10 ways to get better data from your lead-capture forms 

Capturing a new lead is the spark that ignites your customer journey. For B2B companies, a lead-capture form is where that adventure begins. You might have forms for gated content, demo requests, sales inquiries, or newsletter signups—just to name a few.

Yet, one tricky aspect of all lead-capture forms exists behind the scenes: capturing clean customer data with every form field completed. Ensuring the data you collect is correct and ready for your team to use is no easy feat. How would you characterize the data you receive from your lead-capture forms today? Is all the information accurate and consistently formatted? Can it be seamlessly ingested by all the tools in your martech stack? If not, that spark of first contact can be a lot more challenging to build into the fireworks of a successful conversion.

That’s why data hygiene is so important.

Inconsistent formatting or errors in customer data can hinder your team’s ability to use it, leading to automations going awry and time wasted cleaning data instead of acting on it. You don’t want that, and neither do your prospective customers.

Instead, try these 10 techniques for getting better data from your lead-capture forms. When implemented, each one will help ensure your forms deliver clean data that can easily be used.

A data input mask establishes a set format for form input fields. It defines how your data “looks.” Applying an input mask to fields like phone numbers, postal codes, and dates ensures a standardized format, minimizing incorrect entries and simplifying data cleaning. You can also add placeholder “hint” text to guide people on inputting the data for a better user experience.

Without a data input mask, you might receive phone numbers in many different formats, like (555) 867-5309, 555.867.5309, and 5558675309. That inconsistency can lead to various tools in your tech stack reading the data differently—and more manual work for you down the line. A data input mask shows customers how the information should be formatted and automatically corrects it as needed.

Using auto-fill features for standard fields like country, state, and city makes the experience more user-friendly and promotes uniform data collection. You can also auto-fill fields common to your specific business, such as industry, company, or the name of your products and services.

Say you regularly deal with employees from the same company. People might enter the company name differently, like using an abbreviation or shortened form. That makes it difficult to accurately identify which leads are from the same company and increases the chances of typos, further muddying your data. Auto-fill fixes this problem. As the customer starts typing, the form will suggest the complete company name based on your predefined possibilities.

Checkboxes or radio buttons for fields with a limited number of possible responses help keep your data simple and clean. But, you’ll need to provide enough options for customers to express themselves without overwhelming them. To avoid narrowing the possibilities too much (or giving your customers choice overload), you can include an optional text field for additional input—but be aware that you’ll have some non-standardized data to deal with.

Say you’re asking customers to tell you how satisfied they are with your product or service. A free-text field will give you responses that are hard to quantify and compare. Even the same meaning will be expressed differently across customers, e.g., “Totally” and “It’s great.” Radio buttons capture all sentiments in a standardized way, making results quantifiable and easy to compare.

For data that always follows standardized capitalization rules—like countries and cities—automatic capitalization keeps your data formatting consistent. Text fields can be programmed to automatically capitalize certain letters like the first letter of the text or the first letter of each word entered.

Say you’re promoting a live event to everyone in San Francisco. If someone gets an email that says, “Join us for san francisco’s most exciting conference of the year!” it will come off as sloppy. While you can handle the issue when you code the email itself (by using Liquid in your email code), that requires extra time and effort. Initiating correct capitalization during data capture will add an extra layer of consistency when using data in your automations.

Whenever possible, use predefined options instead of free-text fields. This minimizes the possibility of nonsensical entries (a common issue with gated content when people want a free download without giving their information).

💡 Pro tip: it’s essential to strike a balance. Offering too few options can turn off some customers who don’t see their needs reflected. A workaround is to provide an “Other” option with a corresponding free-text field. But keep an eye on the incoming data; if many leads choose “Other,” your predefined options may be too narrow.

People tend to describe the same role in wildly divergent ways, so a free-text field guarantees messy data. While “Team Lead,” “Team Leader,” and “Head of Team” might refer to the same role, your system may treat each as a separate job. Instead, provide a drop-down of predefined choices that align with your data needs and the options relevant to your audience.

Validation rules are just that: they validate that the data entered matches a rule you’ve set for that particular form field. A validation rule will flag errors and suggest real-time corrections to minimize human error. You can use this technique for any data with a set format that’s always applicable, like email addresses, U.S. phone numbers, and U.S. zip codes.

💡 Pro tip: Be sure to check your assumptions to ensure inclusivity. If you have customers in China and your phone number field requires exactly ten digits, you’ll lose the chance to connect with those leads. Or if you require that all last names be a minimum of four letters, you’ll tell everyone whose last name is Xu that you don’t care to do business with them.

Validating that data conforms to required formats is one way to reduce bad data, but it’s not a magic bullet. A third-party verification tool checks to be sure the data itself is valid. It’s ideal for any data that can be checked against a trusted source.

Let’s consider email addresses again in this context. Even an address that conforms to the right format could be invalid due to typos or intentionally fake information. When you send marketing communications to an invalid email address, the email will bounce, which harms your deliverability rates. Poor deliverability can damage your domain reputation—and that’s a surefire way for email clients to treat all your messages as spam. A third-party email verification tool can verify an email address in real time, checking if the domain exists and if the address is active.

Timestamps help you keep track of data relevance and accuracy when data is captured and updated. This requires nothing from the customer but provides invaluable intel for your sales and marketing teams. Insights from timestamps can indicate when leads are most active, the speed of the sales funnel, and the effectiveness of engagement strategies.

Suppose your sales funnel involves four lead-capture forms of increasing engagement. Include timestamps when a lead completes each form, and you can easily track their progress through the sales funnel. If someone’s moving more quickly than average, you might proactively reach out to catch them while they’re highly engaged. Or, if a lead stalls after completing two of the steps in the funnel, you could trigger an engagement campaign to bring them back into the process.

Say someone fills out the same form twice. Without back-end functionality that detects and de-dupes form entries, the data you use for prioritizing leads will be skewed, and your audience numbers will be off.

Duplicate entries can be a big problem for lead scoring. A lead that’s entered twice isn’t actually twice as valuable as other leads. Still, it can look that way in your system—leading to incorrect prioritization and misallocation of sales resources. By preventing dupes, you ensure that each potential customer is scored only once, enabling you to prioritize your leads accurately.

Getting someone’s name right is fundamental to personalizing your communications. If you just have a “Name” field, you run the risk of confusing data. Let's say you have a lead named Abdul Aziz Muhammad Al-Said. If you have just a single name field and no set format, he’d enter his entire name there. But, when your system attempts to split the data into first and last names, it might not know how to handle names with more than two strings of characters. That could lead to an email that says “Hello Abdul,” when his first name is actually Abdul Aziz—making your message feel careless and impersonal. A standardized naming convention with fields for entering first and last names separately solves the problem.

When someone fills out a lead-capture form, they signal that they want to hear from you. The next step is up to you—and if you’re practicing good data hygiene, your efforts will be easier and more effective.

If your automated messaging platform integrates with your forms, it’s even easier to use that data for personalization and automation. Customer.io Journeys makes it simple to feed form data directly into the platform, no matter what tool you use to create forms.

A bit of attention to your lead-capture forms can eliminate wasting time and resources cleaning your data—and ensure you’re prepared to fan the spark of initial contact into a brightly burning eternal flame of customer loyalty.