Personalization engines help engage and retain customers
Content personalization is essential to getting the right material to the right customers. Here are some personalization engines that can help you better target your content.
If you can recognize your customers and better understand their needs, you can provide them with the goods and services they want, thus improving your chances of converting browsers into buyers.
Creating and managing content -- launching a website and rolling out a marketing campaign -- is only the tip of the iceberg; personalization is the holy grail for doing business in the digital age.
You need to target the content you deliver to customers and prospects based on what you know about them as well as what they tell you about themselves. And you can capitalize on existing investments to make your digital presence more relevant through automating personalization.
Personalizing the customer experience ecosystem
Personalization engines represent a rapidly maturing class of software that bundles capabilities for sorting, selecting and targeting content delivery, based on knowledge of the intended audiences. These engines are a key part of an overall CX ecosystem, linking content to context, monitoring results and dynamically producing delightful -- and profitable -- experiences.
A personalization engine matches actions with intent. The engine runs in the cloud and augments existing investments in CX technologies. Key capabilities include:
connecting with content collections, through content services platforms that manage content through its lifecycle and expose predefined tags;
defining customer segments based on collecting, organizing and normalizing customer-related data, and aggregating from third-party sources when needed;
modeling experiences to describe the criteria and logical information flows that need to be met to deliver personalized results;
defining the events that occur within a modeled experience that produce actions with triggers;
testing supports tools to compare alternative designs or information flows; and
monitoring the choices customers make and determining where improvements can be made to refine experiences.
Multiple personalization engines are now on the market, including Acquia Lift, Adobe Target, Episerver Personalization Suite, Evergage 1 Platform and Google Optimize 360. Pricing for a personalization engine ranges from free -- for the basic version of Google Optimize -- to several thousand dollars per month, depending on the size and scope of the implementation.
Modeling and personalization strategies
Don't let price be the driving factor. The real cost of personalization is the upfront investment to model how you want to engage with your customers and assemble the experiences you want to deliver.
The real cost of personalization is the upfront investment to model how you want to engage with your customers and assemble the experiences you want to deliver.
Building audience profiles from disparate data sources -- some generated by internal company activities and others acquired from third parties, such as data brokers and online publishers -- takes time, effort and funding. A customer data platform (CDP) can simplify and accelerate this process by providing a centralized source for all customer-related data. Some personalization engines even include a CDP, while others rely on third-party tools to support segmentation.
Personalization requires access to a lot of content. Notably, a personalization engine benefits from a well-defined information architecture where content is tagged by business-relevant criteria. Some personalization engines are tightly linked to a content services platform while others are agnostic about content sources.
Equally important are your overall personalization strategies: how targeted dialogues can engage your customers, increase revenue and customer satisfaction, and justify the required investment. Personalized customer experiences can be based either on explicit or implicit criteria -- a sequence of steps that are defined beforehand or those that are inferred based on statistical or algorithmic patterns. Personalization engines increasingly support machine learning algorithms for more precise pattern recognition, with varying degrees of delivering personally useful experiences.
It is best to start with two or three defined situations to explore personalization outreach. Pick examples for which you can easily acquire the information you need to segment your audience into meaningful groups and target content delivery. And test your personalization strategies to see what works. A personalization engine provides the enabling technologies to experiment with multiple approaches and optimize the ones that are best for your business.
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