Intelligent Metrix

Data to Metrics to Insight to Intelligent Decisions

B2B CRM: The Right Contact Mix for Your Customer Relationship

You’ve spent years gathering contacts into your databases.  You’ve implemented a data quality practice that is now starting to give you a solid picture of your universe.  It is now time to classify your contacts.

Invariably, your database is more than just purchasing/decision maker contacts.  All departments have gathered people’s information depending on the purpose.  It offers a window into your business dealings.  It also offers a window on your ability to market and sell.  Just as you consider vehicles, content, and message to deliver to your database, you also think about who you are reaching and who can be converted.

SOA and MDM initiatives are great because they bring together a full picture of interactions with the customer as well as who is part of those interactions.  But, not all contacts are created equal.  Just as not all customers or companies are created equal.  It is the first thing that is considered when determining targeting strategies.  The size of a database is typically determined based on the silo it is intended to help.  Marketing wants decision makers, finance wants accounts payable, customer support wants end users, investor relations wants analysts and media.  By themselves, these data silos serve a purpose.  Together, they can show a picture of where your awareness, message and brand really are.

A good  test once consolidation of data bases is done, or even within your CRM system alone if it receives lists and feeds from other internal sources, is to classify contacts based on their primary interaction with your company.  Everyone in your database has had a reason to connect.  Bringing these reasons into a standardized category will help determine the value they bring to a marketing program, customer relationship, or evangelist role.  Monitoring the ratios of these groups within a cusotmer relationship and firmographic data can give insight into the ability to grow a relationship, if it is at risk, or there is no relationship and the company serves another purpose.

While as marketers we typically look at the entire size of our database to determine if we have enough contacts to convert to leads, if those leads are weighted towards a low number of companies, or they are not the right contacts, then our efforts can be wasted.  With the cost to acquire customers and contacts expensive, having a mechanism to determine when to purchase lists and how much to purchase will refine the amount of resources and budget needed.  In addition, messaging and engagement strategies can be modified to align to the type of relationship outcome you intend.

So, rather than thinking about personas when you need to target, think about them strategically and as an indicator of the strength of relationship with your customer.

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Stuck in First Gear

porscheBig investments were made in recent years in IT.  IBM, Oracle/Siebel and SAP lead the market and were successful not only with the multi-national enterprise companies but, also with mid-sized companies.  There are a lot of companies out there that have purchased application and data management/data warehouse solutions only to find themselves using a portion of what it could do.  It’s like driving a Porcshe in first gear.

There are some fundamental reasons for this, outside of the fact that companies may feel it is the fault of their sales execute selling them the wrong bill of goods.  IT will blame the business for not knowing what it wants.  The business will blame IT for not getting it.  Doesn’t really matter, there is plenty of blame to go around.  What matters is that now you have a solution that isn’t giving you the benefits that it really could and should be.

Maybe I’m a bit biased since I’m the data chick.  Well, more than a bit.  Regardless, I think that from a data management perspective, companies are failing.  The maniacal focus on process efficiency has drowned out the fact that process runs on data and feeds data.  This focus has put data in the back seat too long and now when we need it to better understand our customers, our business, and make decisions, it is sorely lacking.  Our data lacks unity, structure, definition, and most of all purpose.  Companies simply cannot leverage their information except at very basic levels.  When things are good, this may be okay.  When things are bad, this is a real problem.

What makes this even more sad, is that companies are looking to spend more money on applications and data infrastructure to ‘fix’ the problem.  The promise of the new model and more sophisticated bells and whistles that will solve anything you throw at it is just marketing.  Until you can understand and control what you already have under your hood, getting something bigger, better, and shinier isn’t going to help anymore than it does now.  So, there was no ROI on existing purchases and there won’t be any ROI on new purchases.

There are two things companies need to do to make the investments in enterprise solutions worthwhile:

  • Clean-up the back-end data management practice so that it is fluid with business process and application usage.
  • Have a clear data management strategy for new applications that is fluid and scalable outside of application databases.

Your company may already be embarking on SOA or MDM projects.  But, have you looked at how these new practices will support applications outside of changing the oil?  Can the data drive process?

Today, applications are bogged down because data is treated as something to put in the trunk and horde.  Until data is thought of as fuel, you’re IT investments will stay in 1st gear and never get to 6th.  Now how fun is that?

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