Raise your hand when you get tired of hearing people say “the world has changed” or “this is our new normal”. (We’re pausing for the collective raise of hands.)
The truth is in these tropics, but the reality is that you rarely get any really actionable advice on how to adapt your marketing strategy in a COVID (and post-COVID) world.
Why? Because honestly, most of us are still navigating changes week to week.
At this point, it’s difficult enough to predict the next month, let alone the next few quarters or years.
But we do know this: The world was going digital before COVID hit. That is doubly true. And with that, marketers and revenue operations teams who previously didn’t think about the quality of their data are now absolutely thinking about it.
The reason is simple: whether you are augmenting or augmenting your own first-party data with third-party firmography attributes, it is difficult to activate a successful marketing campaign when the data your team is putting 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 Precious Resource Is No Longer Oil, It’s Data.”
It was a menacing look at tech giants and antitrust regulations. But the headline message carried weight across all industries. For years we have heard that companies and executives represent the value of data-driven products. We’ve built tech stacks to collect and respond to data, and there isn’t a single highly functioning company in the world that doesn’t use data in some way to inform and advance its strategies.
Used properly, data can be an incredible asset.
But beneath the surface of the data rush is a dirty little secret: While most organizations make data-driven decisions today, not all of those decisions are well informed.
Worse, not all data is useful.
Last June, Dun & Bradstreet dug a little deeper and tried to answer a simple question: When companies deal with incomplete or inaccurate data, how badly does it hurt business? The results of the report were pretty clear: bad data practices directly translate into lost sales opportunities and lost customers. Almost 20% of companies say they lose a customer due to incomplete or inaccurate information.
The risk is equally high for marketers and revenue operations teams.
With inaccurate, incomplete, or unenriched data, the campaigns you run are like throwing arrows blindfolded in a crowded room. You might hit something, but it probably isn’t the growth goal you have been aiming for.
All of this is especially true of the world we live in today.
Five use cases lead to increased investments in data hygiene
Many companies these days are under budget freezes. Others spend, but only with existing providers or for essential products and services.
Navigating a difficult world is difficult for marketers as the traditional game book has to be thrown out the window. Today the key is to focus on the segments of the market and buyers who can buy and pull the right levers to reach them.
To do this, marketers and revenue operations teams need high quality, reliable, and accurate data about their customers and prospects.
In particular, five key use cases in the current business climate encourage the adoption of data hygiene and enrichment practices:
- Discover and use existing relationships. Many industries freeze spending; Hence, marketers and audit teams are looking for current customer relationships to drive growth. However, selling on these accounts requires precise insights that allow effective targeting and segmentation. When you cleanse your first-party data and enrich it with third-party data, you can discover and manage these relationships with surgical precision.
- Develop a clear view of the relationship between parents and siblings. One of the best ways to drive growth in a downward economy is to reach out to current customers who have not stopped spending and have potential for cross-sell and upsell. To do this, however, you need a clear view of your penetration in each account and any possible parent or sibling relationships that you can target. A combination of clean and enriched data from first and third party vendors is critical to defining these hierarchical business relationships.
- Target the parent company of subsidiaries or franchise accounts that you have already won. When you’ve successfully sold to affiliates, contact headquarters to see if you can close a bigger deal that will give you new revenue and possible expense consolidation. To do this, you need clean, enriched data to properly manage that relationship and make sure you’re targeting the right people.
- Create lookalike campaigns. Similar to the previous use case, you can also double the types of accounts that you know are in the market and that you already have a solid market adjustment on. The best way to do this is to create a like audience based on these accounts – a tactic that in turn requires excellent data sanitation for an accurate audience composition.
- Make a clear, defensible, data-driven case of ROI. When you can piece together disparate views from customers, it creates a single source of truth that should help improve your overall reporting. In addition, more precise targeting with improved data quality will help you find the right accounts at the right time and improve conversion. The net result: you’re capturing more value for every dollar you spend and have trusted data to prove it.
There are more use cases in both sales and marketing organizations that are causing companies to focus more on data hygiene, but you understand what it is about.
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More than ever, it is important to see your data as a resource that needs to be managed and maintained on an ongoing basis, rather than something you put on the shelf – just to be accessed when needed.
Data, like most other resources, will deteriorate over time. And if marketers or revenue operations teams do nothing to address this breakdown, they will likely be in the awkward position of explaining why their campaigns are not effectively delivering a quantifiable ROI.