We got one!
Published: December 15th, 2023
Cold, warm or hot? IQL, MQL, PQL, SRL or SQL? There are many ways to describe lead, but how do you figure out if the email that just hit your inbox or CRM is more likely a hit than a miss with your current website toolkit?
If you’re like most websites (non-e-commerce), you have a legacy-style form to capture an email or other information from a visitor. Great! You have an email address and maybe some additional information from your form submission to send off to your email drip or sales team. But is the email from your drip campaign on the topic they were looking at? Is the email address a burner that this visitor uses to download the content they want and not be bothered with a follow-up email? What is the quality of this lead? How do you score it?
Some articles will tell you to take Explicit attributes (information or data you receive from a lead directly), such as job title, company size, industry, and location, usually attained from a form or survey. Others will say using implicit attributes (information based on a lead’s behavior), like gated content downloads, web page visits, email engagement, video watch time, etc., is best. Your lead capture method may vary, but most products use one of these methodologies.
Regardless of your company’s method, it’s now up to your sales team (sometimes a team of one – we see you!) to connect with that lead and move them from a prospect to a customer. If you’re a seasoned salesperson, you will have tools honed through trial and error, but what if you could fill your CRM with complete (and updated each visit) user journies based on the interactions with your website? Contact cards filled with first-party data related to each user’s visit, not just page views, bounces, heat maps or time-on-page statistics, but the complete interaction with a lead score – enter Bread & Butter.
That’s right, and not just a generic lead score, but a contextual lead score based on all visitors to your website (not a general data set or shared cohort/audience like in GA-4). Wasn’t that the promise of the internet?
Furthermore, lead scores get more accurate over time as Bread & Butter learns how your visitors interact with the content on your site. Add conversions or custom event triggers, and you now have a toolset that can drive automation (either with Zapier or Bread & Butter’s Nurture AI tool), making your website a true 24-hour-a-day sales platform.
Sample use cases:
1. Website visitors come from paid sources. We capture the source so you can track your ad spend. Follow the complete visit and any other sessions the visitor might have.
The paid visitor converts on an event specific to your sales funnel. That user journey is passed to your CRM, dropped into a drip email list, or turned over to Bread & Butter’s Nurture AI engine to connect with users’ verified email addresses. Nurture AI then sends a bespoke email, not a generic cold sales email, but one based on their interests, interactions, and custom events chosen by you. The now verified user returns, and the cycle starts again, updating your CRM’s user card and lead score.
2. A visitor comes from an organic source and bounces after a few pages. A few days later, they return directly and spend a little more time but still don’t convert. Two weeks later, they convert on a gated content link or opt-in on an offer. All these now verified user interactions are compiled under the user, given a lead score and sent through automation like before. Taking what would have been separate sessions, hits and page views by GA4 and attributing them to our now-known customer.