Introduction
If you feel like you are constantly scheduling emails, LINE broadcasts, SMS messages and app push notifications yet customers still do not open or click, you are not alone. Many retail brands in Asia have already turned on every major communication channel but still see flat open rates, rising unsubscribe or block rates and weak engagement. The core problem usually is not the lack of channels. It is that messages are still sent in the same way to everyone at the same time with the same content and frequency. When outreach looks like mass blasting, it is almost impossible to match each customer’s habits and preferences.
The real challenge behind omnichannel marketing
Most marketing teams face two recurring issues. First, they collect more and more customer contacts but struggle to turn that database into meaningful segments. Without a clear way to group and target audiences, the only option is to broadcast identical messages. The result is predictable. Open rates drop, click rates decline and block or unsubscribe rates quietly climb. Second, manual segmentation is exhausting. Pulling lists, applying filters, choosing send times and updating audiences for every campaign consumes time and still falls behind fast moving retail calendars and promotions.
To escape this cycle you need much better use of zero party data and first party data. Zero party data is what customers willingly share such as interests or preferences. First party data is what your brand collects from behaviour such as browsing, purchase history and channel interactions. When you can aggregate and activate both in a smart way, you can finally move beyond blind blasting.
From tools to intelligence using beBit TECH CDP
beBit TECH CDP is built to sit at the centre of this problem. It brings together O Data operational data such as orders and interactions and X Data experience data such as feedback and responses. Then it applies an AI module that automatically creates precise segments. On top of that sits the smart channel capability. The AI powered send function reads each member’s history across every channel, including opens, clicks and blocks. Based on this pattern it predicts the best channel and best send time for that individual and delivers the message only through that route at that moment. Instead of you guessing, the model chooses the single most efficient path for each customer.
In practice, this looks like the system recognising that customer A almost never opens EDMs but frequently taps on LINE and therefore choosing LINE for the next campaign. Customer B might regularly open emails on Wednesday around lunchtime, so the system schedules an EDM at that exact time. Over thousands of customers these micro decisions add up to a much healthier overall performance curve.
Why open rates often get stuck
Every marketer understands the principle of using the right channel at the right moment yet putting that idea into daily operations is hard. There are three common bottlenecks. The first is channel overload. With email, SMS, LINE and app notifications all competing for attention, teams often fall back on blasting everything everywhere just to ensure reach. This inflates sending costs and quickly irritates customers. The second is timing. Standard best practice advice such as send newsletters on Monday morning or push offers during dinner does not reflect real life. People have wildly different routines and media habits. Some clear their inbox at dawn, others scroll LINE at midnight and behaviour varies by age, job and weekday versus weekend. The third is technical. To truly optimise sending you must integrate data from all channels, update it continuously and run machine learning models that can make predictions in near real time. Doing that manually is unrealistic.
Smart channel as a three step process
The AI smart channel approach turns what used to be a messy, manual workflow into a simple three step process that can be reused across campaigns.
Step one is data alignment inside the beBit TECH CDP. You import scattered first party data and write all relevant interactions into a single system. That includes members, transactions, onsite events and engagement with EDM, LINE and SMS such as opens, clicks, blocks and unsubscribes. The result is a complete 360 degree profile for each customer rather than separate records in separate tools.
Step two combines rules and models. You can start with simple logic such as reducing email weight for customers who have not opened EDM for thirty days. On top of those rules the AI learns each person’s behaviour, automatically estimating preferred channels and predicting ideal send windows for every profile. Over time the model improves as more interaction data flows in.
Step three is full marketing automation. In the visual journey editor you chain together audience selection, smart channel, AI powered channel choice and personalised send time into a single flow. That flow then runs continuously for both big batch campaigns and lifecycle programs such as welcome, upsell and reactivation. The workflow does the choreography while your team focuses on content and strategy.
Fashion retailer Ann’S using AI smart channel
Taiwanese fashion brand Ann’S illustrates how this works in reality. Over time they had accumulated a large and complex mix of customer data, communication channels and transaction records. Managing this manually was heavy and limited their ability to react quickly. After implementing beBit TECH CDP, they started using channel interaction history for each member to infer the best communication route. By plugging the Highball AI prediction module into the smart channel node, every send was preceded by an evaluation of which channel each member responded to most frequently.
For example, if a member had stopped opening EDM entirely but consistently engaged with LINE messages, the system would shift that person’s messaging to LINE only. This avoided wasteful email sends and improved the overall experience for the customer. After turning on AI smart channel, Ann’S lifted email open rates by about one quarter and boosted click rates by around sixty percent, proving that better channel decisions translate directly into engagement. (beBit Tech)
Beauty brand 19again orchestrating campaigns with phased exposure
Skincare brand 19again faced a different challenge. Rapid growth in membership and product lines had left their marketing team reliant on manual exports and imports, which consumed a lot of time and limited campaign frequency. After adopting beBit TECH CDP they shifted to a strategy built on phased exposure plus AI smart sending. In a recent scalp care launch they first warmed up interest through their own YouTube channel. When the product officially launched, they used the CDP to orchestrate LINE and EDM waves using strong visual content.
In the final countdown to the end of the promotion they sent SMS reminders six hours before the offer closed. This multi channel rhythm avoided repetitive bombardment while keeping urgency high. As a result, the early bird offer aimed at existing members hit eighty percent of total campaign revenue on its own and overall revenue from returning customers grew by 136 percent that month. The case shows how smart channel selection, combined with good creative and pacing, can dramatically strengthen both engagement and sales from loyal customers.
Before and after automation
Comparing life before and after AI smart channel makes the value clear. Previously, brands would push the same content through every channel to the entire list, sometimes repeating sends just to ensure reach. This drove up messaging costs while open, click and conversion rates stayed low and block and unsubscribe rates climbed. After integrating all channel data into beBit TECH CDP and switching on the AI module, brands could decide automatically which single channel and time each person should receive a message. Campaigns became more focused, less annoying and significantly more effective, with better open and click performance and lower average cost per successful touch.
A new engine for retail digital transformation
AI smart channel is not just another button on a dashboard. It connects data, decision and delivery into one marketing automation engine. Instead of hand picking who gets EDM, who receives LINE and who should get an SMS, you let the model determine who, when and through which channel while you put your energy into better offers, journeys and creative. Results from brands using beBit TECH CDP show that average open rates can rise by more than fifty percent and ROAS can improve by around sixty percent while marketing teams save a significant amount of time on scheduling and reconciliation.
For retail brands, this kind of capability is the missing piece in omnichannel marketing and a fast acting lever in digital transformation. The earlier you build this data and decision infrastructure, the sooner you create a defensible moat of customer insight and a communication strategy that feels personal rather than noisy.
Bringing WhatsApp into your smart channel mix in Malaysia
For Malaysia and much of Southeast Asia, you cannot talk about smart channel strategy without including WhatsApp because for many shoppers it is the default way to talk to friends, family and increasingly to brands. When you plug WhatsApp into the same CDP and AI smart channel framework as EDM, LINE and SMS, you give the model another powerful option for reaching customers in the place they already check multiple times a day. Instead of you guessing whether to send a promotion by email or messaging, the AI can see that a particular customer usually replies fastest in WhatsApp and route the next campaign or reminder there, while choosing email or LINE for someone else who rarely opens chat based messages.
In practical terms this means treating WhatsApp as both a service channel and a conversion channel. Your CDP should record events such as opt in status, message opens, link clicks, replies and completed orders that started from a WhatsApp conversation, then feed that history into the smart channel model. Over time the AI learns which customers like to get order updates and reminders in WhatsApp, who is comfortable receiving personalised offers there and who prefers to reserve that space only for high value messages like delivery notifications. For example, a shopper in Kuala Lumpur who frequently chats with your team about sizing and restocks might be tagged as WhatsApp first for back in stock alerts and live selling invitations, while a customer in Penang who mainly engages with newsletters would stay on email for most marketing but still receive critical WhatsApp alerts such as payment confirmation or last mile delivery updates.
The key is to avoid turning WhatsApp into another blast channel. Because the app feels personal, customers are more sensitive to spam and will quickly mute or block brands that overdo it. A smart channel setup helps you protect that trust because the AI can give WhatsApp a lower weight for people who ignore or block past messages and a higher weight for those who respond well. Combined with clear consent flows and frequency caps managed in the CDP, this lets you keep WhatsApp as a high impact, high respect channel that supports your omnichannel strategy in Malaysia rather than overwhelming customers with noise.
For reference on WhatsApp usage and business messaging ideas, you can explore Meta and WhatsApp Business resources such as https://business.whatsapp.com and regional case studies shared there.