Friday, February 6, 2009

Is Database Marketing on Your Marketing Operations Radar?

How many times have we heard in the B-to-B marketing press the past several months about the importance of increasing content relevance to our prospects and customers, better engaging them through digital marketing vehicles and improving our ability to generate and qualify marketing leads? Yes, all extremely important priorities for us as marketers, however, if you're a $100M+ company none of this can be accomplished in an efficient and effective manner without the back-office infrastructure to support it. And we all know how difficult an infrastructure conversation is in this economic downturn. For the purposes of this conversation, let's focus on the area of database marketing.

Even the best marketing organizations struggle with consistency in database marketing processes; consolidation of prospect and customer data across the multitude of databases in use across the world; cleansing of data to prevent a "bad data in = bad data out" scenario; and overcoming the complexity of data analysis and list pulls, especially with the increased data flow from digital marketing activities. In a recent best practices study, we spoke with (12) multi-billion $, complex organizations representing in total over $250B in revenue. When asked to indicate their marketing organization's satisfaction with the components of database marketing, some of the most fundamental elements of this area were identified as being the weakest. . . . including data cleansing, digital data integration and contact management.

So enough about the problems out there: that's the easy part to identify. What are a couple concrete things that you can do to help improve marketing's "back-office", especially in these difficult economic times when "throwing money" at the problem is not even a possibility?. . .
  1. Establish a global database marketing council or team to set standards and govern processes and technology. (yes, virtual if need be and it will take more time out of your day . . . but this will pay off in the long-term)
  2. Leverage third party partnerships for external expertise and best practices (e.g., data cleansing). Establish an approved vendor supply list to achieve economies of scale and better govern data standards.
  3. Develop a process to enable the average marketer to obtain a highly targeted list for their activities or campaigns. A 100% self-service model will lead to supplier proliferation, poor leverage of scare marketing resources and an inability to leverage the power of your data. Ideas include: establish a relationship marketing team, deploy a shared services model to get dbse. marketing experts closer to the field (more on shared services to come in future blogs), create an expert analytics team that can do some of the "heavy lifting" for your team's larger projects (e.g., predictive modeling).
  4. Reduce and consolidate disparate data sources. If you're lucky enough to have or pursue a universal data mart or EDW then great. For the rest of us, another option may be deploying an application that serves as the front-end for multiple databases. This option is available through several marketing automation vendors.
  5. Ensure your database marketing and lead management teams are working together if not part of the same group. This is particularly important for establishing a closed-loop lead management process.
  6. And last but certainly not least, establish metrics and targets to measure the performance of your database marketing capabilities. (e.g., data quality indicators, lead generation data to track the success of list pull activities, response times and internal customer satisfaction if you're leveraging a shared services model)

If you're fortunate enough to have a marketing operations individual or team, then turn to these folks for help in deploying the process rigor needed to initiate these actions.

1 comment:

  1. Thanks for a great post. In my experience, database marketing - including great segmentation strategy, data quality initiatives and privacy best practices - are often neglected due to the complexity of fixing the problems. And much of the data quality issues are a result of factors outside of your control - employee turnover alone means that 20% or more of any given B2B database goes stale each quarter. I ran a webinar for Salesify on this very topic if anyone is interested in learning more: http://www.salesify.com/webinar-data-quality-counts/

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