article | February 18, 2015
Marketing Analytics: 5 Things You Must Do to Create an Effective Data Plan
“Big Data.” It has been billed as the biggest game changer for marketers in years.
As CMO, you may already have massive amounts of data at your fingertips. Your campaign reports are bursting at the seams. Clicks, clickthroughs, conversions—they’re all there.
But what is this data telling you?
Do you understand how leads are progressing through the funnel? Are you drawing the right conclusions? Are you equipped to make sound decisions?
That all depends on whether you have an effective marketing data plan in place.
With Gaps in the Funnel, Your Data Is Useless
Suppose marketing sends a new lead to sales. The sales rep thinks, I know this prospect. We have a relationship. So he closes out the marketing-generated lead and creates an entirely new record.
There goes your end-to-end data.
CMOs without an effective data plan are forced to rely on attribution models. By matching campaign responses with client wins, they take credit for sales. Right or wrong, they’re assuming cause and effect.
Here’s why this approach is problematic.
The bottom line: Your report may be overflowing with marketing data. But if it paints a faulty picture, you can’t glean useful insights. And you’re not bringing much to the table.
Begin Laying the Foundation Today
Proper data planning gives CMOs the clear, complete, precise picture they need. They can look at previous campaigns and determine which pieces originated in marketing. They can see what’s working and what isn’t. And they can demonstrate the value that marketing brings to sales.
Ready to set your data plan in motion?
Just follow our five-step data planning process.
Step 1: Data Assessment
Conduct executive interviews to understand your existing data and how it’s being applied.
Ask which important decisions have been and are being made regularly. How good is the data? How well is it assembled? How is it being accessed (e.g., dashboard, regular reports)?
Step 2: Understand Data Sources
Determine where your reports are coming from. Are they manual or automatic? If there are third-party data sources, can they be appended or expanded upon?
Where are the gaps?
Step 3: Data Architecture Plan
Map out your data as it exists today. Then decide where you’d like to end up, and create a phased rollout plan. What are some quick wins you can achieve to generate momentum for the plan?
Step 4: Data Cleanliness Plan
Create a plan for validating and cleaning up lead generation data. Establish rules for eliminating sales-qualified leads that are languishing in the funnel. Distinguish acquisition list contacts from regular contacts in the CRM. Avoid replacing good data with bad by pruning non-responsive acquired leads.
Step 5: Identify Ownership and Stewardship
Once your data plan is built, don’t let it erode away. Assign data management responsibilities, and be sure to include them in written job descriptions. Add appropriate metrics to data managers’ evaluation scorecards.
Measuring the Impact of Your Plan
B2B enterprises gauge data planning success in a variety of ways. Most begin by asking the following questions:
Another important measure of success is the credibility marketing enjoys among sales leaders. Marketing content and tactics may help buyers along, but the sales team closes the deals. Proper attribution is paramount.
The bottom line: Prove your value, but give credit where it’s due. Acknowledge the distinct contributions both teams are making to advance company goals.
Don’t Miss These Essential Tools
Explore our ProForma Campaign Tool—the Silver Bullet for Marketing ROI.
Download our Data Planning Case Study to learn how data planning can transform sales and marketing.
© 2017 Sales Benchmark Index (SBI)
A Business Strategy Consulting Company
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© 2018 Sales Benchmark Index (SBI), B.V.
A Business Strategy Consulting Company
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Amsterdam, The Netherlands