Welcome to Part 2 of our series on the 4 most valuable CRM features. After collecting client feedback, the next step is understanding who your clients are, and that is where customer tags and targeted marketing come in.
What Are Customer Tags and Why Do They Matter?
Customer tags are labels you attach to each client to group them and understand their spending habits, preferences and behaviour. With tags in place, you can run targeted marketing campaigns for different client groups.
Many small business owners run promotions the same way: they send one message to every client and assume the job is done. But this kind of blanket marketing usually performs poorly:
- Clients who are interested in the product may feel the message says too little
- Clients who are not interested see it as a nuisance
- Open rates keep dropping
- Some clients may even block your WhatsApp number
Once you learn to use customer tags, you can avoid these problems and do real targeted marketing.
The Main Types of Customer Tags
Spending Behaviour Tags
These tags are based on how clients spend:
- High spender: over CA$250 per visit
- Mid spender: CA$100 to CA$250 per visit
- Low spender: under CA$100 per visit
- Regular: visits more than 3 times a month
- Occasional: visits less than once a month
- Dormant member: no purchase in over 90 days
Preference Tags
These tags show what each client likes to buy:
- Beauty lover: often books facials and treatments
- Hair loyalist: comes in regularly for cuts and colour
- Price-sensitive: often asks about deals
- Product buyer: often buys hair care and skin care products
- Service lover: prefers one-on-one service
Client Profile Tags
These tags describe the client personally:
- Gender: female or male
- Age group: 25 to 35, 35 to 45
- Area: Downtown Toronto, Markham, Mississauga
- Occupation: office worker, homemaker, student
- Skin or hair type: sensitive, dry, oily
Custom Tags
On top of the system tags, your staff can manually add custom tags to clients:
- Special needs: for example, pregnant or postnatal
- Service preferences: for example, prefers a particular staff member
- Habits: for example, likes to visit on Saturdays
- Health notes: for example, prone to allergies
Targeted Marketing in Practice
Use Case 1: Birthday Offers
- Blanket approach: send the same “Happy Birthday! CA$20 coupon” message to every member
- Targeted approach: filter members with upcoming birthdays and send different offers to different age groups
- Results: 3x higher open rate and 2x higher redemption rate
Use Case 2: Winning Back Dormant Members
- Blanket approach: send a “We miss you” message to every member
- Targeted approach: filter dormant members with no purchase in 90 days and send each one an offer that matches what they bought before
- Results: win-back rate up 40%, and 3x more effective than blanket messages
Use Case 3: Promoting a New Service
- Blanket approach: send a Botox treatment promotion to every member
- Targeted approach: filter high spenders who love beauty treatments and have had facials but never Botox, then send the promotion only to them
- Results: 5x higher conversion rate, without bothering clients the offer doesn’t suit
The Numbers: Targeted vs. Blanket Marketing
Based on our client data, the gap between targeted and blanket marketing can be huge:
Blanket Promotion
- Messages sent: 1,000
- Open rate: 15%
- Conversion rate: 1%
- Total revenue: CA$200
Targeted Promotion
- Messages sent: 200
- Open rate: 45%
- Conversion rate: 8%
- Total revenue: CA$3,200
The Bottom Line
Targeted marketing converts 8 times better than blanket marketing. Even when you message 5 times fewer people, revenue can be 16 times higher.
The 4 Most Valuable CRM Features: Full Series
- Part 1: Service Survey and Rating System
- Part 2: Customer Tags and Targeted Marketing (you are here)
- Part 3: Customer Churn Report
- Part 4: Customer Follow-Up List
Ready to put customer tags and targeted marketing to work? Explore our beauty salon management system, hair salon and barber shop system and retail POS system, or contact us to speak with our Toronto team.
