Customer Segmentation in Retail Loyalty
Being relatively new to retail marketing, I think about and spend a lot of my time putting myself in the shoes of consumers. While my clients are Retail merchants, our end users are consumers. B2B2C.
The reality in Retail in 2016, is how consumers want a greater level of personalization and are more willing to give their personal information when they “opt-in” to a loyalty program. Need my phone number, no problem, just don’t call me, text me!
This opens the door for some quite advanced personalization of offers, for algorithms to come into play and for even real-time offers in-store. While Email is still the best way to reach the most people for the cheapest, this won’t necessarily always be the case.
Introduction to Retail Segmentation
In this article I’ll be briefly exploring customer groupings called segments. Segmentation (sub-groups) is a term synonymous with how we used to do Email marketing. Instead of sending out your blast to all of your Email subscribers or loyalty members when there is a special offer, you would customize the message to the persona of the customer. That’s where segments come in.
Segments that Sync with Smarter Data
However in 2016, this also means the segments based on your transactional data from a cloud POS solution, like Lightspeed or Vend, that can be used for SMS and personalizing Email offers. How would you describe your store’s ideal customer?
They are those who:
- Are the most profitable, i.e. they have the largest transaction size (buy the most stuff per visit!). This is a metric related to monetary value.
- They shop the most, their shopping frequency is high compared with your average. This is a metric related to transaction frequency.
- They show up at your store on a regular basis, they’ve been there recently. This is a metric related to recency. They are not just one-time shoppers, they are local and visit your store often to touch base with your products, customer service and latest offers.
The RFM model, is based on just that: KPIs relating the recency, frequency and monetary value of your customers. Obviously these are a decent measure of who your high-value customers are and are important native segments.
A normal ESP (email service provider) does not have the ability to map out the actual data on the behaviour of your customers and therefore cannot provide information like the average number in days in which your customers visit your store.
Along the customer journey of consumers who visit your store, there is a spectrum: The RRS spectrum shows (green = in play) & (red = churn)
- First-Time: Shoppers who only visit once, walk-ins that are random from the street.
- Repeat: Customers who visit your store again.
- Loyal: Customers who have visited your store a number of times.
- At-Risk: Customers who have not visited your store in a while.
- Dormant: Customers who may have forgotten about your store or may not plan to come back.
Omnichannel RFM Cloud Segments
If you think about your customers in terms of value (RFM) and their journey with your retail brand (recency) you get a picture of how each group must be marketed to differently depending on their:
- B&M Engagement level with your brand, store and products (Monetary)
- Digital Engagement with your brand online in terms of advocacy (Social Media, UGC, Contest participation, CSR advocacy)
- Actual Stage of the Customer Journey (Recency).
- Channel Preference: younger consumers are more likely to prefer SMS messages as loyalty marketing offers. Consumers over 34 years typically prefer Email messages still.
Emotional Customer Journey
- Emotional Customer Experience Level:
- 1-Ignorance: they don’t know you exist
- 2-Indifference: they no engagement logged with you but they are in your system.
- 3-Trusting: they have shopped and or are a brand advocate online of your store.
- 4-Reciprocal: they show high RFM and brand advocacy, though they are not yet a member of your loyalty program.
- 5-Loyal: they are a high-value customer and a member of your l
- 6-Committed: They are a high-value and a member of your loyalty program.
* The Emotional experience of the consumer is key in 2016 to do customer engagement and customer loyalty better!
Future of Retail Segmentation
Thanks to cloud POS systems and innovative loyalty marketing Software, Retail customer segmentations is catching up with email segmentation and triggers (transactional) messaging.
In 2016–2018, I expect SMS Marketing integrated with loyalty reward programs and marketing automation to become more personalized, mainstream and appealing to consumers to offer a more enjoyable real-time shopping experience that’s omnichannel and integrates both digital and physical retail touchpoints in the customer journey.
Customer Lifetime Value
The concept of customer lifetime value is very important in Retail. It can be expressed in the terms we expressed before, good ‘ol RFM:
The idea is that the net present and future value of a visitor is a function of:
- How recently the user interacted or purchased
- How often they interact or purchase
- How much they purchase
The highest ROI would be generated by thosehigh-value customers who purchase more, more often, and have done so recently. Ideally, this customer takes minimal cost to retain and requires minimal discounting in order to remain a loyal customer
7 Real World Segments that Matter
According to some agencies, these 7 categories are significant retail segments that can be useful in personalizing an offer to a customer in loyalty marketing in Retail.
- Acquisition Path: How they came to be a customer.
- online or offline
- channel/social network
- word of mouth or referral
- random walk-in
- First Purchase: Predictions based on first purchase.
- Price sensitivity (scored)
- Probable Shopping persona
- Level of attachment to store (sentiment)
- Device Type:
- Mobile vs. Web
- Android vs. iOS
- Smartphone vs. Other
- Weblinks clicked
- Geography & Location
- Postal code of home address
- Number of visits to store divided by number of transactions
- Distant from store in Miles
- Monetary value by postal code
- Monetary value of customers by state
- Monetary value of transactions by age
- Median income and home price in customer’s postal code
- Tailor message to customer’s predicted income and product preference of transactional history
- Gender can correlate with a shopper’s predicted spend
- Female customers CAN be more valuable
- Some message copy (SMS or Email) will be preferable to females or males
- Open rates and conversion rates by Gender of past messages
- Relationship between age and lifetime value tends to vary from retailer to retailer
- For Independent retail merchants (IRMs) age can be a huge factor. E.g. “vape” stores usually have a very young average customer and the same goes for a trendy female apparel store. While a Pet or a Bike store may have a higher average age.
- Older customers tend to be more affluent
- Older customers tend to be more brand-loyal (pre Millennials)
- Younger customers are more valuable in terms of online advocacy and UGC.
I hope this has been helpful to you, if you’d like to keep track of what I write, you can. I work at a company that is disrupting the way small to medium sized retail merchants, entrepreneurs and store owners can integrate loyalty marketing that is seamless for their store and frictionless their loyal customers, in case you are curious.
Mar 16, 2016