5 Steps to Clean up your Marketo Database

5 Steps to Clean up your Marketo Database

Healthy databases make happy marketers. There are many benefits to clearing worthless leads out of your Marketo database:

  • Give your organization a reputation of paying attention to detail by not pestering leads outside your targeted demographic with endless messaging.
  • Step down a tier in Marketo’s database-size pricing to immediately raise your marketing automation ROI.
  • Instantly increase your lead quality by purging the bottom-of-the-barrel leads—those with a negligible chance of interacting with your organization, let alone purchasing a product.

Begin your cleanse with these 5 steps and enjoy all the benefits of a healthier database.

#1 – Build a list of Inactive Leads

Inactive leads are easy to identify using the inactivity filters in smart lists. Consider using a combination of all the following filters when building a list of leads for removal:

  • Lead Created: Before your timeframe of activity history. This is to exclude leads who entered the database recently but have not had a chance to engage yet.
  • Not Visited Web Page: Is any
  • Not Program Status was Changed: New Status is a list of the program statuses that you consider to be engaged. “Tradeshow – Visited Booth”; “Webinar – Attended”; “Online Advertising – Converted”, among others.
  • Not Clicked Link in Email: Is Any. If you are nervous about this one, you can use Not Opened Email to be extra safe. But understand that some email clients automatically open emails to classify spam, so you’ll likely get some false actives.
  • Not Filled Out Form: Is Any
  • Not Activity was Logged: Subject is Not Empty. This filter will exclude leads who have had any SFDC activity in your timeframe.
  • Unsubscribed: False. As always, you’ll want to make sure you keep your unsubscribed leads. That way you won’t message them if they find their way back into your database.

Inactive Leads Smart List Filters - Digital Pi, Marketo consulting*NOTE: One thing to remember here is that when using inactivity filters, you want to use the “ALL” filter logic. “ALL” turns the filters into “NOR” logic: they haven’t visited a web page, nor have they filled out a form.

Take a look here for a visual of this smart list. I’d recommend using 1-2 years for the timeframe of the activity, as long as the type of activity is available that far back. (Some types of activities are archived after 90 days.) Experiment with dates and view the number of leads returned to help you decide how long you are comfortable with. Also take your sales cycle into consideration. If you have a very quick and transactional deal cycle, then you might want to shorten the time frame to 6 months.

#2 – Build a list of Invalid Leads

Leads are marked “Email Invalid = True” when there is a hard bounce upon an email send. You can identify the leads who are invalid, and the reason for the hard bounce by building a “Leads by Invalid Reason” Lead Performance report in Analytics. For the smart list, filter for leads who are “Email Invalid = True”, then Group Leads by “Email Invalid Cause”. You’ll see reasons such as:

  • 550 [internal] [oob] The recipient is invalid.
  • 550 Requested action not taken: mailbox unavailable
  • 550 5.1.1 User Unknown

These email addresses don’t exist and/or are not deliverable, so there’s no reason to keep these leads. If you see a reason such as:

  • Invalid data type in field Email Address

Take a look at the email address of the lead, and see if it’s a punctuation error you can fix (i.e. a comma at the end of the address, or two email addresses in the field). When you’ve fixed the address to a correct format, change “Email Invalid” back to “False”, so that you can attempt to message this lead again in the future.
Once this is complete, make a smart list of leads who are “Email Invalid = True” to be used for removal.

#3 – Review the Sources of your Bad Leads

Don’t you want to know where all these useless leads are coming from before you purge them? Discover your low-quality sources with a simple Lead Performance report grouped by your Lead Source or Lead Source Detail field. For the smart list of the report, use two “Member of Smart List” filters and include the inactive and invalid lists built above. Sort leads “Descending”. Who’s at the top? You may not want to renew your contract with that vendor next year.

#4 – Back up your Leads

Before you delete your leads, export CSVs of each smart list with all columns to back up all data possible. There’s no cost to keeping these leads, and knowing you can easily import the leads back into the database reduces your stress level when hitting that final delete button.

#5 – Delete!

Using the smart lists, highlight all leads and delete. Go ahead and remove them from CRM too, since you’ve included the SFDC inactivity filter. Don’t be nervous! Think of it as taking out the garbage, and enjoy a cleaner and healthier place to productively manage your leads.

bob@digitalpi.com

Over the last 20 years, Bob has built, managed, and advised marketing teams of technology companies, including Arbortext (PTC), Brocade, CA Technologies, LLamasoft, GXS, HAHT Commerce, Intuit, QAD, Sybase, and WorkForce Software. Bob thrives on solving business problems with marketing technologies and will not quit until a suitable solution is found.

  • July 19, 2016

    Solid info and process – thanks for sharing. I recently wrote a blog post with Craig Elias, author of SHiFT!, on a process that leverages bounced emails. My recommendation would be to modify Step #2 by saving this list outside of Marketo and running it through Craig’s process. His process could yield some healthy opportunities. Here’s the link to the blog post: https://www.leadgnome.com/blog/take-trigger-selling-next-level-account-based-intelligence

  • Kevin Payne

    Leave reply
    August 4, 2016

    A well written and very thorough article full of good ideas! Nicely done Nate! Keep up the good work! Kevin Payne

  • December 5, 2016

    Great article. I feel like all the other articles was finding about database clean-up were pretty useless.

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