Cloudingo vs Dataloader.io

• The automation engine is extremely powerful. I have over 500 fields on some objects and I want to do different things with that data depending on what the master record is. I was able to configure Cloudingo do all this. i.e. set it and forget it and I just get an emailed report.
• Visualization of the problem areas is completely unique. Cloudingo has a dashboard concept with tiles and those tiles represent ways of looking at the data and potential duplicate records.
• Innovate - every suggestion I've given them they have implemented and then some. Cloudingo really pushes the pace and I am always thankful when new releases come out because they put in cool stuff that I would have never thought of.

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• The selection of objects is much better and more extensive than the Salesforce built in data loader.
• Cross referencing of fields for record IDs is easy to use. I can work through this so much more quickly than using the built in Salesforce data loader.
• Success and error files are easy to identify what needs to be fixed (errors) and identification of records created (successes), so you can quickly do spot checks in your Salesforce org after doing a data load.
• The number of rows per month for a basic package, 100,000, is great for our business.

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• I wish there were a few more merge operators. You can set merge rules based on "equals", "oldest date", etc., but there is no "contains" operator.
• Hard to use. The platform is just very complex. Not sure how you'd get around this though since this type of mass action is very involved.
• The price difference between the standard package and the pro package is a very big jump. But it has to be since the pro uses a REST API.

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• At the moment, I can't find a way to rename jobs. This would be useful to organize what was previously created hastily by techs in a rush.
• A preview of the job, especially upserts, would take a great deal of stress away from some of us (especially those who are not so confident in their ETL practice).
• A native vlookup equivalent may be a welcome addition.

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• Neglected and not used due to destructive automation
• Fear of cleaning up data
• Not wanting a human to do proper cleansing

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• Saves hours vs. manual data entry of getting records into Salesforce which saves a lot of money.
• Makes our IT group more efficient by pulling them out of standard data upload tasks that can be done by less technical folks.
• Allows the marketing department to more quickly communicate with their prospects by quickly getting them in to Salesforce, thus helping with sales.

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