'Collaborative Commerce':The Big Kahuna

Kate visits www.skateboardingismyworld.com. She prowls the web site for her favorite skateboard, which she busted up pretty good in a bad fall at a recent X-Games event. She's been to this site many times to purchase much skateboarding paraphernalia, and the site greets her by name. She finds the skateboard that she needs, but realizes that it's the new version of her old standard, and she's worried about the new, larger-size wheels they have as the standard configuration for it. She clicks on the Talk To Me Now button, and via Voice over IP, she connects immediately with a knowledgeable customer service rep. She explains that she'd like the skateboard with the original size wheels. The customer service rep, through collaborative web browsing, shows Kate how she can custom order the skateboard with her preferred wheel size on the web.

Kate hangs up with the rep, and adds the customized skateboard to her online shopping cart, and proceeds directly to checkout. Since she's a regular, the site automatically discounts her purchase 20%, and presents a full screen with her Billing and Shipping address and credit card information pre-filled in. She selects same-day shipping, since she can't skip a beat practicing for the next competition. She confirms the order and the price on the next screen, her credit card transaction is processed, and she's off to school in time for homeroom.

A local vendor of skateboarding equipment gets an electronic order for Kate's skateboard, and the request for same-day delivery. They put on the original wheels, and deliver it to Kate's door by 2 pm, just when Kate returns from school and is ready to once again hit the local boarding course.

Meanwhile, skateboardingismyworld's logistics package is notified that they just dipped beneath the pre-set threshold for stock on that skateboard. An order is automatically sent to all component manufacturers of the board for re-stock.

ERP and CRM: Their trademark functionality

Let's review the very high level attributes of both ERP and CRM systems, in order to set us up for evaluating the state of various vendor C-Commerce solutions.

ERP

Enterprise Resource Planning, which came into its own in the early 90's, is typically comprised of the following key high-level components:

• Manufacturing and Logistics
  
  
• Finances and Accounting
  
  
• Human Resources and Payroll

For a complete definition of the scope of ERP, please refer to the article: Essential ERP: It's Functional Scope.

ERP has extended backward, outside the organization through e-Procurement (electronic Purchasing) and Supply Chain Management (Distribution and Inventory Management).

CRM

Customer Relationship Management, which has followed on the heels of ERP and is just now coming into its own, can be thought of to comprise the following key high-level components:

• Sales Force Management (SFA)
  
  
• Enterprise Marketing Automation (EMA)
  
  
• Customer Interaction Center (CIC) - formerly called Customer Service; now with a broadened scope.
  
  
• e-CRM
  
  
• Field Force Automation (FFA)
  
  
• Professional Services Automation (PSA)
  
  
• Partner Relationship Management (PRM)
  
  
• Analytics

'Collaborative Commerce': ERP, CRM, e-Procurement, and SCM Unite! A Series Study

In the early 90's, ERP came of age. Everyone had to have the functionality ERP packages promised. Since then, as Web and Internet technologies have matured, CRM on the front end, and e-Procurement and Supply Chain Management on the back end, have come into their own.

Now in 2001, the catchphrase is "Collaborative Commerce," where we unite all of the above elements into one coherent system within and between organizations. This is the Big Kahuna, the zero latency, fully transparent, 360 degree exposure that is the stuff systems integrators dream of. Is it here? Are the technologies mature enough? Simple enough?

A Data Strategy

Shifting from acquisition to retention transfers the goals to a focus on establishing loyalty, advancing the relationship and building a sense of community, participation and affinity. The retention data strategy, as with prospecting, also must be built on determining which customers meet that "ideal" criteria.

Even minimal improvements in retention rates can lead to big improvements in profitability and overall ROI. With this in mind, look for factors that will feed back into the acquisition cycle to trim marketing costs and/or increase success rates. Analyze the trends in the length of customer relationships to help determine if something can be done to avert customer losses at critical points along the way.

All organizations that regularly update customer data should review and analyze it to pinpoint opportunities to up-sell, cross-sell and service sales. For example, sales data can reveal which customers are due for product/service upgrades or warranty extensions.

To guide development of a retention data strategy, answer the following:

* What are the characteristics of the best customers?

* What keeps them loyal?

* What's the potential for developing similarly loyal customers?

* What are the information and service needs of established customers compared to those of prospects?

* What prospect information, if any, needs to be saved once a relationship is established?

* Are there changes the organization should make as the relationship evolves?

* Why were products returned?

* How many service calls did customers place and why?

* How were service calls resolved and how long did it take?

* Why does one set of customers respond to opportunities when another doesn't?

Supporting Acquisition

The first goal in the acquisition phase must be deciding which prospects most closely match the profile of an "ideal" prospect. Cherry pick prospects and resist chasing those that don't meet acquisition criteria. Keeping marketing efforts sharply focused will cut costs and increase your CRM return on investment (ROI).

Ongoing assessments of marketing campaigns must be made to determine which are most effective in bringing in new customers. An effective CRM system will assign each contact to a specific marketing campaign, "tagging" the data for continual analysis of marketing ROI and effectiveness in identifying likely prospects. By tracking expenses tied to leads generated, customers acquired, and potential and realized revenue, campaigns can be shaped to individual customers and prospects based on specific responses or effectiveness rates.

The needs and interests of individuals, of course, can be best understood by examining data from individual prospects. But aggregate data can better forecast which groupings or classes of would-be customers respond best to marketing appeals. This broader view can efficiently guide development of products or services to satisfy specific target groups.

A CRM System Needs A Data Strategy

An underutilized customer relationship management (CRM) system - or one that cannot match its owner's expectations - will reflect poorly on both the vendor who sold it and the IT manager who authorized the purchase and installed it. Both, however, can help successfully manage such expectations (and add value to their respective roles) by wisely counseling about the strategic context into which a CRM system must function.

Simply put, the market includes plenty of CRM products - embracing a variety of technical approaches - for gathering data from each contact with a customer or prospect. While each can support customer acquisition and retention efforts, data collection cannot be an end unto itself. In fact, a data strategy is needed to target and keep the right types of customers.

For vendors and IT managers to help enterprise users, this is an overview of how they can develop and implement a data strategy to guide both the acquisition and retention phases of a marketing campaign - within which a CRM system can be optimally flexed.