The problem of dirty data and why every sales and marketing leader should care

It’s dirty data week on the Funnelholic.  And in honor of this theme, we have webinar this Wednesday, Sep 18 2013: The Impact of Dirty Data on Marketing ROI and How to Avoid It.

Today’s post is from Brian Hansford, a Director with Heinz Marketing. He is a passionate about the need for clean data. (I mean PASSIONATE). He is the perfect guy to talk about the topic. Enjoy the content after this “dirty data” pic from Duncan Hull.

data cleanse, marketing data

What is dirty data and why should we care about it?

Bad data is like bad fuel for a car.  Fuel that has lots of sediment combined with sugar in the gas tank will pretty much destroy the machine.

Dirty data is outdated, non-normalized, poorly entered and maintained, full of spam traps and misspelled names, lacking lead sources, and loaded wrong phone numbers and incomplete records.  Dirty data can render any database ineffective.  But for marketing organizations, dirty will cripple any demand generation and customer marketing using a Marketing Automation Platform.  And once dirty data gets into a MAP, the negative effects can permeate the entire organization like a disease.

What are the implications for bad data for your marketing campaigns?

In my opinion, data management and data hygiene are probably the most overlooked components to a successful marketing automation initiative, right after content.

According to Sirius Decisions:

  • 25% of the average B2B database is inaccurate
  • 60% of companies surveyed had an overall data health scale of “unreliable”
  • 80% of companies have “risky” phone contact records

The implications are critical and completely underestimated.  I recently learned of a blacklisted publicly-traded company with an enterprise marketing automation platform.  This company is heading into Q4 and like most B2B organizations have a huge focus on solidifying their revenue pipeline to close the year.  Because they were blacklisted by ISPs, their outbound marketing efforts were effectively shut down.  Think about the implications in this scenario: A stalled pipeline with no funnel-stage marketing.  Limited forecasting. No marketing air cover. No nurture campaigns. Limited promotion of events. Missed revenue targets. Falling share price. CAN SPAM Act complaints and lawsuits. Board meetings. Terminations.

Some people may think the scenario is dramatic.  I don’t.  Notice how I didn’t mention anything related to sender scores, campaign response rates, email deliverability, click-thrus, bounce-rates or unsubscribes.  Yes, dirty data impacts all of the tactical campaign performance metrics.  But data hygiene is much bigger than email campaign performance.

Data hygiene and data management is strategic to any marketing efforts with massive implications on revenue generation and customer engagement and the CMO needs to take it that seriously.

What are best practices for maintaining clean data?

Start with a plan and work the plan.  Keeping data clean isn’t a one shot deal where a CSV file can be pulled and sorted and imported back into the CRM or marketing automation platform.  Marketing Automation and CRM platforms need regular updates, health checks, de-dupes, and data appends. A database will have a natural decay of contact data because people change jobs, companies go out of business, and mergers happen.  All of these events directly impact the effectiveness of a database.  Keeping the database healthy is strategic to maintaining a strong revenue pipeline.

Keeping data clean should take these steps:

  1. Establish a data management strategy – Define the standards for complete and normalized records and manage how the database grows and where records come from.  Define the minimum standards for deliverability rates.  Establish requirements for data providers.
  2. Check your database for a baseline of health – How bad is it? Get a database health scan before implementing the strategy or randomly buying tools or hiring consultants.  A good health check should identify spam traps and determine record completeness at a minimum.
  3. Budget for data hygiene in 2014 – Imagine the situation where in July 2014 your email deliverability tanks to 80% and pipeline opportunities decline. Data hygiene is an investment that builds marketing automation effectiveness and drives revenue!
  4. Maintain Regular Maintenance and Updates – Regular maintenance keeps the machine running smoothly and efficiently with the best performance.  Here are just some of the items to monitor and manage:
  5. Deliverability – anything below 90% is a red flag.  Monitor the soft email bounces – are they increasing over time? Why are soft bounces happening?
  6. Opportunity pipeline growth – Are conversions and opportunities decreasing?  Many factors go into this but even the best content and campaigns will fall flat without a healthy database.
  7. Reputable Data Sources and Partners – Don’t use the offshore list brokers that offer contacts for pennies on the dollar.  You get what you pay for.
  8. Monitor sender scores using services like ReturnPath –  This is especially critical for marketing organizations using dedicated IP addresses for outbound marketing.  The higher a sender score, the better the reputation which helps ISP’s monitor and allow emails from trusted sources.
  9. Prevent Duplicate Records – Have a process to clear out and merge duplicate records.
  10. Append and Update Records – Keep records up to date with a data provider to ensure the proper taxonomy, addresses, phone numbers, email addresses, and syntax are correct.
  11. Segment Old Records – Don’t delete old or outdated records completely.  I recommend placing old records in a quarantine or sandbox that is kept away from marketing and sales operations.  Even after de-duplication and data append, old records may be needed for an audit or opportunity research.
  12. Contact cadence and governance – Who can send outbound communications, when, how often, and who receives the messages?  Set a clear policy that the entire organization understands.
  13. CAN SPAM – Does your marketing operations team understand CAN SPAM requirements for the US?  What about Canadian and EU requirements? Ignorance is not the same as innocence when trouble arises.  The US Federal Trade Commission offers these guidelines for compliance.

Clean data is a competitive advantage and an investment that has a direct positive impact on driving revenue, branding, and customer engagement.  Operate a data management plan now before hitting a crisis point.

Again, we have a webinar this Wednesday, Sep 18 2013 featuring Matt Heinz and Mary Firme: The Impact of Dirty Data on Marketing ROI and How to Avoid It.

Craig Rosenberg is the Funnelholic and a co-founder of Topo. He loves sales, marketing, and things that drive revenue. Follow him on Google+ or Twitter

  • Caren Bailey

    For more on how to clean up dirty location data check out http://www.placeable.com

  • Scott Miller

    We have founded that social is a great way to keep data current – after all, who knows better than the individual themselves? Check out Social123 for more on the topic

    BTW – Meagan Eisenberg of DocuSign plugs Funnelholic yesterday on our webinar on the same topic – here is a recording https://www4.gotomeeting.com/register/731055983

  • Michael Griebenow

    Great post Craig and Brian, you have given
    readers a lot to think about. I love the addition of deliverability to your
    evaluation of data quality, it’s an aspect many overlook. One of our clients
    contacted us for their data quality issues and in my post “The Impact of Dirty
    Data (And What One Marketer Did About It)” http://ideaexchange.quarry.com/2011/09/the-impact-of-dirty-data-and-what-one-marketer-did-about-it/