If you are old enough to remember the disco era, one of its biggest hits was “Got to Be Real” by Cheryl Lynn. (And if you’re younger, it’s been sampled over 100 times since.) Decades later, if you work in marketing, this tune should become your new theme song.
The lifeblood of any marketing operation is its lead generation efforts. And sadly, many of these leads aren’t real – according to industry figures, as much as 25% of your contact data is bad from the start, and from there 70% of it goes bad every year as jobs, roles and contact information changes. This ranges from fake or fraudulent contact data, often entered to gain access to lead generation bonuses, all the way to fat-fingered data entry.
Unfortunately, when your contacts aren’t real, the costs involved are very real:
Marketing costs: Direct mail costs can easily total $2-3 or more per piece mailed, while outbound telemarketing costs can top $35 to $60 per lead. In both cases, there is direct cost in both time and resources to working with bad contacts. Nearly any lead conversion strategy has a scalable cost per prospect, and bad or fake leads directly eat into these costs.
Wasted human effort: Take the labor costs, taxes and benefits you pay for the direct employees on your sales and marketing teams. Add in the costs of the overhead and infrastructure they require to do their jobs. Now multiply that by the percentage of time these people spend mitigating bad leads, and this total probably adds up to a very real and tangible cost, as well as impacting sales conversion rates.
Inefficiency: Ultimately, every business must deal with the problem of bad contact data. But the real question is when you deal with it. In many businesses, where data quality is no one’s responsibility, it gets fixed the hard way when prospects don’t answer and direct mail pieces bounce back. We describe it as the 1-10-100 rule, where it may cost a penny to catch bad contacts as they are captured, 10 cents to cleanse them after capture, and a dollar to work with uncorrected data. In addition, bogus leads can bog down your CRM or Marketing Automation platform, driving up costs and negatively impacting marketing campaigns.
Customer service reputation: Your all-important first impression on a potential customer pivots around responding to their requests – and if you fail to respond due to bad or misdirected contact information, the damage is often permanent. For example, if a customer enters their email incorrectly but are waiting to receive information from customer service, causing dissatisfaction and frustration.
The good news is that each of these costs can easily be controlled by automating the data quality process for your contact lead data, using tools that range from address verification to filtering out fraudulent names. For marketing operations, you can also use bundled lead validation capabilities that check over 130 data points to yield a lead quality score from 0 to 100, as well as lead enhancement that appends phone and contact information to your existing lead data.
The key to success in marketing, according to Forbes Magazine, is to know your customer. Data quality – making sure every contact record in your database is as genuine, accurate and up-to-date as it can possibly be – represents an important and cost-saving first step for this. Or as Cheryl Lynn would say, they’ve got to be real.