B2B marketers are certainly aware that business marketing data degrades quickly. Most know that there is no such thing as a “good list”. Keeping data clean is critical to lead generation success. Yet, it is frequently done wrong.  

To reveal segments with higher probability of generating leads, compare your marketing database, which could number thousands of contacts, to your customer database. For example, after sorting your customers into categories, you may find that most of them fall into three SICs and one revenue range. Next, extract contacts from your marketing database with the matching three SICs into separate test groups in addition to one or two other groups that seem like they should perform well.

Break each of the resulting segments into small discrete lists of a few hundred names, test each segment with marketing activity including tele-prospecting calls. The categories that match your customers have priority. Rank by other pre-determined classification, such as company type or region. Focus on the top two segmented and prioritized lists, then move down.

The sales opportunities generated from these small tests will reveal predictable segments that warrant building full marketing programs. The test phase confirms the market segments that are more likely to buy and are therefore worthy of marketing investment and resources.

The process doesn’t end with a single round of data cleanup, segmentation and prioritization. Ongoing testing to differentiate characteristics reveals the most valuable segments. This knowledge can be predictively applied to generate higher return on future programs.

So, instead of contacting all names in the databases or tossing out every name and starting over, use segmentation and prioritization techniques to focus on the quality list segments and predict the likely success of B2B marketing programs. Continued deployment of this predictive relational equation helps marketers:

• Balance return against investment and determine optimal program deployment
• Develop the intelligence to fully fund the right model for future programs

The PointClear Relational Segmentation approach provides companies with the market intelligence they need to fully fund and roll out programs targeted to high-return segments. This model has increased individual campaign results at PointClear by up to 50 percent and simultaneously decreased costs by as much as 35 percent.

Want to know more? We have an ebook that provides more information.