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Massive Enterprise

Consumer Data Lists 

AWant to buy fresh and accurate consumer data so you can reach your target audience ?

BWant better results from your telesales team? Our telemarketing data is TPS verified!

CWant better results from your email marketing broadcasts? Our opt-in options ensure that your target audience is receptive to your emails!

DDon't want to waste your money on dead leads?  All our data is regularly updated and cleansed to ensure that your B2C marketing efforts are not wasted!

Buy consumer data

 

I run a call centre and one of the biggest issues we have is finding interested buyers, with the consumer data plan we bought from massive enterprise we were able to overcome this hurdle and sales are up! - John Seymour

 What are Consumer Data Lists?

The basics

Consumer data includes all demographic data including name, address, age, job title and education. Marriage, birthdays and injuries fall under the 'Life-event triggers' category and of course salary and spending patterns are also important factors to consider. If you then include a persons health records and social patterns then you truly get the full picture.

Not all Consumer Data companies are the same

We consult with you to understand your target audience, your competition and your business goals to help form a strategic and cost effective data marketing campaign. All our data is updated regularly and cleansed to ensure the highest quality.

How do we do it?

We have a huge network of data sources; businesses and entities that for one reason or another have to collect specific consumer data to function properly. Shop loyalty cards are a particularly useful source of data to our clients.

How can I use this data?

Consumer data can be used for any one of these direct marketing formats

  • Telemarketing - reach your customers at home or when they're out
  • Email marketing - opted-in email addresses to reach peoeple at any time
  • SMS marketing - reach people on their smartphones to get an immediate response

 

Hundreds of Variables

  • Demographics
  • Income and expenditure
  • Contact method
  • Online behaviour
  • Lifestyle and interests
  • Property prices
  • Savings and investments
  • Credit risk
  • Vehicle ownership
  • Neighbourhood characteristics
  • Individual data
  • Property data
  • Income data
  • Credit card data
  • Pensions data
  • Online data
  • Car data
  • Green data
  • Household data
  • Banking data