PERSONALIZATION
AT SCALE
MEANS GROWING
40%
FASTER
Than Competitors.*
PERSONALIZATION AT SCALE
Our solution brings together customer data, technology, and agile marketing to deliver personalized experiences. We do this by empowering your first-party data. First-party data provides everything you need on customer information and behavior, and it’s much more reliable than data collected by a third-party company or data marketplace. It is proprietary to your brand and a clear signal of users motivations.
With Leverage Lab as your partner in personalization at scale, you can expect higher performing marketing campaigns, improved return on investment and more sales for your company. At the core, it’s all about knowing your customer and giving them what they want. Through successful personalization, you can increase customer engagement and enhance brand loyalty.
Do you believe personalizing your customer's experience can improve your performance? If your answer is yes, Leverage Lab is for you.
80% of Consumers Demand PERSONALIZED Experiences When They Shop*
You cannot achieve personalization at scale successfully without our Data, Decision, and Delivery methodology. Success requires building a rich customer profile, identifying the moments of opportunity and delivering experiences across all platforms. Relevance is key; it’s about getting the right message to the right customer at the right time in their Infinite Customer Journey.

DATA
One of the biggest roadblocks companies experience with personalization is within compiling and organizing the data in one place. That is why the first step in personalization at scale is to pull the trapped data out of silos and build a customer data infrastructure that unifies data and creates a rich customer profile that can be made accessible to all systems.

DECISION
With unified data, comes along actionable insights. Marketers ask questions such as: What is the customer interested in? Where are they in the process? What should be recommended at the next touchpoint? Through the use of machine learning and AI models, integrated decisioning is completed to predict the consumer’s behavior. Important moments of opportunity are identified from the data at an individual level to create personalized recommendations outside of basic models.

DELIVERY
Delivery is more than just applying actionable insights into the customer journey. It is more than just channel integration. Delivery is the real-time orchestration between providing customers a personalized experience, coordinating communication and reacting to the customer’s actions. It is an automated infrastructure that sends insights back into the data following the success or failure of the delivery providing instant reporting and quick refinements.

DATA
One of the biggest roadblocks companies experience with personalization is within compiling and organizing the data in one place. That is why the first step in personalization at scale is to pull the trapped data out of silos and build a customer data infrastructure that unifies data and creates a rich customer profile that can be made accessible to all systems.

DECISION
With unified data, comes along actionable insights. Marketers ask questions such as: What is the customer interested in? Where are they in the process? What should be recommended at the next touchpoint? Through the use of machine learning and AI models, integrated decisioning is completed to predict the consumer’s behavior. Important moments of opportunity are identified from the data at an individual level to create personalized recommendations outside of basic models.

DELIVERY
Delivery is more than just applying actionable insights into the customer journey. It is more than just channel integration. Delivery is the real-time orchestration between providing customers a personalized experience, coordinating communication and reacting to the customer’s actions. It is an automated infrastructure that sends insights back into the data following the success or failure of the delivery providing instant reporting and quick refinements.