Every company is using some sort of Marketing Automation to execute their email campaigns and to maintain their database. But do they know how dirty data could be affecting their output and productivity?
Every marketer know that the success of their demand generation programs depends on the quality of their data. A clean and accurate database is fundamental for success.
Bad data not only affects marketing success, but it also indirectly affects sales outcomes, finance and customer relationships – costing the company billions every year in wasted resources and lost revenue.
What problems can dirty data cause?
Here is a list of the problems that could be created by allowing your marketing efforts to run on dirty data.
- Botched delivery: Every time a marketer sends an email that does not arrive to the correct recipient you are making a fool out of yourself and your company and costing your team marketing dollars.
- Wrong gender: As a consumer, there is nothing worse than having an email directed at you in which they think you are a different gender. It shows you don’t care about them at all – and it’s just rude.
- Misspelled or incorrect names: The whole point of having the ability to put in a token in your email campaign to auto populate is to get it right and thus create a bond between marketer and consumer – for example addressing them by their first name. If you get the information you will not only get it wrong and embarrass yourself – your credibility will go straight out the window.
- Multiple emails to the right person: No one likes a spammer. Period.
- Right person, wrong size: When you buy a clothing article for a loved one, you always make sure to get the right size for them. As a marketer, same thing goes. Don’t send an email offer for your plus-size database featuring clothing that only runs in petite sizes.
- Wrong location used for geo-targeting: If you are sending out an offer that can only be fulfilled in a certain state, make sure not to blast your entire database. Always think of what region you are targeting.
All of these problems streaming from dirty data will result in lost revenue, wasted resources, lower productivity and dupes with inconsistent information
How to correct the dirty data problem
- Standards: Take the incentive and request that your team begins practicing standardized data entry formats and requirements companywide to ensure critical fields are complete and formats are consistent.
- Scrub and clean: Never upload lists or introduce the leads into your CRM or marketing automation system before validating the quality of each lead – regardless of where it came from. Even if you are uploading a list of people from an event – you need to sort those leads based on whatever categories are most important to your company. Take the time to clean your data before uploading it into your database.
- Ask for help: Enlist your customers and prospects to clean and update their own data by using lead nurturing techniques. By encouraging prospects to give you accurate data in steps, you can capture more accurate data for your marketing programs throughout time.
Where should I start?
AgilOne, the predictive analytics program, comes with a data profiling and ee-duplication tool.
Along with predicting your customer’s next move and helping you act upon it - it removes duplicate records and prevents the creation of new duplicates.
Remember - feeding marketing programs dirty data can take a toll on your marketing budget, sales productivity, your reputation and your company's brand and image.