Response to Past Campaigns: Which segments responde positively to previous SMS campaigns, telemarketing Analytical Techniques: Unearthing Insights offers, or specific promotions.
Lifecycle Stage: Segmenting by new lead, active customer, repeat customer, churn risk, or lapse customer.
Psychographic Segmentation . A More Advance. :
Interests and Preferences: If collecte via surveys or inferre from behavior . A e.g., product categories browse. .
Values and Lifestyles: Understanding what motivates your customers can lead to highly resonant messaging.
Analytical Techniques: Unearthing Insights
With clean, segmente data, you can apply various analytical techniques phone number list to extract actionable insights.
Descriptive Analytics: What Happene?
List Health Metrics:
Validation Rate: Percentage of valid phone numbers.
Mobile vs. Landline Ratio: Distribution of number types.
Time Zone Distribution: Geographic spread of your audience.
Opt-out Rate: Percentage of numbers that have opte out over time.
Source Performance: Which lead sources yield the highest quality, most engage numbers.
Segmentation Profiles:
Generate profiles for each segment, highlighting key characteristics, average purchase personalization and contextual relevance values. The typical behaviors. For example, “Customers in Segment A . A e.g., ‘High-Value Repeat Purchasers’. are primarily mobile users, age 35-55. The have a 2x higher engagement rate with promotional SMS compare to Segment B.”
Geographic Hotspots: Map your phone numbers to identify areas with high customer density, which can inform localize campaigns or events.
Diagnostic Analytics: Why Did It Happen?
Correlation Analysis: Look for correlations between phone number characteristics and desire outcomes. E.g., “Do numbers acquire from online sign-ups show higher SMS click-through rates than those from in-store sign-ups?”
Response Rate Analysis by Segment: Analyze why certain segments performe better . A or worse. than others for specific campaigns. Was it the offer. The timing. The messaging, or the inherent characteristics of the segment?
Churn Analysis: Identify characteristics of phone numbers that opte out china database or became unresponsive. What patterns emerge among churne customers? Is it a lack of recent purchases, specific demographic traits, or Analytical Techniques: Unearthing Insights over-communication?