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Understand Your Best Customers To Find New Revenue Opportunities

Manufacturers have traditionally sold products through sales channels with a one-size-fits-all approach. However, as the marketplace becomes more competitive and customers have more options, they are turning to data-driven marketing solutions to better target end-users.

Manufacturers have traditionally sold products through sales channels with a one-size-fits-all approach. However, as the marketplace becomes more competitive and customers have more options, they are turning to data-driven marketing solutions to better target end-users according to their individual needs and preferences. Just as importantly, manufacturers are using new ways to more fully integrate with their sales channels to increase loyalty, acquisition and retention.

Why the change? Manufacturers are learning from retailers in this regard. Rather than using traditional incentives and mass messaging to push products, they are learning to focus on customers’ needs by understanding who the customer is, what different customers buy, how they buy and what influences their purchases.

With more sources of customer information and new technologies to evaluate data, manufactures are using data management and marketing analytics to overcome some longtime challenges and reach some important goals.

Manufacturers & Data: Four key stages of a new relationship

  1. Manufacturers have long sought a seamless, adaptable process to integrate numerous data sources residing in multiple silos to create a comprehensive, 360o customer view. With technology advances they are finding that process, and can include internal information like tradeshows, customer loyalty programs and purchase history, plus external information from third parties.
  2. More than one manufacturer’s targeted marketing campaign has fizzled as they faced data quality issues regarding customer retention and acquisition. Now, data quality and integration solutions standardizes, cleanses and enriches customer data with missing information, including firmographics such as annual revenue, geography and size of company.
  3. They have also been frustrated by not having proper customer intelligence to effectively target their customer base. Using custom analytics and business intelligence solutions, manufacturers can now profile customers and prospects to identify top customers, prioritize marketing investments, strengthen customer relationships and increase sales.
  4. Manufacturers finally have the power to better manage sales channels with data-driven market intelligence to improve partner relationships and sell more products. And they are learning how to automate marketing communications through targeted campaigns and email deployments based on customer segments and triggered or event-driven actions.

Cleaning up the Mess: How One Manufacturer Transformed Data into Actionable Insights

As manufacturers seek better ways to target their customers, many are finding that their marketing databases are less than accurate, with incomplete and inaccurate data that severely impacts their ability to clearly define and understand end-users and sales channels. Meanwhile, these manufacturers generally deal with huge quantities of information from multiple, disparate sources. Many of these sources are often stored in legacy systems, further limiting the ability to integrate and analyze for comprehensive customer intelligence. Too many manufacturers have gotten stuck at this point, or limped along, trying to make the best of their data mess.

Here’s how one company, an international commercial vehicle manufacturer with $10B in sales, was able to transform messy data into marketing intelligence:

Data Challenge

First, the manufacturer needed to shift from a vehicle-centric marketing strategy to a customer-centric model. But inaccurate and incomplete data blocked their ability to clearly define and understand customers. Several definitions of “customer” existed, depending upon where the vehicle was in the purchasing life cycle. The company was making assumptions as to the best contact at a company level. Without a comprehensive understanding of which contacts were the decision-makers and what was driving their purchase behavior, market growth was stalled, important client relationships were damaged, and up-sell and cross-sell opportunities were lost.

Also, their poor customer intelligence affected dealer relationships. This vehicle manufacturer realized that it needed to improve channel partnerships and provide dealers with marketing intelligence to help drive end-users to the dealership.


Turning to data management technology, the company’s first step was to integrate fifteen disparate source systems, including a variety of internal information such as tradeshows, customer loyalty programs and vehicle finance data, plus external information supplied by public sources. The manufacturer then used that same technology for a flexible and adaptable solution to integrate new and changing sources of information as they became available.

They made sure they were getting through to key targets, applying custom cleansing and standardization rules to particular large corporate parent-child relationships, e.g., General Electric; GE Energy; or GE Power and Water. They also worked on normalizing the variations in company names that result from data being housed in various internal systems, like 3M Company rather than its former name, Minnesota Mining & Manufacturing, 3M, MMM, 3M Co. and various abbreviations of the former name. It may seem like just a few letters difference, but to a marketer, those few letters can create a maze where dollars, time and resources are lost never to be recovered.

They also committed to staying current, incorporating National Change of Address (NCOA) as part of the regular marketing database build on a quarterly basis.

In another key move, The manufacturer enhanced its ability to know where buying decisions were made, adding relationship identifiers with customized match rules to identify specific site locations, such as company branch sites, multiple brand dealers, and other locations where important demand may be generated, separately from larger corporate relationships.

The bottom line? Early results have validated an immediate positive ROI due to more accessible data and a singular version of the true customer. Engagement metrics have also improved dramatically by segmenting customers for differentiated marketing programs, which has further enabled advanced customer analytics.

Having cleaned the data significantly, they can now use recency, frequency & monetary (RFM) analysis and lifetime value analysis to understand the future migration of customers among RFM segments. That intelligence enables them to spend marketing dollars smarter to better support their dealers and the enterprise.

For this manufacturer, searching through the data maze to find and understand their best customers is already paying off, with a host of new revenue opportunities in sight.

Anders Ekman is president of DataMentors, a full-service data quality, data management and business intelligence provider that leverages proprietary data discovery, reporting and analysis, campaign management, data mining and modeling practices to identify insightful customer sales and marketing directions.

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