The Scariest Thing about Marketing Automation and 3 Things You Should Do About It

The data “monster” lurking within

scarypumpkins2With the adoption of Marketing Automation technology, B2B marketing teams are able to do more with less and measure everything. But what’s the scariest thing about these systems? Sending a campaign to the wrong list or forgetting to finish a landing page before a campaign launch may haunt you. Maybe you’re spooked that you won’t make your demand generation and ROI goals. However, I contend the number one scariest monster to tackle now is your data, or more specifically, the poor quality data that’s lurking in your system. It’s just waiting to rear its ugly head…and maybe it already has, but you just haven’t realized it!

According to a D&B survey of over 500 B2B companies, 27% sited poor data quality/accuracy as their biggest obstacle for maximizing return on investment in marketing technology. Without reliable sales and marketing company and contact records, how will you target the right audience with the right message at the right time?

Marketing data is the foundation of all your digital marketing efforts.

Another survey from Openprise and Ascend2 found 72% of B2B marketers say a top goal of their marketing data management strategy is improving ROI measurability. And 44% said data quality is the most significant barrier to marketing data management success. This same study revealed the top 3 most effective uses of marketing data are campaign targeting (62%), content personalization (51%), and sales attribution (43%) – pretty important stuff wouldn’t you say?

Let’s delve a bit deeper into 3 things you should be doing to ensure your data takes you in the right direction and drives the results you want.

1. Conduct a data audit – Review your existing contact and company records, see where your biggest problems are, and develop an improvement plan.

  • How many duplicates are there?
  • Which fields are being left empty or have inconsistent entries?
  • How many records haven’t been touched in 6 months?
  • What fields have typos or wrong information?

Very likely you’ll quickly see where the biggest issues are and can prioritize what to work on first. As you tackle each issue, it’s helpful to think about how the data is used (or is it even needed any more) and where the data is coming from (users or other systems such as CRM, social media, or other marketing tools).

Unstructured data such as text fields and comments or notes entries cause many problems if you need to use it for filtering, creating criteria, or when trying to do analysis. I’ve found that structuring field input, for example using dropdown lists or multi-picklists, reduces blank entries and increases the quality so that your campaigns, personalization, and analysis will be more accurate and effective.

2. Develop a data management process – If you don’t have a data management process, develop one. Make sure you have people dedicated to routine maintenance, data input standards (with agreement from sales), and documented processes that detail who, what, and when. The data audit discussed above will highlight the lack of or broken processes such as data importing, duplicate handling, data cleansing, and archiving/merging/deleting old contact and company records. Clean out the cobwebs and establish processes for keeping it clean.

3. Training, training, training – Let’s face it, most bad data comes from a lack of data management processes and user training. So once you have documented processes that make it easy for users to provide accurate data, it’s time to train users. Provide documented data entry standards, create on-boarding training for new employees, and periodic tips/updates/helpful hints to your users. Provide one-on-one help to those not in Halloween Background Scary Eyes Orange Vectorcompliance. Make sure your CRM and Marketing Automation systems have on-screen field level help. Provide short tutorial videos for on-demand, self-service help.

Without good data your team struggles with personalization and campaign effectiveness, and you may make decisions that’ll haunt you down the road.  That’s not scary, that’s terrifying!

What’s your biggest challenge to data management?

 

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