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A Solid Data Foundation

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A Solid Data Foundation

More data has been produced in the last two years than in all previous history. And thanks to the Internet and an ever-expanding variety of connected devices, the amount of customer data available to businesses and brands is growing exponentially and will continue to do so. Properly collected and analyzed, customer data can deliver increased business revenue, bigger wallet share, and happier and more loyal customers willing to advocate for your company’s brand(s).

How do you accomplish this amidst the “digital deluge”?  I will now share the steps with you, using ISM’s Engaged Customer Strategy framework as a roadmap. Let’s start with the foundation.

Creating a rock-solid data foundation begins by gathering three distinct types of data:

1. Transactional Data – Purchases, returns, etc. from ERP, POS and/or loyalty systems

2. CRM Data – Sales lead/opportunity tracking, marketing campaigns, customer-service calls

3. Third-Party Data – Customer demographics, lifestyle and industry-specific data

This data can be derived from either online or off-line sources, and both are important. Activities like store visits, service calls, or contact-center interactions are non-digital and take place off-line. Online data like website visits, eCommerce transactions and Social Media engagements also must be captured, organized and stored. Often, this data will be anonymous. New Identity Resolution tools can then be used to integrate off-line and on-line data, match both anonymous and identifiable information, and feed this into individual customer profiles. These holistic customer profiles, residing most often within a CRM system, are the foundational building blocks that enable companies to transform customer data into value.

Once your holistic customer profiles are in place, the next step is to perform detailed data analysis on these profiles. The goal is to develop accurate customer segmentation, customer personas, customer journey maps and more, to help identify the right customers and their preferred buying channel(s). While there will always be challenges to performing good data analysis, there is no shortage of opportunities. Many of ISM’s clients use look-alike modeling, opportunity sizing, acquisition modeling, lead scoring, cross-sell, next best offer, retention/survival modeling, response modeling, customer lifetime value (CLV) and other techniques to derive meaningful, actionable insights from their customer data.

Upon completion of your data analysis, you are now ready to sell products through one or more of four customer engagement channels.

IISM would be happy to discuss data analytics developments impacting your business in more detail with you over a call.  You can also choose a good time here: The link will take you to our calendar where we can arrange a time to speak.  Other options: contact us page or call 301-656-8448.

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