By inspecting relationships among all of the data amassed on customers, data mining seeks to discover patterns of behavior – or indicators of such patterns – that can be used to formulate marketing programs or campaigns aimed at maximizing revenue per customer. Alternatively, it can be used to reduce the marketing spend on probable low-value customers.
Pinpoint ensures insights from data mining activities are made actionable by formally connecting the data mining process to the offer/message formulation and targeting processes using campaign management. Without this connection, the value of the insight will remain unrealized.
Marketing business intelligence provides reporting on a known customer pattern or profile, either on a periodic, ongoing basis or as a one-of or ad-hoc query. Business intelligence informs decision makers and knowledge workers of the latest developments in customer behavior and marketing effectiveness.
Pinpoint delivers personalized business intelligence via:
Segmentation involves clustering customers by common characteristics – based on interaction and/or external psychographic or demographic data – so as to enable differentiated treatment of them by Sales, Marketing and Customer Service.
Pinpoint’s approach combines traditional customer segmentation metrics, such as purchase activity or assets under management (in financial services), with measures such as attrition risk and customer profitability to provide more fine-grained segmentation, thereby maximizing customer value.
Pinpoint’s Web Analytics Services help you understand a users’ path to engagement and how to turn that data into the actionable intelligence you need to improve marketing relevance and customer engagement.
Modeling lifetime value at an individual customer level is the first step. The next step is making this model actionable as a key piece of segmentation information used to provide differentiated treatment of customers in Marketing, Sales and Customer Service.
Pinpoint helps its clients build models that accurately forecast each customer’s lifetime value to the firm, by identifying the determinants of customer lifetime value (CLV) that apply to your business. CLV models are used to score customers in real time at the point of an inbound interaction, such as a website session or call, so that the latest CLV information helps drive how you respond to each customer. Our clients seek to improve the current value of their highest-CLV customers through cross-selling campaigns and other means of increasing their brand’s “stickiness” with these customers.
The wealth of customer data collected by most organizations provides an opportunity to predict customer behavior based on statistical analysis and other quantitative methods. This predictive information is a key ingredient of making the right offer at the right time to each customer. The objective is to predict customer behavior in a given situation, based on the customer’s known attributes and past behavior.
It’s important to realize that the kinds of analysis discussed above do not require our clients to build a department of statistics experts; the marketing applications that Pinpoint usually installs include “wizard”-type capabilities that make such complex analyses available to the non-expert marketing user.
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