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【2021 Solutions】 Join the Marketing Technology Ecosystem - Janchiang Lab Solves Your Marketing Issues with LINE

In the digital age, there are myriad advertising channels: physical and digital ads, plus platforms like Facebook and Instagram, all competing for consumer attention. Recently, the emerging LINE Official Account (OA), backed by a substantial LINE ecosystem of technology partners, has gained prominence. Janchiang Lab, a Silver Partner of LINE, harnesses AI to assist notable clients like RT-Mart, FamilyMart, and IKEA among 300 brands, helping them grow and solve their marketing issues.

Janchiang helps brand owners gain a deeper understanding of their customers, demonstrating significant benefits through Online Merge Offline (OMO) strategies.

With up to 21 million users, LINE has become one of the most dominant marketing channels in Taiwan. Janchiang Lab, specializing in LINE data marketing since its establishment in 2017, foresaw the trend of app ecosystems when LINE announced it would open its API. Hsueh Chin, Co-founder and CEO, joined the lineup of LINE technology partners, anticipating future trends.

Janchiang Lab established a LINE data ecosystem.

▲ Janchiang Lab established a LINE data ecosystem.

"Brands can consider Janchiang Lab's services as a Customer Relationship Management (CRM) system to better understand consumers," Hsueh Chin stated. Janchiang provides three primary services to brand owners:

1. Member Dynamics Insights: Through Janchiang's MAAC backend system (Messaging Analytics & Automation Cloud), brand owners can quickly gain insights into each member's gender, browsing history, and purchasing behaviors. Also, as each member accesses their LINE account at different times, the system sends advertising messages at the optimal time based on this activity;

2. Proactive Product Recommendations: The system detects when a customer purchases product A and proactively recommends product A+ or similar yet distinct products to enhance purchasing intent;

3. Automated Consumer Journey: After a customer purchases products in-store and joins the LINE official account, the system can set up to automatically send promotions after a certain period, to increase purchasing intent. Janchiang Lab also strengthens the interaction between online and offline, utilizing beacon technology in retail storefronts. They installed beacons at a furniture brand showroom, and whenever a beacon captured a consumer's phone Bluetooth signal, the backend system of Janchiang Lab proactively sent related advertisement broadcasts. This project, from April to October 2020, significantly increased the brand's official account by nearly five thousand members, doubling its effectiveness.

Despite LINE's tens of millions of users, and logging into their LINE account being the first thing they do every morning, a primary concern for operators of LINE official accounts is the surge in messaging fees. Hence, 'precision marketing' has become the most crucial principle for dispatching messages. Janchiang Lab aids brands in understanding user profiles and thus tailoring messages to appropriate recipients, making LINE a foundational tool for CRM. Users also do not need to download other apps, as they can perform their daily needs via the existing messaging channel, clearly displaying the power of LINE for marketing.

The pandemic accelerated the pace of digital transformation for companies; Janchiang will increase customer service through multiple channels

Annually, Janchiang Lab sends over two billion LINE messages, helping over 300 brand clients actively use data through data tracking and marketing automation technologies within LINE official accounts. The pandemic has also sped up digital transformation steps for various industries including e-commerce, retail, media, and finance, with clients like A.S.O., IKEA, and Books.com.

Janchiang Lab milestones

▲ Janchiang Lab milestones

However, during the advancement process, Janchiang Lab also heard the voices of digital transformation vendors who, facing many digital marketing channels, hope to not only invest in LINE but also diversify into other advertising platforms, like SMS, thereby helping brands enhance their overall reach.

After accumulating rich marketing data experience in Taiwan, Janchiang Lab also set sights on overseas markets like Thailand and Japan. Given Thailand's local population of over 40 million LINE users, in September 2021, Janchiang Lab co-hosted its first online seminar with the local advertising agency Adme, leveraging its successful case studies with over 300 brands in Taiwan in industries such as e-commerce, retail, and media, aiming to offer a fresh digital transformation agenda to Thai brand owners.

AI social commerce sales software service iKala Shoplus also signed with Janchiang Lab, becoming its first major client as Janchiang Lab entered the Thai market. Both firms will combine their strengths in the MarTech field to seize big data opportunities. Dialogue-focused commerce AI startups GoSky and Janchiang Lab, in collaboration with iKala’s KOL Radar, have pooled their data to launch a social commerce traffic solution entering the social commerce battlefield. Janchiang Lab is also partnering with CDP brand Treasure Data to make inroads into the Southeast Asian market.

Hsueh Chin acutely realizes that the future of the MarTech market will embody an ecosystem concept, involving strategic alliances between technologies to develop integrated services needed by clients. For instance, if brand operators need LINE push notifications combined with e-commerce platform services, Janchiang initially collaborates with e-commerce platform vendors to integrate both databases, thereby sending e-commerce order information to specific LINE users to boost 'precision marketing' rates. Likewise, if owners wish to conduct surveys among LINE members, they might first negotiate with online survey vendors to propose solutions, all part of future efforts. In the short term, expanding cooperation with technology partners to jointly serve customers; in the long term, Janchiang will gradually develop a complete product line to become the best marketing partner for brands.

Janchiang Lab Co-founder and CEO Hsueh Chin.

▲ Janchiang Lab Co-founder and CEO Hsueh Chin.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

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【解決方案】瑕疵辨識率達百分百 耐銳利科技獲面板大廠青睞
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On the machine tool production line, there are some slight differences in the first step of assembly Accumulated tolerances will cause the assembly work to be repeated, which is time-consuming and labor-intensive, resulting in shipment delays that will impact the company's reputation Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutions It uses machine learning models to inherit the experience of old masters In the CNC processing machine assembly and casting process, it uses AI to analyze production line data, accurately adjust various data, and improve Production accuracy is 25 This AI production line data analysis system is called "Master 40" by Huang Changding, chairman of Naruili Technology It is the most evolved version of the master plus artificial intelligence It has been used in machine tool processing factories with remarkable results In addition, Nairi Technology used AI defect detection technology to participate in the 2021 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significantly from 70 to 95Tang Guowei then said that the original size data set by Master during assembly All were recorded on paper After the information was written, it was stored in the warehouse and sealed No one studied the relationship between the dimensions Narili assists customers in designing the Fu 40 system Through the human-machine panel, the master can directly input the measured dimensions and related data during assembly After collecting data from different masters, AI algorithms are used to analyze the relationship between the data and create an AI model The AI model automatically notifies the operator what size to adjust to, and the quality inspection will definitely pass In this way, the yield rate will be improved It has increased significantly from 70 to more than 95 Narili Technology Company focuses on the field of smart manufacturing and provides various AI solutionsTang Guowei added, assembling the spindle of a CNC processing machine It took four hours In the first step, the machine made measurement errors, including vibration, temperature, speed, etc that were out of range It had to be dismantled and reinstalled, which took another four hours How to adjust after disassembly depends on the experience of the master At first, the master may have done the best assembly method based on experience, but the error rate was also 30, and the assembly took several days With the assistance of AI masters, the assembly time only takes half a day, and the yield rate reaches over 95, saving a lot of time and manpower "Use the AI model of machine learning to collect the experience of all the masters and provide it for AI learning The first step is digitalization, and the second step is knowledgeization This is the transformation of the enterprise "An important key", Huang Changding believes that Narili Technology is an important partner in the transformation of traditional manufacturing from automated production to digital transformation In addition, another industry that Naili Technology focuses on is the smart car dispatching system of the leading brand of elevator manufacturers The so-called car dispatch referring to the elevator car means that if there are more than two elevators, group management is required In the past, car dispatching was based on fixed rules If the elevator was closer to the requested car, that elevator would be automatically dispatched On the one hand, it did not take into account that dispatching a car if the elevator was called too many times might make other people wait longer The previous vehicle dispatching model did not take into account the usage characteristics of the building, resulting in a lot of waste For example, in an office building, there are peak hours in the morning, lunch break, and afternoon after work AI smart car dispatch can be flexibly adjusted according to off-peak and peak hours, increasing the efficiency of car dispatch, reducing waiting time, and reducing wasted electricity Introducing elevator smart dispatch to improve transportation efficiency and have environmental protection functionsHuang Changding added that just like the previous traffic lights at intersections, the system has already The number of seconds to stop and pass on highways, sub-trunks and small streets is programmed Smart traffic lights are now used to flexibly adjust waiting times to make road sections prone to congestion smoother Using AI to learn usage scenarios and introducing a smart dispatch system into elevators will improve transportation efficiency and make it more environmentally friendly In addition to introducing smart elevator dispatching, Nairili also introduced AI into the smart production and shipment scheduling system of elevator factories Elevator factories often cannot accurately estimate the customer's elevator delivery date For example, office buildings or stores must be completed to a certain extent before the elevator can be installed on the construction site If affected by unexpected factors such as delays in the customer's construction period, the elevator factory will often be idle or the schedule will be difficult to arrange Tang Guowei pointed out that generally those who understand the progress of client projects may be from business or engineering, but overall, the accuracy rate of shipments is only about 60, which means that 40 of them will not be shipped as scheduled Therefore, if the shipping schedule can be accurately estimated, the production line can be freed up for emergency orders or other product production needs The AI smart scheduling system will analyze past shipment data, about 20-30 parameters such as climate, distance between the factory and the construction site, and customer credit, and put them into the AI algorithm to accurately predict whether shipments can be made as scheduled goods Huang Changding also specifically stated that the machine learning of Naili Technology is not ordinary machine learning, but also incorporates various calculation methods such as traditional image processing technology and statistics Only by being very familiar with the domain knowledge can we make good products AI models are also where the company’s competitiveness lies He emphasized that the data that general SaaS platforms can process is very limited, and the accuracy rate has increased from 70 to 75 at most Naili’s strength lies in AI algorithms and machine learning, and it must be coupled with in-depth industry knowledge to produce output Good AI model Narili Technology started with the AI project, gradually deepened the technology, chose to start with the more difficult tasks, and accumulated rules of thumb It is expected to develop SaaS services this year 2022, based on customer needs starting point, gradually gaining a foothold and becoming an important partner in smart manufacturing The picture left shows the general manager of Naruili Technology Tang Guowei and Chairman Huang Changding right「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」