The High Cost of Poor Marketing Data Orchestration
A lot of marketers recognize that poor data quality is an iceberg capable of sinking any campaign, sales goal or product launch. However, poor data quality is actually a surface issue—albeit an expensive one—of something bigger and more sinister lurking below. If you want to leverage data to keep customers happy and close more deals, you must begin at the beginning. It’s not enough to scrub a list once or twice a month and think you are in the clear. You need to know, and more importantly control, how data is entering your organization, and how it is being processed, maintained and shared throughout your organization. In other words, you need to master the art of data orchestration. Show me a top marketer with superior data quality, and I’ll show you someone who has done the work necessary to set their current and future data processes up for success, a maestro of data orchestration, if you will.
Show Me the Money
Both Forrester and Gartner have conducted studies on the high costs associated with poor data quality and lackluster data orchestration. Here’s what they had to report:
- $1.2 million is the average annual loss caused by poor data quality at a midsize firm
- $16.5 million is the average annual loss caused by poor data quality at an enterprise-sized company
- $611 billion per year is lost on poorly targeted digital marketing campaigns each year in the U.S. alone
- 21% of media budgets are wasted annually due to poor data quality
- 26% of marketing campaigns are hurt by poor data quality each year
According to Melody Chien, Senior Director Analyst for Gartner, “Data quality is directly linked to the quality of decision making. Good quality data provides better leads, better understanding of customers and better customer relationships. Data quality is a competitive advantage that leaders need to improve upon continuously.”
Show Me the Impact
When Forrester asked marketers to divulge how poor data quality and poor data management had negatively impacted their organization, here’s what they reported:
- 37% — Wasted marketing spend
- 35% — Inaccurate targeting
- 30% — Lost customers
- 29% — Reduced productivity
- 28% — Poor customer experiences
- 24% — Inaccurate marketing/media performance
As Shaggy might exclaim after being confronted with so many evil outcomes at once—ZOINKS! Every last single item on the aforementioned list has the potential to sink a business over time, but together, or in any combination, they spell impending doom. If you recognized any of these killers as being present in your marketing results, it’s time to pick up your conductor’s baton and show them you are dead serious about orchestrating your data.
The Origin of Poorly Orchestrated Data
Left to its own devices, data is like milk, destined to go bad, begin stinking, and become gag-inducing in a matter of weeks. This begs the question, if data is in a perpetual state of impending decay, what can be done? First, you’ll want to develop a data orchestration strategy. The first step in this process requires you to track down how customer data is entering your organization. Notice we didn’t say department, but instead recommend you get a handle on how everyone, who is using customer data throughout your organization, is taking it all in. What you will typically find as you begin this process is that the same customer’s data you use in marketing is quite different from the records accounting, sales or customer service may have. Moreover, not only are the standards different, but some may have more up-to-date info than marketing, and some may have embarrassingly out-of-date information.
In addition to mass data discrepancies, which have a proven negative impact on the customer’s experience of your brand, this process should also uncover the data silos at your company, which are the bane of good data orchestration. Currently, 41 percent of critical company data is trapped in legacy systems that cannot be accessed or linked to cloud services. While it’s one thing to learn how sales takes in their data and where they store it, it’s quite another to get some paranoid corporate types to recognize their need to share and share alike. In fact, 44 percent of executives site a lack of collaboration between business departments as a major challenge to their attempts to unite and integrate all company data. However, here’s some research that might turn the naysayers heads and win their hearts as you build your case for connected data sources throughout your organization with a single standard for truth:
- Organizations in the US and UK lose $140 billion each year in wasted time and resources, duplicated efforts, and missed opportunities as a result of disconnected data
- 47% of execs believe disconnected data negatively impacts their organization’s ability to innovate, develop new products and services, and get them to market quickly
- 46% of execs say disconnected data impacts their ability to engage, support, and meet customer needs
- 72% of execs say their organization is missing out on opportunities as a result of disconnected data
Centralize Data Control and Maintain Data Quality
Once you have connected all the data sources throughout your organization and set a data standard that all follow, you are ready to take the next step in good data orchestration. Ideally, this step begins with you having a centralized dashboard by which you can see and control the quality of all data enterprise-wide. Naturally, this is an undertaking that relies on automated checks and balances for keeping data clean. It will also require access to third party sources to ensure data is complete and enriched with every dataset needed to grow a rewarding customer relationship.
Finally, now that you have adjusted all the main players in your data orchestra—connection, centralization, cleanliness, completion, quality—you are ready to conduct how data is shared from one tool to the next. This is the real magic and power of good data orchestration and it requires you to automate as many data processes as possible. If done well, you will be able to automate how data from multiple sources is shared and used in real-time. While that may sound daunting at first, fortunately, there are tools that greatly simplify data orchestration, as in you won’t need IT to do it. More importantly, you can save yourself and your company from the high costs of poor data orchestration.