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Personalization Engine

Personalization engines analyze customer data collected from outside software and use it for customized interactions and for building long-term customer relationships. These engines can generate effective marketing tactics as well as presentations, such as landing page content specific to user data, product carousels in the purchase funnel and specific email messages based on site events or triggers.

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Customer Experience Tools and Trends

Our insights share how the right CX tools make customers’ lives richer and more fulfilling and strengthen a company’s economics by holding down costs and securing new revenue streams.

The personalization tools rely on advanced analytics to build a deep understanding of a specific customer's evolving needs. Marketing and innovation teams then use the data to create unique and dynamic messages, offerings and experiences. They send personalized content at the ideal time to engage the customer, or adapt the content to the customer profile on a website or mobile app.

Personalization engines thus can enhance the customer experience, make advertising more effective and increase retention, loyalty and sales. 

Customer Experience Tools and Trends: Personalization engine


How companies use personalization engines

  • Customized promotions address an individual customer’s needs based on engagement across different channels and stages.
  • Similarly, engines help to tailor content for customers throughout their lifecycle of interactions with the company.
  • Advertisers use the engines to inform paid and owned channel marketing and adapt the content of online ads in real time.
  • Mobile network companies might use the approach to identify and target their most connected customers, so they can encourage them to refer friends and colleagues.
  • Retailers often deploy personalization engines to offer promotions to customers who are at risk of defecting.
  • E-commerce and digital media firms track their customers’ actions, click patterns and transactions, allowing them to offer product recommendations that reflect a customer’s preferences and previous buying behavior. The data also can be monetized by selling it to other parties.
  • Financial institutions analyze customers’ credit card use and cash withdrawals to improve their products and make targeted offers, such as loans for late credit card payers and new credit cards for heavy spenders.

Key considerations

  • Optimize the full experience. Put the decision engines at the heart of all marketing. Use them throughout the experience of becoming a customer and subsequent use of products, as well as to build high-converting customer journey maps by leveraging data from website entrances.
  • Own your digital destiny. Take control of consumer data and integrate marketing and advertising technologies, avoiding “black box” solutions whenever possible. Invest in and exhaust first-party data, then integrate third-party data.
  • Stay in control. Overlay clear marketing controls on these engines and retain the ability to set customer budgets and marketing objectives, and to prioritize different customer segments.
  • Master the timing. Behavioral insights can reveal the best times to seize a customer’s attention and stimulate a purchase or interaction, helping the company build brand loyalty over time.
  • Build a test-for-results culture. Use timely analysis from experiments and metrics with common definitions in decision-making. Encourage experience sharing among marketing and commercial groups.
  • Enable fast decision making. Create an in-house team to oversee customer acquisition and retention, with accountability for budgets, technology, data and analytics.

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Vector℠ is a service mark of Bain & Company, Inc.