108. Lead Evaluation AI (Temperature Estimation) Design
Just by being able to identify 'immediate customers,' sales can change. We estimate lead temperature from behavior, statements, and attributes, and automate prioritization and next actions.
The biggest loss in lead management is "delaying responses to hot leads." In B2B, the consideration period is long, and if all leads are pursued with the same intensity, sales teams become exhausted, responses are delayed, and hot leads are missed. Conversely, applying "strong sales" tactics to colder prospects can lead to disengagement and a negative impression. In this service, we will design an AI evaluation logic to estimate the temperature of leads (Hot/Warm/Cold) based on inquiry content, document downloads, browsing behavior, form submissions, and company attributes. Depending on the temperature, we will differentiate response templates, proposal content, and next actions (calls/meetings/documents/waiting), clarifying sales priorities. ■ Provided Content (3 Points) 1. Design of temperature definitions (what constitutes Hot, verbalizing winning strategies) 2. Estimation logic design (AI + scoring, reliability) 3. Operational design (next action branching, improvement cycles, KPIs) *First, please tell us about the "winning patterns (characteristics of inquiries close to closing)" and the "system for follow-up (how many days it takes to respond)." We will translate this into evaluation criteria.
basic information
■Concerns like these - Leads have increased, but the conversion rate to meetings is not rising - Sales are busy and it's unclear who to follow up with - There are many document downloads, but priorities cannot be assigned - The quality of inquiries varies, and judgment is becoming subjective - There is confusion between agency requests and direct sales prospects ■Provided Content (Details) - 1) Definition design of temperature (Hot/Warm/Cold) - 2) Input data design for evaluation (realistically collectable) - 3) Estimation logic (Hybrid of AI + scoring) - 4) Next action branching (It's meaningless if you can't act even if you know the temperature) ■Deliverables - Temperature definition (Hot/Warm/Cold: criteria, examples, exceptions) - Input data design (acquisition items, acquisition methods, handling of missing data) - Scoring design (weights, thresholds, judgment logic) - AI evaluation design (elements to extract, reliability, basis output) - Next action design (temperature-specific templates, SLA, assignment of responsibilities) - KPI design (conversion rate to meetings, first response speed, follow-up completion rate, closing rate) - Operational improvement rules (review of misjudgments, dictionary updates, threshold adjustments)
Price information
■3 million to 15 million yen (varies based on data volume and integration scope) - Light (temperature definition + score design + ledger output): 3 to 5 million yen - Standard (AI evaluation + reliability + next action branching + operational design): 5 to 9 million yen - Extended (CRM/MA integration, behavioral data integration, dashboard, improvement support): 9 to 15 million yen *Estimate required
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Applications/Examples of results
■Purpose - Reduce hot lead loss (priority response) - Optimize sales labor (narrow down targets) - Improve nurturing accuracy (temperature-based scenarios) - Standardize response quality (templates/SLA) - Improve deal conversion rate (focus on winning strategies) ■Examples of Achievements - High document downloads → Clarified priority through temperature estimation - Many inquiries → Improved deal conversion rate by proposing immediate meetings for hot leads only - Mixed agency/direct sales → Organized responses through branching to eliminate confusion ■Approach 1. Winning strategy analysis: Inventory of conversion/loss data and past inquiries 2. Temperature definition: Establish criteria for Hot/Warm/Cold 3. Input design: Determine achievable data based on realistic lines 4. Logic design: Integration of rules + AI evaluation + scoring 5. Testing: Validate judgment accuracy with past data (eliminate unexpected issues) 6. Operation: Improve thresholds/dictionaries/templates monthly
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