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The lead journey in GetResponse: from form submission to the right sequence
A high-intent B2B contact reaches an account owner with an alert, while everyone else enters an educational sequence. The form separates them from the start.
3 min read
- Client
- B2B/B2C services company
- Industry
- Marketing / Email automation
- Scope
- AI sales agents & lead generation
Who the client was and what was getting in the way
The client runs a service company selling to both businesses and individual consumers. Those involve two very different conversations: a company asks about engagement terms and scope, while an individual asks about price and timing. Yet every enquiry landed in the same place.
As a result, a promising lead waited in line alongside a minor question. No one was at fault; there was simply no mechanism to tell them apart. Enquiries were handled manually, so response time depended on who happened to be free. That is costly in service sales because a person who submits a form is usually sending it to two other companies at the same time.
The second problem concerned the point of entry. The form and the way contacts were tagged had to be legally correct from day one because retroactively fixing consent in an email database is painful and sometimes impossible. Third, email communication did not follow a consistent approach. Every campaign looked different because each one was built from scratch.
What we built
We built everything in GetResponse without adding more tools. The starting point was a GDPR-compliant enquiry form that captures the source and customer type alongside contact details. It may seem like a small thing, but those tags determine everything that happens next.
We used them to build segmentation. The first split is between businesses and individual consumers. The second is by lead-quality tier, based on the information someone provides in the form. The system therefore knows not just who the contact is, but how urgent the enquiry is.
GetResponse marketing automation handles the next step. A high-intent business contact goes straight to an account owner with a notification, so the conversation can begin immediately. Other enquiries enter an educational sequence that develops the topic and alerts the salesperson when the contact starts responding. No one is ignored, but account owners are not pulled in too early either.
The final piece is a modular email template. It has one consistent visual identity, reusable content blocks, and is ready to copy for future campaigns. A new email now means filling in the blocks, not designing a message from scratch.
How it works today
Someone submits the form, and the system immediately knows whether they are a business or an individual, where they came from, and the quality of the lead. It sends them down the appropriate path: to a person or into a sequence. The account owner gets an alert only when there is a reason to act.
The marketing team uses one template and copies it for future campaigns, so the communication looks consistent regardless of who prepares it. The entire journey, from lead intake to automated sequences, is documented and repeatable.
The outcome
Every lead now has a complete journey from form submission to automated handling, with no manual sorting. Segmentation works across two dimensions at once: customer type and lead-quality tier. The form and contact tagging have been GDPR-compliant since launch, so the database started with properly recorded consent. The template is modular and ready to copy for future campaigns.
The qualitative outcome is easier to describe than any metric: a high-intent business enquiry no longer waits behind a minor question.
What we would do differently
Contact tagging is foundational, but we defined it while building the workflows. That was the wrong order. Changing tag names and rules after contacts are already in the database means cleaning up historical records and fixing automation conditions. Next time, we will define the full tag list, naming conventions, and assignment rules before building the first workflow.
The second lesson concerns lead-quality tiers. We set them based on what the client said about its customers rather than on real enquiries from recent months. Reviewing one hundred historical enquiries would have produced better thresholds and fewer post-launch changes. The third lesson is to have a lawyer review the formβs consent language before launch, not afterward β a quarter hour of work that safeguards the whole database.
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