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3 Ways Unmatched and Duplicate Records Damage your Sales and Marketing Ecosystem
Using an AI-driven CRM matching and deduping solution can be the solution for bad data that has infected your organizational ecosystem.
Pollution in the environment is an apt metaphor for how bad data infects your organizational ecosystem. Like with excess CO2 and unbiodegradable plastic, data has a way of hanging around your business, finding ways to slow things down, and making businesses less efficient.
While sales and marketing data might not be a heavily audited source of truth like finance or have the gravitas of the day-to-day necessity of operations and supply chain data, sales and marketing is the engine room of all businesses and that data is the heart of every organization. So how does poor data quality in a CRM or marketing automation platform impact customer relationships and the business bottom line? Why is it vitally important to prioritize sales and marketing data improvement?
Let’s examine different ways duplicated and unmatched sales and marketing records affect your organization and quantify the damage it could potentially be causing.
Bad Data Leads to Missed Business Opportunities
According to Gartner, poor data is responsible for an average $15 million cost a year to businesses. It seems an absurd number. How can imperfections in ones and zeros really accumulate to a figure that large? The answer lies in a concept known as data decay.
“With marketing, sales, sales ops, admin, contracts, and delivery all using the same platform, often with different objectives or processes, duplications, imperfections, or inconsistencies are a natural occurrence.” This was how Brian Haering, Syniti VP of Direct Solutions put it in a recent interview. But this is no small problem, data decay can create meaningful negative impacts to the business.
According to Dun and Bradstreet, 19% of businesses have lost a customer through using inaccurate or incomplete information about them – a stunning number for just holding incorrect information. But it doesn’t have to even be that noticeable for the damage to be felt. What about the lost opportunities for sales and revenues through maintaining poor prospect data? What about the reputational damage that can arise with a misplaced ‘Dear Client’ when emailing your customer base? What about the legal/ data privacy ramifications of sending e-communications to opted-out contacts?
While one incorrect record may seem inconsequential, they can soon conspire to cause your business irreparable damage.
3 Ways Bad Data Leads to Wasteful Marketing Campaigns
Poor data impacts marketing teams in three distinct ways: data collection and hygiene, campaign performance, and revenue attribution.
Let’s start with the collection of data. Those experienced with the process will fully appreciate the difficulty of acquiring accurate customer data, whether that be from online means, marketing events, or 3rd party lists; however, the challenge just starts there. According to Haering, “It’s very difficult to bring in data from outside of your CRM without introducing duplicates. The traditional solution to ensuring data is accurate and up-to-date, has been to utilize a spreadsheet with a V-LOOKUP and then conducting a manual review to assess the comparison’s accuracy. A slow, mind-numbing inaccurate process that inevitably leads to many errors.”
In B2B account-based marketing (ABM) and customer communications, Haering says, “duplicate accounts obscure that true 360-degree account-based view and distort how we’d want to communicate to those accounts.”
In 2022, the relevancy of messaging is essential for marketing to succeed. For example, according to Forrester, 21% of all media spend had been wasted over the prior 12 months due to poor data quality. Could you afford to waste 21% of your marketing budget?
Finally, let’s discuss attribution. This is the ultimate KPI for all marketing departments, as this helps prove to the business that things are working, that marketing is pulling its weight, and yes, that more budget is justified!
This issue can be seen in the B2B world of sales and marketing, where duplicated, decentralized accounts or inaccessibility of data can cause opportunities to stall or to be created fresh, not converted from the original marketing lead. This means either the marketing attribution is missed, or a manual resource has to be taken off assignment and utilized to check opportunities to ensure marketing is appropriately credited for their contribution.
How Data Pollution Decreases Sales Efficiency
Every sales manager, account executive, or entry-level business development rep can sympathize with Haering, who stated in the aforementioned interview, “in every organization I’ve ever worked in I’ve used the world's leading CRM system, and I’ve experienced first-hand the pain that even one duplicated record can cause.”
This "pain" can come in many forms: time taken to correct a data record, conversations with other record stakeholders, and eliciting IT support. All consume a salesperson’s time and takes them away from the obvious critical thing they should be focused on. And this is no small amount of wasted time we’re talking about; according to DiscoverOrg (now ZoomInfo), an incredible 550 hours is lost yearly from an average sales team’s productivity due to poor prospect data.
A percentage of this enormous number is due to the huge amount of poor data currently in the average organization’s CRM. Dun and Bradstreet have discovered that 96% of contact data within CRM systems are at least partially inaccurate, and ZoomInfo has estimated that 30-50% of CRM and ERP data is inaccurate.
Whatever the exact number is, it doesn’t just hurt sales in terms of individual employee productivity, it also impacts sales forecasting too. Many key decisions, such as hiring and asset acquisition, are made on the basis of accurate sales forecasting, and it is essential to have the CRM speaking the single source of truth; however, for many organizations, sales forecasts are not giving an accurate picture. According to one study, 46% of surveyed businesses were unable to call their sales forecasts accurate.
All this "pain" inflicted because of poor data quality ultimately hits salespeople and the business they serve where it hurts the most, in lost sales. For businesses seeking growth, reduced costs, and higher profits, perhaps sales and marketing data should be the first place they look.
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