Personalization Engines

Personalization engine is a marketing tool that leverages data to enhance the customer journey. These engines deliver personalized content to customers on the company’s digital channels. They are most commonly used in e-commerce.

Customers expect a personalized experience thanks to their routine interactions with highly personalized digital solutions like Netflix and Amazon with their accurate content and product recommendations. According to studies they are willing to pay more for a personalized experience in many cases.

This trend creates a demand for personalization engines. According to another study, 91% of shoppers are more likely to convert with brands who understand their customers to provide content relevant to consumers daily routines. This shows how important personalization is, especially when you know almost 84% of an e-commerce website visitors are one-time shoppers that do not return.

Features include

• Inbound: website/mobile app personalization, personalized product recommendations, category specific discount coupons
• Outbound: general email/push notification/message personalization, cart-abandonment marketing emails

Companies can take an iterative approach in their personalization investments starting from low cost/high impact initiatives. A company could follow these steps to advance its personalization efforts over time:

• Unpersonalized optimization: This level contains testing and optimization. With testing, organizations can create the most optimal page design while maximizing site performance. This is initially done without personalization since personalization requires additional tech investment.
• Limited personalization: Organizations use basic targeting capabilities by leveraging contextual data such as location, device type, weather and time of interaction. Patterns in the data help organizations create a relevant digital experience.
• Channel specific personalization: Next, companies can find value in segmenting customers by combining contextual data with CRM, Point of Sale (POS) and 3rd party data management platform data. Segmentation data can be used in outreach as well as personalization of digital properties. Though companies better understand customers thanks to this data and segmentation effort, they tend to keep customizations in one channel due to the additional cost of rolling them out in all channels. Of course, companies that manage all their channels through one system could be rolling out these customizations to all channels.
• Omnichannel personalization: Synchronization of channels helps businesses unify experiences across web, email, app, and display ads.
• 1-1 personalization: Finally, organizations can perform predictive 1-to-1 personalization. Marketers predict customer needs and perform marketing activities accordingly. Organizations use machine learning algorithms to optimize their results.

We benefited from this description of levels of personalization in this answer.

• Drives traffic: With personalized web and email marketing, it increases the traffic to your site.
• Increases brand loyalty: Your customers feel like they are valued as individuals due to personalized content/offers/products your engine delivers. This increases the chances of them shopping from you again.
• Boosts ROI: Launching personal campaign can increase conversion rates. Mckinsey estimates that personalization can deliver five to eight times the ROI on marketing spend, and can lift sales by 10% or more.

Personalization engines have different capabilities and can be sold as a point solution. Capabilities can be categorized as:

Data and Analytics: Personalization starts with collecting data and performing analysis to gain insights that let you know consumers.

Testing: Your solution should be able to perform testing algorithms such as A/B and multivariate testing so that you can design your channel in an optimal way that attracts and nurtures visitors.

Behavioral predictions: Personalization engines can identify patterns of customer behavior and predict customer behavior (e.g. predict products that the customer is likely to buy).

Marketing Channel Support: Personalization engines can create and launch personalized campaigns through channels such as web, email marketing, mobile app engagement, mobile messaging, digital advertising, retargeting and paid search. This is especially relevant for e-commerce companies as they personalize their marketing outreach and their digital properties

Customer Experience Support: Personalization engines can support your omnichannel strategy by enhancing customer experience across touchpoints such as chatbots, voice assistants, interactive voice response (IVR) and call center conversations. They can also improve real-life experiences in digital kiosks or they can provide intelligence to retail sales reps via their devices (also called clienteling applications).

Measurement and Reporting: At the end of the campaign, your solution should help you track KPIs such as engagement and conversion rate to evaluate strategy via dashboards, and data visualization.

Our sources include Gartner 2019 Magic Quadrant report.