Marketers are under growing pressure to effectively consolidate and leverage an increasingly complex landscape of customer data, which includes mobile, social and other consumer generated data, internal CRM data, and highly contextual, third-party lifestyle and life-stage trigger data.
Increasingly, marketers are turning to data models and other big data analytics to transform these high-volume, high-velocity data sources into valuable customer insights, relevant customer engagement, and impactul, loyalty-building customer experiences.
Marketers frequently utilize Response Models and Cloning Models, each of which are built and perform differently, answer different questions, and present unique advantages. So what is the right data model for you? The choice depends on your objectives.
Response Models use historical marketing data or marketing test data to identify influential attributes of responders and non-responders, and then ranks prospect files based on the likelihood to respond to a particular offer. Choose a Response Model if:
- You need an analytical tool that is able to predict response characteristics, e.g., response rate, revenue, profit, or R.O.I., on an on-going basis.
- You are making significant changes to your marketing strategy, such as targeting a different market, changing or repositioning a product, or changing sales, marketing or media strategies.
Cloning Models use customer data to identify key demographic attributes of existing customers, and then match these demographic attributes to prospect files. Chose a Cloning Model if:
- Your primary goal is to identify prospective customers who are like your current or best performers customers.
- You are not making major changes to your offer or other parts of your marketing strategy.
For more information, please view the “Choosing The Right Data Model”, which provides a detailed overview of Response Models and Cloning Models and important factors to consider when choosing a data model.