Technology sales prospects

Zero in on your best Technology sales prospects

We're almost to the end of first quarter in 2011. It's time to have a quick look at our technology marketing and our data. I've a question. Are you still struggling to reach the sales targets? Are you in short of prospects from technology markets. If yes, here's some real meat for your marketing.

We have recently updated our B2B technology data list with more counts and segments. In last 2 months 12 vendors bought B2B list based on these criteria. Here's the most popular list:

• Oracle ERP Users list
• JDE list (Accounting and finance professionals) 
• Oracle DB  (US & Canada)
• IT Executive Mailing List
• Oracle decision Makers list
• IT decision Makers (manufacturing corporations )
• JD Edwards software( Nordic market) 

They were very happy to give testimonials on how this B2B data helped them to increase response rates, as well as profits.Click here to submit your request.

Success Rates from niche B2B data:  Benefits

• Increase first call contact success rate by 65%
• Decrease in cost of sales by 35%
• Improved conversion rates up to 3x
• 25 day ROI

Where are your customers? Tell us to reach them!
All you need is to give us your criteria and we'll deliver sample data. Get verified data before you buy from us. Get counts, order and explore B-to-B marketing opportunities without wasting your time and money.

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Amplify your IT Marketing data?

Before you set to uncover the data issues residing in your data file  it's imperative to answer few questions. Answer to these questions gives you the blue print toward providing the solution.

1. What's your data quality goals?
2. What does high quality data look like?
3. What process did you follow to reach here?
4. Why is optimal objective of data quality goal?
5. What are the normal issues to reach these goals?
6. What are you going to do to achieve the Data Quality goals?
7. What are the top data churn confronting your business?

Step One: Identify the Problem

Most biz know the issues with data, such as duplicate, invalid, junk or untrustworthy data. But they are not aware of the quantum of issue residing in their system. 

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