The True Cost Of Bad Data In Your Marketing Automation

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Inbound marketing and marketing automation platforms promise to make your marketing more effective, and they have the potential to live up to that promise. However, reality often tells a different story — especially when bad data plays a starring role.

Marketing automation platforms like Eloqua, Hubspot, Marketo, and iContact are great tools that can help you connect with your leads and customers. But they are just that, tools. The idea of marketing automation tools is promising, but poor execution and bad data will limit your success.

The Cost of Bad Data

You pay for every contact residing in your marketing database. If your data quality is bad, you are wasting time and money. Data quality suffers for several reasons. Some data starts out clean before going bad due to address or phone number changes. Meanwhile, it’s not uncommon for users to enter bogus information into lead and contact forms. For example, 88% of online users have admitted to lying on online contact forms.

Bad email addresses mean your messages never arrive as intended; the same is true with bad postal addresses, plus you’ve just wasted money on postage or shipping, and bad phone numbers waste your sales and marketing team’s time calling bogus numbers. Improving the data accuracy within your marketing automation platform could save a ton of money.

How much money is at stake? It’s more than you may realize. Applying Deming’s 1-10-100 rule, it costs $1 to prevent bad data, $10 to correct it, and $100 if it is left uncorrected1. So, if you had just 10 bad records, that would be $1,000 wasted. Chances are, you have far more than 10 bad records in your marketing automation software. Approximately 10 to 25 percent of B2B contact records contain critical errors2.

Moreover, using bad data has a cascading effect on the organization. Not only are you expending valuable resources to capture leads, each lead, whether good or bad, takes up a “seat” in your marketing automation plan — with each seat costing money.

The cost to contact bad leads is real. Some of the more obvious costs include printing and postage cost for direct mail and outbound calling, which average costs are about $1.25 per attempted call. Even email costs money, albeit not much (roughly $0.0025 per email), but this adds up over time if left uncorrected.

There’s More to Data Accuracy Than Cost Savings Alone

PrintLooking beyond obvious costs, it is important to understand the cascading impact of bad data on other areas of your business.  For example, even though you are using the latest and greatest real-time CRM or marketing platform, if the data is bad, your CSRs will begin to doubt the effectiveness of the platform. This can lead to a lack of confidence in your data, poor morale, and poor performance.

Another example is the impact on your marketing intelligence reports and decision making. Marketing to bad leads will result in “false-negative” data. Since these leads do not respond (because the data quality is bad), your marketing campaigns’ performance will be dragged down.

If you don’t like to throw money away, cause undue stress on the team, or make decisions based off of bad data, improving the data accuracy of your marketing automation software can go a long way toward solving these problems. If that’s not compelling enough, consider this: clean records improve contact conversion rates by 25 percent2.

Service Objects can help ensure that the promise of marketing automation becomes a reality in your inbound marketing strategy. Our data quality tools correct and improve the data in marketing automation platforms, resulting in better performance. Benefits include reduced cost per lead and cost per sale, more reliable performance data, increased contact rates, increased response rate, reduced cost to contact, and more sales.

Isn’t it time you banish bad data from your Marketing Automation Platform?

Sources:

1 siriusdecisions.com/TheImpactofBadDataonDemandCreation.aspx

2 deming.org/index.php?content=61