Retargeting Automation

What is Retargeting Automation?

Retargeting is a marketing tactic of serving ads and content to customers and potential customers who have interacted with your website or other properties. Depending on what content they have interacted with, corresponding content can be served to them as they traverse the internet so your brand stays top-of-mind. The automation part comes in when machine learning and AI are involved in the retargeting.

Why is Retargeting Automation Important?

Taking action at that moment of truth often requires responding in real time to customers’ cues. Real-time marketing spans a spectrum that extends from ad hoc (e.g., one-time targeted communications) to automated (e.g., triggered, dynamic, adaptive) – but the most important aspect is that it needs to be real time from the perspective of the recipient of the message. Consider: Even a Tuesday batch message email blast is still considered real time to the recipient at the time it is opened. Consequently, marketers should incorporate a variety of real-time tactics to improve message relevance. Not doing so leaves companies open to delivering poor customer experiences.

Getting Started

Begin with a focus on real-time marketing through one channel. Use business rules that suppress message volume and offer repetition, run cart abandonment campaigns, build customer segments, and test dynamic personalization in outbound channels. Technologies that support this basic approach include campaign management, email marketing tools, and customer data platforms – solutions that bring together first-, second-, and third-party data, probabilistic and deterministic record matching, and identity resolution to generate a holistic view of the customer.

Graduate to incorporating more than one channel in an orchestrated way. Introduce and test multichannel campaigns that comprise at least two channels. Add retargeting and event-based trigger campaigns to the marketing mix. And, establish a customer preference center to inform future campaigns. Technologies that support this more advanced approach include ad tech, content management and e-commerce platforms, and next best action/offer tools, which use advanced analytics such as machine learning algorithms, as well as business rules, to automate decisions across the customer journey.

The Future of Retargeting Automation

Retargeting has been and continues to be an important tool for marketers, but change is coming. Third-party cookie data collection is soon to become a thing of the past. Chrome, Safari, and Firefox will not support cookie data tracking in 2022 so marketers need to find new ways to get in front of customers and potential customers.

The confusion over how to bridge this gap stems from a traditional viewpoint that a customer identifier as it relates to an enterprise strategy – an overall operational view – must be separate from an analytical view used for marketing purposes. There is uncertainty over who is responsible for what, and how a universal key for a customer that contains every transaction and anything related to risk, compliance, finance and accounting will mesh with the marketing side, which will contain household information, channel activities, campaigns run, lifetime value, and other data points historically used by and for marketing.

A consequence of divergent strategies is uncertainty that an enterprise strategy is, in fact, based on an accurate view of the customer. A familiar example is the pricing of term deposits. Many institutions offer blanket or individual rates rather than pricing the fixed-term investments as loss leaders for their most valuable customers. For many, the reason is that they just don’t know who their most valuable customers are, and thus are unable to price any product as part of a customer’s overall portfolio. That’s just one small example of how knowing everything there is to know about a customer may help spur revenue growth, and it wouldn’t by conventional standards be considered a marketing use case.

Everything stems from the single customer view, and in some instances driving revenue growth may not even be the overarching objective. Perhaps the institution wants to segment an audience to attract a more diversified customer base, or to attract customers that better align with a brand’s image as it pertains to social or environmental issues. The point is, a strategy centered on the customer must have a solid understanding of an individual customer, and that understanding depends on combining the traditionally separate operational and marketing views.

The Way Forward

The right CDP can help marketers see, using their own data, not only what a true single customer view looks like, but one that’s fitted for both marketing/analytics and the enterprise data strategy.

Many vendors in the customer data platform space have a very difficult time playing both sides of the aisle primarily because they stop at basic identity stitching – leaving it up to marketers to decide what data is pertinent. The customer data platform must provide not only a single view of the customer, but one that is in real time and relevant to the entirety of the customer’s journey. To do that there must be a capability to do householding, to do advanced identity resolution with both probabilistic and deterministic matching, and to bring online and offline data together.

rgOne helps companies advance the vision, from knowing they should start with what they know – the customer – to actually envisioning what a unified, real time profile looks like and how to begin experimenting with using a single view to deliver a personalized, customer-centric experience.

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