AI-Assisted CRM Automation

Project at a glance

Challenge: Scattered engagement and follow-up dependent on manual checks.
My delivery: An integrated cycle of prioritization, SMS, transcription, and CRM notes.
Business value: Richer customer context and a clear daily contact routine.

Process overview: from incoming information to team use.

The challenge

A large lead and customer base generated interest signals across property views, email opens, replies, and communication history. The team needed to identify who deserved attention and preserve conversation context for the next contact.

My contribution

I designed and operated the automation workflow, connected CRM tools, and defined prioritization and profile-update rules. I used AI for code and prompt implementation while taking responsibility for review, testing, troubleshooting, and maintenance.

The workflow connected the work before and after a call: contact selection guided the team’s next action, while conversation records informed the next interaction. My work included maintaining rules, reviewing outputs, and troubleshooting integrations to preserve that cycle.

How the solution worked

Prioritize. Daily routines reviewed engagement across the database, organized a contact list, and prepared call tasks based on interest, history, and priority.
Prompt action. A scheduled SMS told the responsible agent that contacts were ready for follow-up. Customer conversations remained human.
Preserve context. An end-of-day routine reviewed calls across the database, retrieved available recordings, transcribed them, and added summaries, notes, and next steps to the corresponding profiles.
Integrate. MCP services and webhooks connected events, communications, tasks, and records. Duplicate checks and data verification supported consistency.

Business value

I connected scattered activities into a follow-up cycle: the team received clear priorities, reminders, and current context for each relationship. This reduced manual signal gathering and information organization and supported continuity in human and AI-assisted service.

Expanded sample deliverable

Follow-up workspace and customer memory

Fictional content, properties, contacts, and figures. Recreated deliverable structure, without client data or actual results.

From engagement identification to conversation records in the CRM

Open each section to explore the complete deliverable.

01Action list prepared for the team

Fictional contact	Context and signal	Suggested action
Contact A · buyer	Returned to two-bedroom listings and replied about association costs.	Call to clarify costs and confirm criteria.
Contact B · owner	Replied to the condominium market update.	Clarify sale intent and offer an agent conversation.
Contact C · buyer	Requested more information after viewing a listing.	Review history before following up.

Internal SMS notification

The follow-up list is ready. Customers have replied or shown recent interest. Review CRM tasks, check conversation history, and record each contact outcome.

02Call task ready for action

Contact A · agent brief

Goal: confirm criteria and clarify association costs.
Context: seeking two bedrooms, prefers natural light, and wants to assess total housing cost.
Questions: priority location, purchase timeline, and costs needing clarification.
Expected output: conversation outcome and next step in the profile.

03From recording to structured note

Fictional conversation excerpt

Client: I liked the natural light, but I need to understand what the association covers before arranging another showing.
Agent: I will gather the details and confirm which options fit your needs.

Note prepared for the profile

Summary: still interested in a two-bedroom apartment; decision depends on cost clarity.
Preferences: natural light and predictable total cost.
Open question: items included in association fees.
Team commitment: gather information and follow up.
Next action: send the cost breakdown before proposing another showing.

04Cycle completion and continuity

Step	Sample outcome
Contact made	Outcome linked to the correct contact.
Context updated	Summary, preferences, and open questions gathered in the profile.
Next interaction	Team and assistant consult history before suggesting another contact.

When a recording is unavailable

The example handling flags the call for review without inventing a transcript or filling the summary with unavailable information.

Applied capabilities

Systems integration, sales-process design, agent orchestration, event processing, call transcription, and automation maintenance with human oversight.