Data-first marketing: A strategy to stop wasting 30% of your budget
Focus on the fundamentals ensures the contact and account data generated from our marketing efforts is compliant, marketable, informed, connected and actionable. This commitment makes our people, programs, and results better.
Data, data, data. The fuel for the engine, the grease for the system, the protein for the body. All apt descriptions of the role data plays in smart, effective marketing (and business). Like eating well, sleeping restfully, and getting exercise, it’s what increases our performance. We know it, maybe we even preach it. How come most B2B teams fail to conquer data readiness and governance?
In today’s digital-first world, a world where the customer comes first, a world where it’s about the buyer and not your internal team structures, data silos or sales process, data quality is the first and foundational building block that your marketing and sales teams need. It’s what allows your teams to align around, develop strategies, execute programs, and attack your target markets.
With expectations at an all-time high and growth the charter for B2B teams, now is the time to (re-) commit to getting your data right. “Right” today means focusing on the fundamentals ensuring the contact and account data generated from our marketing efforts is compliant, marketable, informed, connected and actionable. This commitment makes our people, programs, and results better.
The real cost of bad prospect, customer and account data
When we fail to address data quality, first and upfront before it hits your database, the out-of-pocket, hidden, and professional costs are real. It’s expensive, it burns resources, and it delivers crappy experiences when you’re marketing is off the mark.
Bad – incomplete, inaccurate, unstandardized data – significantly hampers marketing’s performance and ability to deliver against its numbers to the business and promise to their customers and prospects. Like smoking, it’s a costly, bad habit that needs to be addressed. Let’s dive deeper and break down the numbers.
- 25-30% of data generated from your demand programs is unmarketable because the data is inaccurate, non-compliant for privacy and/or doesn’t match your Ideal Customer Profile (ICP). Worse, you’re spending budget to generate unmarketable prospect data. Doing the quick math, that $1 million budget you thought you were putting to work is now only $700,000.
- It costs $100-120 per record to clean data once it’s in your systems compared to only $2-$3 to get it right before it hits your database. At 100,000 new records a year that is the difference between investing $200,000 for clean data first strategy versus spending $700,000 to try and fix it later.
- SDRs spend on average 27 hours per month (Sales Assembly, January 2020) cleaning up bad data generated from marketing’s programs. That’s $4,000 worth of monthly salary for every SDR you have on the front lines. You can run the math on productivity and costs.
These are just the “in your face” numbers. The “hidden” costs come in the form of losing sales trust and turning off potential prospects and customers when follow-on outreach misses the mark.
Strategies and tactics to getting your data right, first
As the costs add up quickly, we need scalable strategies to shake up the traditional way we have thought about fixing bad data and ensuring clean, marketable data. One approach is a proactive strategy and the other is an emerging benchmark for B2B organizations. Both are proven strategies and they’re even better when used together.
- Take care of bad data before it hits your database. Most of us say, ”I have tools or services that will clean it up once inside my Marketing Automation and/or CRM databases.” If we’re honest that never really happens. One marketing executive recently shared, “…it’s like trying to clean water when it enters the sewage treatment plant. It needs to be done but it’s so much harder after the fact.”
- Make it a top KPI, setting goals, benchmarks, and metrics around data health. As more B2B teams focus on precise targets and account-based strategies, one powerful benchmark is based on hitting a high % of marketable database and coverage of their personas in their named account buying groups. For example, “our goal is that 85% of our database is permissioned and matches our target audience.” Or “…of our 7,150 named accounts, we have at least 3 opt-in members of our buying group”. This data first commitment helps everybody perform better.
Create a marketable, segmented, compliant database of ideal buying groups and accounts
A data-first strategy supports an essential marketing and sales strategy – a healthy, active and permissioned database of prospects and customers. Deploying and mastering these data-first strategies become even more critical if your organization has any of these progressive growth strategies in action or on the drawing board.
- Deploying an account-based strategy or shifting to ABM – it’s a lot of heavy lifting if your contact and account information isn’t accurate or synched for programs. No matter how strong the account-based sales and marketing plays you run in the market are, you’re dead on arrival without good data. And there’s no hope for sales-marketing alignment.
- Mapping buyer and/or account journeys – segmentation is nearly impossible if your prospect and account data is not actionable, your contacts aren’t permissioned, and/or your account data is not linked across buying groups and across channels.
- Building databases and audiences as you enter new vertical or geo markets – jump-starting marketing and sales requires opt-in contacts across the buying groups within your named accounts or ICP to create demand and support sales. A marketable database is essential.
Marketing in 2021 is going to be much harder as performance demands from execs increase and prospects and customers interacting, research and purchasing remotely is the norm. With budgets being developed this quarter, now is an ideal time for nailing your strategy and committing to getting your data right, first.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
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