Raise your hand if you’re sick of hearing people say “the world has changed” or “this is our new normal.” (We’ll pause for the collective hand-raise.)
There’s truth in those tropes, but the reality is that they’re rarely followed up with truly actionable advice about how to adjust your marketing strategy in a COVID (and post-COVID) world.
Why? Because, frankly, most of us are still navigating changes week-to-week.
At this point, it’s hard enough to predict next month, let alone the next few quarters or years.
But here’s what we do know: The world was already going digital before COVID hit. Now, that’s doubly true. And, with that, marketers and revenue operations teams that weren’t thinking about the quality of their data before are absolutely thinking about it now.
The reason is simple: Whether you’re comingling or just enhancing your own first party data with third-party firmographic attributes, it’s hard to activate a successful marketing campaign if the data your team is stitching together is a mess.
When Data Is a Problem, Not the Solution
In 2017, The Economist published an article with a bold headline: “The world’s most valuable resource is no longer oil, but data.”
It was an ominous look at tech giants and antitrust regulation. But the headline’s message carried weight for all industries. For years, we’ve heard companies and executives espouse the value of being data-driven. We’ve built tech stacks around collecting and acting on data, and there’s not a single high-functioning business in the world that doesn’t use data in some way to inform and drive their strategies.
Harnessed properly, data can be an incredible asset.
But there’s a dirty little secret hiding beneath the surface of the data gold rush: Although most companies are making data-driven decisions today, not all of those decisions are well-informed.
Even worse, not all data is useful.
Last June, Dun&Bradstreet dug in a little deeper, trying to answer a simple question: If companies are operating with incomplete or inaccurate data, how much is it hurting the business? The report’s findings were pretty clear: Bad data practices equate directly to missed revenue opportunities and lost customers—with almost 20% of businesses reporting losing a customer because of incomplete or inaccurate information.
For marketers and revenue operations teams, the risk is equally high.
With inaccurate, incomplete, or unenriched data, the campaigns you’re running are akin to throwing darts with a blindfold on in a crowded room. You might hit something, but it’s not likely to be the growth target you were aiming for.
All that is particularly true in the world we’re living in today.
Five Use Cases Driving Increased Investment in Data Hygiene
Today, many companies are under budget freezes. Others are spending, but only with existing vendors or on essential products and services.
For marketers, it’s a difficult world to navigate, because the traditional playbook must be thrown out the window. Today, it’s all about hyper-focusing on the market segments and buyers who can buy, and pulling the right levers to reach them.
To do that, marketers and revenue operations teams need quality, reliable, accurate data about their clients and prospective clients.
Specifically, five key use cases in the current business climate are driving adoption of data hygiene and enrichment practices:
- Discovering and leveraging existing relationships. Many industries are freezing spending; therefore, marketers and rev ops teams are looking to current customer relationships for growth. But selling into those accounts requires precise insight that enables effective targeting and segmentation. Cleaning your first-party data and enriching it with third-party data allows you to discover and manage those relationships with surgical precision.
- Developing a clear view into parent/sibling relationship. One of the best ways to drive growth in a down economy is to target current clients that haven’t shut down spending and have potential for cross-sell and upsell. To do so, however, you need a clear view into your penetration within each account and any parent or sibling relationships that might exist that you can target. A combination of clean and enriched first- and third-party data is critical to defining these hierarchical business relationships.
- Targeting the parent of subsidiaries or franchise accounts you’ve already won. If you’ve had success selling into subsidiaries, why not call in to HQ to see whether you can work a bigger deal that opens the door to new revenue for you and potential cost consolidation for them? To do that, you need clean, enriched data to manage that relationship properly and make sure you’re targeting the right people.
- Building lookalike campaigns. Similar to the previous use case, you can also double-down on the types of accounts you know are in-market where you already have solid product-market fit. The best way to do that is to create lookalike audiences based on those accounts—a tactic that, again, requires excellent data hygiene for precise audience composition.
- Making a clear, defensible, data-driven case of ROI. When you can stitch disparate views of customers together, you end up creating a single source of truth that should help improve your overall reporting. Moreover, more precise targeting fueled by improved data quality helps you target the right accounts at the right time, improving conversion. The net result: capturing more value on every dollar you spend, and having trustworthy data to prove it.
There are more use cases across both sales and marketing organizations that are driving companies to put increased focus on data hygiene, but you get the point.
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Now more than ever it’s critical to look at your data as a resource that must be continually managed and cultivated, instead of something you put on the shelf—only to be accessed when you need it.
Data, like most other resources, will decay over time. And if marketers or revenue operations teams do nothing to manage that decay, they’ll likely find themselves in the uncomfortable position of explaining why their campaigns aren’t effectively driving quantifiable ROI.