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Lead Generation Database Metrics
Lead generation can be analyzed using statistics and probability. Conversion of database contacts into leads and clients can be modeled as stochastic processes, allowing for predictive modeling and optimization❓.
Database segmentation is crucial. Separating contacts into “Met” and “Haven’t Met” categories reflects differences in relationship strength and information asymmetry.
The “Met” database comprises individuals with a pre-existing relationship. Conversion rates are typically higher in this segment. The “8x8” program involves contacting individuals in the “Met” database eight times over eight weeks, based on the “mere-exposure effect.” The “33 Touch” program involves consistent communication throughout the year, with an expected outcome of a 12:2 ratio (1 referral and 1 repeat business for every 12 individuals).
- NM = Number of people in the “Met” database.
- CR = Conversion rate (referrals/repeats) per person per year (estimated at 2/12 from the 33 touch program).
- SM = Sales generated from the “Met” database.
- SM = NM * CR*
Experiment: Independent Variable: Number of “touches” per year. Dependent Variable: Number of referrals and repeat business generated. Control Group: A segment receiving fewer touches (e.g., 12 touches per year). Experimental Group: A segment receiving the “33 Touch” program.
The “Haven’t Met” database comprises individuals with no pre-existing relationship. Conversion rates are typically lower. The “12 Direct” program involves sending twelve targeted communications per year, with an expected outcome of a 50:1 ratio (one piece of new business for every 50 people).
- NHM = Number of people in the “Haven’t Met” database.
- CN = Conversion rate (new business) per person per year (estimated at 1/50 from the 12 Direct program).
- SHM = Sales generated from the “Haven’t Met” database.
- SHM = NHM * CN*
Experiment: Independent Variable: Type of content and media used in direct communication. Dependent Variable: Number of leads and new business generated. Control Group: Standard marketing materials. Experimental Group: Tailored content based on demographic and psychographic data.
Total sales (ST) = SM + SHM = (NM * CR) + (NHM * CN)
To achieve a sales goal, SGoal, the required database sizes, NM and NHM, can be estimated.
Example:
- SGoal = 320 sales
- CR = 2/12 (from “Met” Database)
- CN = 1/50 (from “Haven’t Met” Database)
Scenario 1: Only using the Met database: NM = SGoal / CR = 320 / (2/12) = 1920
Scenario 2: Only using the Haven’t Met database: NHM = SGoal / CN = 320 / (1/50) = 16000❓❓
Optimization involves marginal analysis.
Market conditions significantly impact lead generation ratios.
* Seller’s Market: increased❓ demand may lead to higher conversion rates.
* Buyer’s Market: Lower demand may lead to lower conversion rates.
* Transitioning Market: Requires constant monitoring of market trends.
Internal factors influence overall sales performance.
Lead Conversion Rate (LCR):
LCR = (Number of Appointments / Number of Leads) * 100%
Appointment Conversion Rate (ACR):
ACR = (Number of signed listing agreements❓❓ / Number of Appointments) * 100%
Listings Conversion Rate (LiCR):
LiCR = (Number of Listings Sold / Number of Listings Taken) * 100%
Chapter Summary
Lead generation depends on database ratios, differing between “Met” and “Haven’t Met” contacts. “Met” contacts yield a higher lead conversion rate. A ‘33 Touch’ program for “Met” contacts shows a 12:2 ratio (1 referral and 1 repeat business per 12 contacts). A ‘12 Direct’ program for “Haven’t Met” contacts shows a 50:1 ratio (1 new business❓ per 50 contacts). Optimal lead generation combines both “Met” and “Haven’t Met” databases. Generating 320 annual sales requires a sufficient database size. Key performance indicators are lead, appointment, and listing❓ conversion rates❓, influenced by internal (agent skills, follow-up systems) and external factors (market dynamics). Low conversion rates necessitate training/consulting or increased marketing. External factor fluctuations require adapting marketing and pricing strategies. Consistent ratio monitoring and intelligent response are crucial for sustainable lead generation and adapting to market shifts.
