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      Data Management

      Transform your Lead Database with the Contact Washing Machine

      Feb 19, 2015

      4 minute read

      Bad data – whether gathered, purchased or downloaded, costs companies billions every year in lost productivity and wasted resources. As per, it costs $1 to verify every record, and this cost increases, as your data gets old.

      What brings in Bad Data?

      On an average, respondents use 3.4 sources to collect customer contact data.

      • 73% of companies collect data from their website
      • 60% collect data face-to-face from sales teams
      • 54% collect data from call centers
      • 47% of companies collect data via mobile websites or apps

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      Impact of Bad Data

      Bad Data

      How can you keep your database clean & convert it into robust lead database?

      The Contact Washing Machine enriches your data, and makes it Consistent, Complete and Correct – the three pillars for data that give a nitro-boost to your campaigns across different touch points. There are two types of Contact Washing Machine – Semi-Automatic and Fully-Automatic:

      Working of Semi-Automatic Contact Washing Machine

      It just cleans & normalizes. It works in a three step process:

      • Creates series of campaigns for passing leads through data filters
      • Triggers when a lead is created, and pushes it through each campaign in a sequence, before sending it for lead scoring
      • Batch runs old data through CWM campaigns for better results

      Semi Automatic Contact Washing Machine

      Working of Fully-Automatic Contact Washing Machine

      Built on the Alteryx platform, the Contact Washing Machine works in a three step process:

      • Cleansing: In the first step, raw data is scrubbed against a set of predefined bad values for the fields, e.g. Name, Company Name, Email etc. The app then flags bad data and separates it from the good data stream.
      • Normalization: This is consequent to the previous step, i.e. good data is normalized for standardization of values such as country, state, city, job title etc.
      • Enrichment: In the last step, the normalized data is enriched with third party business database to help sales executives get extra information for qualifying and prioritizing their leads.

      Contact Washing Machine

      Comparison of Semi-Automatic and Fully-Automatic Contact Washing Machine

      Features Semi-Automatic Fully-Automatic
      Setup in Marketo Platform TickIcon TickIcon
      Setup in Alteryx Platform TickIcon TickIcon
      Integration with Marketing Automation Platform TickIcon TickIcon
      Data Cleaning TickIcon TickIcon
      Normalization TickIcon TickIcon
      Data Quality Assessment TickIcon TickIcon
      Data Enrichment Qs Cross TickIcon
      Converting data in ready-to-use formats Qs Cross TickIcon

      Contact Washing Machine can process as much as 200K records in less than a minute, using Alteryx’s fast data blending capabilities, which otherwise takes hours. The application is absolutely platform independent, and can be integrated with CRM systems like Salesforce.

      Here’s A Contact Washing Machine Success Story

      Alteryx the leader in advanced analytics, transformed its lead database, leveraging the power of the Contact Washing Machine. With CWM Alteryx was able to get:

      • More than 200K clean records processed per minute
      • Over 40% improvement in quality of the leads
      • Upto 37% Increase in the Sales Productivity
      • 25% improvement in accuracy for Sales Qualification and Prioritization

      Want to leverage the Contact Washing Machine for Sales-Ready leads?

      Grazitti InteractiveTM, a marketing technology company, also an Alteryx Partner, works with a number of Salesforce and Marketo customers in Technology, Banking & Financial Services, Healthcare, and more. Grazitti uses the Contact Washing Machine to turn low-quality data into sales ready leads. Drop us a line at [email protected] and our experts will get back to you to discuss about your data enrichment needs.

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