Delivering the best experience requires a deep understanding of each customer across many different dimensions. Not just who they are, but what they feel, what steps in the journey they’ve taken, and which steps they’ll take next. Customer analytics is the key to engaging target customers, reducing customer churn, deepening customer loyalty, growing lifetime value, and expanding revenue through new sales. It’s about identifying the right people to connect with, driving personalised experiences, and optimising marketing investments and resources to continually improve marketing performance.
Merkle helps marketers by integrating their enterprise and customer data, augmenting it with second and third-party data, and performing advanced analytics and data science to tackle critical marketing objectives. We employ segmentation and sophisticated models to identify and group similar customers to create personalised future journey and experience strategies. We forecast their future behaviour using predictive analytics, a sophisticated combination of data, analysis, modeling, machine learning and AI. We determine identity and create addressability within your customer data and ultimately prepare customer data for activation across campaigns, channels, and media. Attribution analyses inform us about what works, enabling us to measure success, identify improvements, and optimise spend.
MORE ABOUT THIS SERVICEAddressability & Activation
Identify and create new audiences that are addressable; meaning relevant data about a customer is assembled to reveal the individual’s personally identifiable information (PII) and other data aspects that enable you to understand the journey, the desires or motivations, what message to send and when. This enables activation, or the preparing of campaign or experience data for use in activation platforms such as adtech, martech, media, channels, social, etc.
Predictive audience analytics brings together integrated data, machine learning, AI, and sophisticated models to identify likely future behaviour of customers (e.g., next best action, NBX, next step on customer journey), often built off of past behavior, shared traits, look-alike models, profile data, sentiment data, and other factors. Predictive audience analytics improves and optimises marketing campaign performance and customer experiences.
Attribution and customer journey analytics use interaction data to discover which specific steps, locations, and times a customer took throughout their customer journey, often to a desired outcome such as a purchase. Attribution analysis is used to measure the performance and efficacy of marketing campaigns or actions, enabling marketers to understand what works and what doesn’t, so they may improve their campaigns and optimise for future performance and budget.
As the cookieless world becomes a reality, and consumer data regulations expand, organisations must have a privacy-safe data environment and analytics tools to support cross-channel insights, segmentation and modeling, and person-based measurement use cases.