October 10

Have a minute? Brian Carroll reveals how sales teams pay dearly for cheap data

Marketing Strategy

12  comments

The temptation to buy data at pennies per contact – especially when you have limited resources – can be overwhelming.

But whatever you do, you must resist.

In the short video below, taken at MarketingSherpa’s B2B Summit in Boston, Brian Carroll explains why.

[youtube clip_id=”ytBYIuNaxnM” width=”600″ height=”400″]

Did you find this valuable? If so, remember, this is merely one of 60,000 minutes of revenue-driving information that is unveiled at MarketingSherpa’s B2B Summit. There’s obviously a lot more where this came from and, even better, there’s still time to discover it all. Just register for the San Francisco summit, October 24 and 25.

About the author 

Brian Carroll

Brian Carroll is the CEO and founder of markempa, helping companies to convert more customers with empathy-based marketing.

He is the author of the bestseller, Lead Generation for the Complex Sale and founded B2B Lead Roundtable LinkedIn Group with 20,301+ members.

  1. @Mitsu Fisher Yes, I totally agree about the value of quality data. As the old adage goes, “if I had 8 hours to cut down a tree, I’d spend 7 sharpening my ax.” If you want to be a great b2b marketer, you need to know how to get the right data and lists with the right people in the right companies.

  2. @Mitsu Fisher Yes, I totally agree about the value of quality data. As the old adage goes, “if I had 8 hours to cut down a tree, I’d spend 7 sharpening my ax.” If you want to be a great b2b marketer, you need to know how to get the right data and lists with the right people in the right companies.

  3. You hit the nail on the head Brian, great video. In my experience, list accounts for perhaps 65% of results. If you don’t take great care to make sure you are working the best possible list, your chances of success diminish greatly. The difference can be as stark as getting one lead per hour or one lead per week. Response rates can range from zero to 15%. None of us can afford cheap data.

  4. You hit the nail on the head Brian, great video. In my experience, list accounts for perhaps 65% of results. If you don’t take great care to make sure you are working the best possible list, your chances of success diminish greatly. The difference can be as stark as getting one lead per hour or one lead per week. Response rates can range from zero to 15%. None of us can afford cheap data.

  5. Yeah, it’s really about optimizing the time of the salesforce team because what you do with those leads is a majority of your time resources. Use them wisely.

  6. Yeah, it’s really about optimizing the time of the salesforce team because what you do with those leads is a majority of your time resources. Use them wisely.

  7. Great video cast Brian! I cannot agree with you more. You know in many instances newbies in the field are just looking to buy up lists at low costs but they end up learning the hard way that it just costs them more in time, money, effort etc. We were able to create a tool that is taking the marketing industry by storm called XVerify where we validate the data and can measure the quality of your lead in real time before it even hits your database. Unfortunately I won’t be at the summit this year but maybe I can plan to make it next year.

  8. Great video cast Brian! I cannot agree with you more. You know in many instances newbies in the field are just looking to buy up lists at low costs but they end up learning the hard way that it just costs them more in time, money, effort etc. We were able to create a tool that is taking the marketing industry by storm called XVerify where we validate the data and can measure the quality of your lead in real time before it even hits your database. Unfortunately I won’t be at the summit this year but maybe I can plan to make it next year.

  9. Wouldn’t you rather have a database of 100 records with content rich data over a 1000 names and addresses?

  10. Wouldn’t you rather have a database of 100 records with content rich data over a 1000 names and addresses?

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