Lead Validation: A Sample Use Case

If you visit this blog regularly, you probably know by now how much contact data quality impacts your marketing efforts. Leads are a very perishable quantity, which are also subject to problems ranging from lead quality to outright fraud. And there is a very direct relationship between your data hygiene and the costs and ROI of your marketing campaigns.

For example, SiriusDecisions has long talked about the 1-10-100 rule: they note that bad leads may cost one dollar to fix at the time of data capture, $10 to correct, clean and de-dupe after capture, or $100 in soft costs if left uncorrected. Various sources have shown that contact data decays at a rate as high as 70% each year as people move, change jobs, or switch email addresses, and 25% of contact records contain critical errors. And increasingly, working with bad contact data can put you at risk of facing severe compliance penalties as consumer privacy laws continue to evolve.

Here, however, I’d like to look at an even more important issue: how lead quality can drive a strategic approach to marketing that, in turn, changes your outcomes across the board: sales, revenue, customer satisfaction, and employee retention. Let’s do this by looking at a use case that lays this all out for you.

Demand generation: A use case

Let’s focus on a sample business whose marketing department launches a demand generation campaign: they ask prospects to provide their contact information in exchange for some high-value content such as a white paper, webinar, or infographic.

Some of these incoming leads will be high-quality contacts. Others will be less valid: for example, they may have missing, invalid or suspicious data for specific fields. Still others will be totally fraudulent, such as someone who signs up as “Donald Duck” to get your free goodie without obligating themselves.

At the time of capture, in real time, our DOTS Lead Validation products validate a contact record’s data elements (such as name, address, phone number, email and IP address) for accuracy. Based on the firm’s business logic and the results from the real-time validation, this business can:

Flag data issues in real-time: This allows the business to message the prospect if there is an issue with a data field, so they can correct it at the time of capture. This will improve overall lead accuracy and prevent poor quality and fraudulent leads from being added to their sales and marketing databases.

Score leads: This business can take the Quality Score from the Lead Validation service for each incoming lead and then build further business logic around it. For example, they can route high quality leads to their best-performing sales teams, flag low quality leads for additional review and follow up, and remove or flag openly fraudulent leads.

Customize lead criteria: Our lead validation service is highly customizable to meet the specific needs of the business. If this business is collecting the leads for an outbound call campaign, for instance, the lead validation can be easily customized to give more weight to the accuracy of the phone number. Likewise, a direct mail campaign can prioritize address data, email campaigns can weight email validity heavily, and so on.

The impact of lead validation

Here are some of the ways this use case can make an impact on this business and its marketing:

  1. Better decision making. Better data quality leads to greater confidence in marketing analytics, and decisions on campaign performance and resource allocation can be made with greater confidence. Moreover, given that at least 25% of records critical data quality errors, correcting these will translate directly to a 25% or greater uplift in lead capture conversion and ultimately sales conversion.
  2. Efficient sales team deployment. Assigning high quality leads to top performers results in greater sales conversion rates, while sending lower quality leads to an automated drip/nurture campaign to monitor buying or intent signals conserves higher-cost resources for where they are most effective.
  3. Greater employee satisfaction. As sales conversions increases with better data quality, so will employee satisfaction and happiness – which, in turn, leads to stronger retention rates for a firm’s best people.
  4. Improved customer service. When prospects need help – or better yet, become customers – having the correct data will ensure that your customer service team can reach and help them effectively. Happy customers AND more efficient customer service both play a critical role in improving the bottom line.

Speaking of bottom lines, here’s the one for this use case study: the road to better marketing decisions, greater ROI and improved revenue starts with better data quality. And lead validation is a convenient, bundled strategy for automating contact data quality in your marketing process. It is an investment that will pay large dividends throughout all of your marketing operations, and in turn your business.