalization managed at the CDP level might not cover as much of the journey as they hoped.
Where to Put the Personalization Engine?
Some think CDP solutions have already begun the slide into a trough of disillusionment, especially when it comes to executing on personalization at scale. Recently, I spoke to Apoorv Durga, Vice-President, Research & Advisory at analyst firm Real Story Group, and he confirmed that he regularly hears from marketers at large brands struggle to implement personalization-at-scale no matter how much money they throw at the strategy.
“The dream of personalizing a customer touchpoint by blending everything we know about them with contextual data about the moment is maddeningly difficult to execute,” Durga said. “Sure, marketers can use the CDP to personalize in-app or on-site to personalize a user experience, but it cannot easily leverage third-party weather data to recommend a hot coco over a sports drink.”
Durga suggests there are at least three places in the MarTech stack that personalization services can reside: at the channel, within a data platform, or as a stand-alone service that covers the user experience. Each has its pros and cons, and ultimately marketers may end up with a “mix and match” of strategies depending on where they are in the personalization maturity curve.
At the Execution Channel
As I mentioned before, marketers have aspired for personalization for over two decades now. From the early days, email platforms allowed you to mail merge list data to personalize email subject lines and body copy. Since these humble beginnings, nearly every activation platform now offers some personalization tools. And though channel-specific personalization might lack consistency controls across a multi-channel user experience, it is certainly the fastest way to include personalized experiences and the easiest to fit into existing workflows.
“This approach offers the tightest integration within marketers’ experience layer,” Durga said. “For example, marketers can easily leverage personalization logic to serve relevant website or email content to a user.”
These in-channel solutions do bring decisioning closest to the user, but are limited by the channel and are siloed from experiences elsewhere in the customer journey making it difficult to address expectations holistically. Often channel personalizations conflict with one another and provide incongruent experiences that are not informed by the customer behavior exhibited in other channels.
On the Data Platform
With the advent of Marketing Automation Platforms, and, more recently Customer Data Platforms and Journey Orchestration Platforms, marketers can decision on a single customer view versus looks that vary between point solutions and channels. Using basic CDP functionality, a marketer can track changes in a user’s status. For instance, if a user’s digital subscription expires, a marketer can set up a rule that sends them personalized incentives via email or SMS to win the user back.
“There are many omnichannel data platforms with personalization capabilities built on top of their data management capabilities or as an integral part of their orchestration capabilities. In some cases, the capabilities may prove light, but you get the benefit of operating them close to the all-important customer behavioral data and the personalization logic isn’t stuck in one channel,” Durga said.
Though CDPs and marketing automation platforms make centrally managing personalization easier, enterprise marketers looking to leverage first-party behavioral data and third-party contextual data like geo and weather may be disappointed. Most CDPs have no sense of contextual data like real-time location and weather.
Personalization as a Dedicated Service
Many major MarTech suite vendors bundle personalization services with their flagship marketing platforms, while newer generation of solutions are decoupled and channel-neutral personalization engines. This way personalization benefits can leverage all types of available data and activate on it consistently throughout the customer journey. Having one customer interaction inform the next touchpoint regardless if it occurs in another channel begins to deliver on consumers’ expectation of a single conversation.
“Consumers respond to interactions that are consistent with and build on previous touchpoints,” Durga said. “Personalization solutions that can take all interactions into account and customize messaging with third-party data help guide consumers along their journey in a more human way.”
Heightened customer expectations, an abundance of behavioral data, and the maturity of machine learning and AI capabilities are all prompting a continued push toward personalization. The tech strategy a brand settles on to tailor recommendations, content, offers, and experiences will depend on where they fall in the push and pull between the ease of implementation and the quality of experience. Real Story Group offers this summary:
Where dedicated solutions may offer more consistent personalization across channels, more personalization scenarios, and more streamlined tech architecture; the decisioning logic is the most removed from the actual user profile. Apoorv does point out that these approaches are not mutually exclusive, with most organizations utilizing a mix of strategies and platforms. He suggests that marketers begin with channel-specific personalization, grow into more sophisticated data platforms, and eventually consider a dedicated engine.
“Decisioning as a dedicated layer atop of the customer data infrastructure provides a more seamless omnichannel experience for users. It provides a tech architecture where point solutions do not wrestle for control, but instead act in union.”
Leverage Lab agrees this is the preferred strategy for executing a consumer-centric strategy, especially for enterprise brands and retailers. We are indeed taking an omnichannel approach by employing a dedicated personalization engine that sits on top of their customer data infrastructure. This way decisioning, in the form of product recommendations, will be managed centrally across multiple customer endpoints and informed by customer data housed in the CDP, along with real-time location and weather information.
The outcome ensures relevant recommendations powered by a collaborative filtering model that factors in transaction histories, inventory, time-of-day, and other environmental information. More importantly, it delivers on consumer expectations that their store knows them as an individual.