The same customer might buy through TikTok Shop today, through Shopee next week and walk into the shop the month after, while the back office counts them as three different people. This system brings buyers from every channel together into a single Golden Record, then builds on it with customer segmentation, channel-by-channel performance analysis and product recommendations drawn from real purchase history. All of it sits on a Thai-language dashboard where you can put follow-up questions to the AI on the same page.
Who it is for
Brands and retailers selling across several channels at once that still cannot say where the same customer has been buying again.
Collapsing several identities into one customer
The heart of the system is the Golden Record: establishing that several purchases made through different channels belong to the same person. The "Search and link buyers" page lets you search by name, phone number, member ID or address, then select several records and merge them into one, with the AI proposing matches first and the team making the final decision. Buyers that have not yet been linked are held in a separate list, so they can be worked through over time instead of disappearing into the database.
- Search buyers by name, phone number, member ID or address
- Select several buyers to merge into a single Golden Record
- AI match suggestions, confirmed by a person
- A list of unlinked buyers to work through
The whole customer base and every channel on one page
The CDP/CRM dashboard summarises the state of the membership base along the top: total members, active members, new members that month, churn rate and growth rate. Below that, customers are segmented by product type together with the average order value of each segment, which often reveals that the segments with the fewest people carry a much higher value per order. Then comes a channel performance section that separates the number of buyers from the average order value for each platform.
- Membership metrics: total, active, new this month, churn rate, growth rate
- Customer segments by product type, with average order value
- Compare TikTok Shop, Shopee, Lazada, LINE Shop, LINE OA, Facebook, Instagram and in-store
- Buyers who purchase on more than one platform counted separately
Segment by behaviour, then recommend products person by person
Once the data has been merged into a single record, the system sorts customers into RFM behavioural segments (champions, can't lose them, loyal, potential loyalists, new customers, about to sleep, at risk, hibernating and lost), so you can choose who to talk to and with what message. The "Recommended products" page suggests products drawn from that customer's own purchase history, with a match score against every item, so the sales team can see the reasoning behind a recommendation and not just the result.
- RFM customer segments with filters on a single page
- Product recommendations from purchase history, with match scores
- Chat with the AI to ask about customers in Thai
What it does
- Merge multi-channel buyers into one Golden Record
- AI match suggestions, confirmed by a person
- Membership and churn overview dashboard
- RFM segmentation by buying behaviour
- Channel-by-channel performance analysis
- Product recommendations from purchase history, with match scores
- Search buyers by name, phone, member ID or address
- Ask the AI about customers in Thai
Want something like this?
Tell us your situation and we will work out what needs adapting to fit it.