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Customer Satisfaction

22
Oct
Pengenalan Talkbot
10 Cara Talkbot Membantu anda Meningkatkan efisiensi call center
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

Efisiensi call center sangat erat kaitannya dengan kemampuan dan biaya operasional. Sebagian besar bisnis kesulitan untuk tetap fleksibel dan menjaga kualitas layanan yang konsisten, karena kondisi bisnis yang mudah berubah. Untuk itu, WIZ AI menawarkan solusi mutakhir untuk menyelesaikan masalah-masalah bisnis yang terjadi akibat perubahan permintaan, tingkat perputaran karyawan, integrasi sistem yang buruk, dan masalah-masalah lain yang mungkin muncul. Untuk lebih memahami bagaimana WIZ AI dapat membantu anda menyelesaikan masalah-masalah tersebut, berikut bahasannya. 

1. Otomasi Berbasis Kecerdasan Buatan (AI)

Saat bicara soal pelayanan pelanggan, kebanyakan pelanggan lebih suka berbicara dengan manusia dibandingkan dengan sistem otomatis. Berbicara dengan robot atau “bot” membuat pelanggan merasa tidak nyaman, atau bahkan tidak dihargai. Hal ini lah yang menjadi alasan mengapa sistem call center otomatis kadang membuat perusahaan merasa serba salah. Di satu sisi, call center dapat membantu perusahaan mengurangi biaya operasional secara signifikan. Di sisi lain, perusahaan harus mengorbankan kualitas layanan yang pastinya akan berdampak pada kepuasan pelanggan. Mengingat hal ini, WIZ AI mengembangkan Talkbot sebagai solusi terbaik call center, yang dilengkapi dengan teknologi percakapan suara hiper-realistik, yang mampu berkomunikasi dengan pelanggan dalam bahasa yang digunakan oleh negara-negara di ASEAN seperti Bahasa Inggris, Singlish, Mandarin, Filipina, dan Bahasa Indonesia. Hal lain yang spesial dari Talkbot WIZ AI adalah kemampuannya untuk melakukan interupsi, mengenali maksud, dan melanjutkan percakapan dengan statemen klarifikasi maupun pertanyaan yang sesuai. layaknya agen manusia. Selain itu, Talkbot WIZ AI terdengar sangat natural, 95% pengguna bahkan tidak tahu jika mereka sedang berbicara dengan bot. Jadi, dapat disimpulkan bahwa mengotomasi call center dengan talkbot dapat membantu perusahaan mengurangi biaya operasional, tapi dengan tetap menjaga kualitas layanan terbaik. 

2. Menjaga Best Practice

Dalam masa pengembangannya, Talkbot dibuat dengan referensi standar terbaik dalam bidang layanan pelanggan. Talkbot WIZ AI dilatih berdasarkan seluruh percakapan panggilan telepon yang berhasil dilakukan oleh agen call center. Setelah itu, Talkbot akan secara otomatis merapikan dialog dan mengadopsi pendekatan alur pekerjaan yang terstandar untuk memenuhi objektif bisnis untuk setiap skenario panggilan yang dibutuhkan. 

Dulu, pelatihan staf pelayanan pelanggan merupakan salah satu kunci bagi call center untuk meminimalisasi inkonsistensi dan kegagalan dalam pelayanan. Tapi, dengan teknologi-teknologi di balik Talkbot perusahaan tidak perlu lagi bergantung pada program pelatihan staf pelayanan pelanggan untuk memberikan kualitas layanan terbaik. Ini juga berarti waktu yang dibutuhkan untuk melatih agen baru dapat dikurangi. 

3. Solusi One Call

Kelebihan sistem WIZ AI terkait desain dan manajemen percakapan dapat dicapai karena basisi pengetahuan yang kuat. Tidak seperti agen manusia yang mungkin harus menyelesaikan masalah di lain waktu karena tidak memiliki pengetahuan yang cukup tentang masalah yang dihadapi, Talkbot WIZ AI dapat menangani berbagai pertanyaan (FAQ) dan melakukan tugas-tugas rutin secara konsisten. Saat Talkbot tidak dapat menyelesaikan masalah yang dihadapi oleh pelanggan, Talkbot dapat secara otomatis mengalihkan panggilan ke agen atau pihak-pihak terkait yang lebih memahami permasalahan yang dihadapi pelanggan. Dengan sistem seperti ini, kesulitan yang dialami pelanggan dapat diselesaikan secara efektif dan efisien dalam 1 panggilan telepon.

4. Mengurangi “Waktu Diam” Dalam Panggilan Telepon

Agen call center adalah ujung tombak perusahaan dalam menjangkau pelanggan. Tapi, mereka tidak selalu dapat memberikan pelayanan dan pengalaman terbaik bagi pelanggan. Karena terkadang ada faktor kesalahan manusia yang menghalangi agen untuk memberikan usaha terbaiknya. Salah satu hasil dari kesalahan manusia dalam call center atau layanan masyarakat ada adalah “dead air”. Dead air atau “waktu diam” adalah kondisi saat tidak terjadi percakapan dalam panggilan telepon dalam periode waktu yang cukup lama. Waktu diam dalam panggilan membuat durasi panggilan telepon menjadi lebih lama, yang mungkin dapat membuat pelanggan pengalaman telepon yang buruk, yang akhirnya dapat membuat pelanggan hilang kepercayaan. 

Waktu diam biasanya terjadi karena beberapa hal seperti; kebiasaan buruk agen, agen yang belum berpengalaman, atau ketika pelanggan bertanya tentang hal-hal yang tidak familiar bagi agen. Terlepas dari alasan terjadinya waktu diam dalam panggilan, pelanggan biasanya menginterpretasikan hal tersebut sebagai ketidakmampuan agen layanan pelanggan dalam menyelesaikan masalah yang sedang mereka hadapi. Alhasil, pelanggan akan memiliki pengalaman dan impresi yang buruk. Untuk itu Talkbot dikembangkan dengan teknologi yang mampu menjamin respons langsung untuk pertanyaan pelanggan dalam 0.5 detik. Dengan begitu, waktu diam dalam panggilan telepon dapat berkurang secara signifikan sehingga pelanggan memiliki kepercayaan lebih. 

5. Waktu Tunggu Lebih Singkat

Ketika terjadi peningkatan volume panggilan telepon yang berlebihan, perusahaan tidak memiliki pilihan selain membuat pelanggan menunggu untuk periode waktu yang lama. Untuk menyelesaikan masalah ini, Talkbot WIZ AI merupakan solusi tepat. Bersama WIZ AI perusahaan dapat meningkatkan kemampuan call center untuk menjangkau lebih banyak pelanggan dalam waktu yang singkat dan dengan biaya sangat murah. Dibandingkan menyewa jasa call center outsource, memasang perangkat baru, mempekerjakan lebih banyak agen, dan mempersiapkan pelatihan agen baru yang mengambil banyak waktu dan tenaga,  perusahaan dapat langsung menambahkan jumlah Talkbot ketika menghadapi peningkatan volume panggilan dalam situasi krisis. Talkbot dapat dengan mudah di scale up dari satu menjadi seratus dalam waktu singkat. Dengan Teknologi WIZ AI, perusahaan menjadi lebih siap menghadapi peningkatan volume panggilan yang tak terduga, pelanggan pun tidak perlu menunggu dan terabaikan untuk waktu yang lama.  

6. Mengurangi Tugas Rutin

Disamping memberikan kualitas layanan pelanggan yang konsisten, Teknologi Talkbot buatan WIZ AI juga membantu perusahaan anda untuk mendapatkan informasi pelanggan yang lengkap melalui dashboard yang komprehensif dan user friendly.. Sistem WIZ.AI akan mengumpulkan, mencatat, dan menganalisa data dari seluruh panggilan telepon yang dilakukan, untuk menyediakan informasi mendalam tentang performa bisnis anda dan preferensi pelanggan. Contohnya, salah satu pertanyaan yang sering ditanyakan oleh para pelanggan dapat memberikan informasi relevan tentang respon pasar terkait produk yang ditawarkan kepada pelanggan, atau permintaan bantuan dari pelanggan dapat memberitahu perusahaan tentang kekurangan dari produk atau layanan yang ditawarkan. Dengan data yang jelas dan lengkap, perusahaan dapat membuat rencana lanjutan, dan meningkatkan aspek layanan yang relevan. 

7. Identifikasi Lead Berkualitas

Disamping kemampuan untuk memberikan layanan secara realtime, WIZ AI memiliki laporan data pelanggan yang sangat berguna untuk mengidentifikasi pelanggan dengan nilai tinggi. Dengan memanfaatkan informasi preferensi dan kebiasaan pelanggan yang didapatkan dari data mendetail panggilan telepon, perusahaan dapat membuat pelatihan telemarketing yang sesuai untuk Talkbot, dan kemudian mengotomasi panggilan keluar (Outbound call). Dengan kedua teknologi ini, perusahaan dapat dengan signifikan meningkatkan efektifitas dan efisiensi operasional call center. 

8. Kecerdasan Buatan yang Terus Berevolusi

Dalam operasi call center tradisional, manajemen bergantung pada pelatihan yang regular dan berulang untuk menjaga kualitas layanan, tapi hasil dari pelatihan tersebut tidak dapat langsung dirasakan. Dibandibandingkan dengan hal tersebut, Talkbot WIZ AI merupakan solusi yang jauh lebih baik. Dilengkapi dengan fungsi Automatic Speech Recognition (fungsi pengenal bahasa otomatis), Talkbot dapat melakukan uji bahasa dalam setiap interaksi dengan pelanggan, yang meningkatkan akurasi dari sistem tersebut dalam setiap panggilan telepon. Selain itu, dialogue engineer yang memiliki fungsi yang mirip dengan pelatih di call center, akan melakukan evaluasi dan pelatihan untuk terus meningkatkan kemampuan Talkbot. Jika dibutuhkan kemampuan atau fungsi baru untuk membantu operasi bisnis, Talkbot dapat langsung mempelajari kemampuan dan fungsi tersebut. Setelah itu, Talkbot akan memberikan pengalaman interaksi pelanggan terbaik dan terus berkembang sesuai dengan data  yang dikumpulkan.

9. Integrasi Omnichannel

Berpindah-pindah database atau platform layanan tertentu bisa memakan banyak waktu yang mengakibatkan aktivitas operasional yang lamban dan tidak efisien. Karena itulah, teknologi WIZ AI dapat dengan mudah diintegrasikan dengan sistem Omnichannel. Salah satu contohnya, saat diintegrasikan dengan suatu sistem, Talkbot WIZ AI dapat mengakses informasi pelanggan lewat sistem CRM yang terintegrasi untuk mengidentifikasi pelanggan dengan nilai tinggi dan melakukan panggilan keluar untuk menawarkan produk baru bagi pelanggan. Setelah melakukan panggilan, Talkbot dapat langsung mengaktifkan sistem pesan yang sudah terintegrasi dan mengirimkan informasi detail produk yang baru saja ditawarkan. Dengan kemampuan integrasi omnichannel, Talkbot WIZ AI dapat merespon pelanggan dengan cepat, dan memberikan layanan terbaik, sehingga pelanggan merasa aman dan nyaman dalam menyelesaikan kendala yang dialami. 

10. Optimasi Sumber Daya dan Biaya Operasional Murah

Dengan kehadiran talkbot yang menangani tugas-tugas repetitif dan rutin, agen call center memiliki lebih banyak waktu untuk melayani pelanggan bernilai tinggi. Selain itu, tanpa bergantung pada sumber daya manusia yang masif, perusahaan tidak perlu lagi mengeluarkan biaya ekstra untuk perangkat keras, aktivitas rekrutmen, pelatihan, dan biaya operasional yang melibatkan agen manusia. Dan yang paling penting, perusahaan yang memiliki sistem Talkbot dapat terhindar dari kerugian finansial yang diakibatkan oleh kegagalan layanan dan kehilangan pelanggan.


22
Oct
e-commerce AI
Pengenalan Talkbot
Transformasi E-commerce Melalui Kecerdasan Buatan
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

e-commerce AI

Industri E-commerce tumbuh subur dalam beberapa tahun terakhir dan telah menjadi bagian penting dari hidup banyak orang. Sementara itu, Kecerdasan Buatan (AI), yang digunakan dalam berbagai aspek e-commerce menjadi kunci utama bagi pertumbuhan e-commerce. Mulai dari sistem untuk meningkatkan kualitas interaksi dengan pelanggan sampai sistem yang mampu memfasilitasi layanan pasca pembelian, AI menyediakan teknologi machine learning dan algoritma yang sangat berguna untuk meningkatkan pengalaman belanja online. Bahkan, beberapa tahun belakangan AI sudah mengelola hubungan pelanggan online tanpa campur tangan manusia.

Kelebihan AI untuk E-commerce
1. Predictive Marketing

Predictive marketing atau pemasaran yang diprediksi biasanya disangkut pautkan dengan big data dan machine learning. Dengan menggunakan kedua teknologi ini, pelaku e-commerce dapat mengumpulkan data pelanggan dari berbagai sisi, kemudian menggunakan data tersebut dengan bantuan kecerdasan buatan untuk membuat informasi profil pelanggan.

Ahli big data percaya bahwa algoritma mampu memahami manusia lebih baik daripada manusia. Hal ini masuk akal jika mengingat bahwa teknologi AI terdiri dari beberapa model fungsional seperti statistika, machine learning, dan deep learning, yang membantu AI memprediksi pola paling akurat. Jika diaplikasikan dalam industri marketing, teknologi ini mampu memprediksi informasi seperti selera pelanggan, tipe rumah tangga, permintaan musiman, dan informasi promosi yang paling efektif untuk menarik pelanggan.

 

2. Proses Penjualan Yang Efisien

AI membuat proses penjualan menjadi lebih efisien melalui beberapa cara seperti mengumpulkan informasi pelanggan, terintegrasi dengan sistem manajemen pelanggan (CRM), mengotomasi data agregasi pembelian, hingga hal-hal sederhana seperti sistem chatbot otomatis untuk membantu pelanggan dalam proses pembelian. Dengan menggunakan teknologi AI, merchant online dapat mengotomasi manajemen bisnis mereka untuk berbagai aspek, selain juga membebaskan mereka dari aktivitas simpel seperti pengaturan harga atau pelayanan pelanggan, yang biasanya membutuhkan bantuan manusia. selain itu, AI juga membantu melancarkan komunikasi antara penjual dan pembeli. Sistem AI yang mutakhir seperti milik WIZ AI mampu mengetahui maksud tersembunyi pelanggan dalam percakapan, yang dapat memberikan arahan bagi sistem untuk berkomunikasi dengan pelanggan dengan poin-poin yang lebih relevan. Dengan begitu, AI dapat melakukan komunikasi yang sesuai dan lebih efisien dengan pelanggan. Jadi, dapat disimpulkan bahwa dengan kehadiran AI penjual dapat melakukan pendekatan yang lebih pintar dan modern dalam mengajak pelanggan untuk membeli produk atau layanan yang mereka tawarkan.

 

3. Pelanggan Lebih Loyal

Tingkat retensi pelanggan berhubungan erat dengan tingkat personalisasi layanan atau produk yang ditawarkan. Memberikan pelanggan konten pemasaran dan pengalaman berbelanja yang dipersonalisasi merupakan salah satu cara untuk meningkatkan retensi pelanggan dan membuat pelanggan lebih loyal. Dengan teknologi AI, terutama deep learning, dan statistic modeling, pelaku e-commerce dapat melakukan analisa pelanggan mulai dari kebiasaan, demografi, dan informasi mendetail pelanggan lainnya dalam skala besar. Dari informasi yang dikumpulkan, pelaku e-commerce dapat membuat iklan khusus, mengirimkan email langsung, memberikan rekomendasi produk, hingga mengatur harga yang disesuaikan untuk berbagai tipe pelanggan. personalisasi berdasarkan data pelanggan dapat membantu pemilik bisnis untuk membangun hubungan emosional dengan pelanggan, yang mampu meningkatkan tingkat retensi pelanggan, yang juga membuat pelanggan menjadi lebih loyal.

 

Penggunaan AI pada industri E-commerce
1. Chatbot & Talkbot

Chatbot adalah sistem percakapan pintar yang merupakan bank pertanyaan yang sering diajukan (FAQ), yang diprogram untuk menjawab pertanyaan-pertanyaan dari pelanggan. Chatbot juga merupakan salah satu teknologi AI yang paling sering digunakan terutama dalam sistem layanan pelanggan 24 jam, termasuk pada industri e-commerce. Sistem ini merupakan solusi paling efisien untuk pekerjaan yang sifatnya repetitif seperti menjawab pertanyaan pelanggan, atau membantu pelanggan memutuskan barang apa yang akan dibeli. Selain chatbot, ada juga sistem yang dikenal dengan nama Talkbot dengan fungsi sama seperti chatbot. Bedanya, Talkbot dapat melakukan percakapan suara dengan pelanggan dan terdengar seperti agen call center manusia. selain menjawab pertanyaan pelanggan, Talkbot juga mampu membuat jadwal, mengirim pengingat, hingga melakukan panggilan keluar (outbound call) untuk untuk aktivitas telemarketing. Penggunaan Talkbot yang paling utama adalah untuk menyelesaikan masalah ketika terjadi peningkatan permintaan yang yang tinggi secara mendadak, mengurangi biaya operasional, dan membantu mempercepat pertumbuhan bisnis.

 

2. Pencarian Visual

Pencarian visual atau pencarian gambar adalah proses meniru proses yang sama saat manusia melihat dan mengidentifikasi suatu objek. Teknologi ini didesain untuk membuat poses pencarian menjadi lebih cepat dan mudah dengan cara mengambil atau mengupload foto ke mesin pencarian. Dalam teknologi pencarian visual, query atau input yang dimasukan ke mesin berupa gambar. Jadi, mesin pencari harus memahami gambar tersebut, bukan hanya mengenali. Teknologi pencarian visual membantu meningkatkan dan mengoptimasi hasil pencarian yang dilakukan pelanggan.

 

3. Manajemen Stok Pintar

Manajemen Stok atau dikenal juga dengan nama manajemen inventory adalah salah satu aspek strategis dalam manajemen merchant e-commerce. Sistem manajemen stok merupakan sistem yang lebih dari sekedar sistem untuk memindahkan dan menyortir stok. Sebuah manajemen stok pintar membutuhkan data dalam jumlah besar agar dapat beroperasi secara efisien. Seperti yang sudah disebutkan sebelumnya, kecerdasan buatan berguna dalam memprediksi permintaan. Dengan begitu, merchant dapat menggunakan teknologi ini untuk menyelesaikan masalah kekurangan atau kelebihan stok. Selain itu dengan kemampuan AI untuk melakukan data mining, merchant e-commerce dapat membangun transportasi pabrik ke gudang yang efisien, yang sangat penting terutama bagi produk yang memiliki waktu simpan yang pendek. Selain itu, sistem AI dapat meningkatkan efisiensi manajemen gudang. Sistem berbasis AI tanpa henti melakukan manajemen stok seperti melakukan pemindaian, menemukan, dan melakukan pembaruan informasi stok yang dapat dilakukan 24 jam tanpa henti.

Dengan kemampuan untuk menganalisa data, memprediksi permintaan, atau menyarankan rute pengiriman terbaik, AI merupakan salah satu teknologi terbaik bagi pelaku e-commerce untuk meningkatkan aktivitas manajemen stok.

 

4. Pengaturan Harga Dinamis

Pengaturan Harga Dinamis berbasis AI adalah sebuah sistem yang memiliki kemampuan untuk melakukan monitoring kompetitor, pengaturan ulang harga, hingga bantuan promosi. Dengan mengumpulkan informasi stok, suplai dan permintaan, ekspektasi pelanggan, dan informasi pasar lainnya sistem berbasi teknologi AI di e-commerce dapat melakukan pengaturan harga otomatis sesuai dengan kondisi pasat. Merchant online tidak perlu lagi secara manual memutuskan untuk memberikan diskon atau merubah harga. Pengaturan harga dinamis membuat proses pengaturan harga lebih efisien, sehingga dapat mengoptimasi profit secara bertahap.

 

Kesimpulan

Teknolog kecerdasan buatan telah hadir dan menjadi teknologi yang tidak lepas dari kehidupan kita, setidaknya hingga ada revolusi industri di masa depan yang akan mengubah kehidupan kita. AI telah terbukti mampu membantu bisnis menghemat waktu, pengeluaran dan tenaga yang dikeluarkan dalam seluruh aspek bisnis. Selain itu, harus diingat bahwa dalam iklim bisnis yang bersandar pada teknologi dan data, adalah suatu keharusan bagi pelaku e-commerce untuk paling tidak memahami bagaimana caranya untuk menggunakan AI untuk keuntungan bisnis mereka, agar bisnis mereka bisa terus berkembang, dan yang terpenting memiliki daya saing.


22
Oct
e-commerce AI
Talkbot Basics  ·  Teknologi Voice AI
Transforming Asian E-commerce Industry through Artificial Intelligence
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

e-commerce AI

Having grown at a rapid pace in the past few years, e-commerce has become an important part of many people’s lives. At the same time, artificial intelligence (AI), which has been embedded into various aspects of e-commerce, is becoming one of the key drivers behind this exponential growth. From improving customer interactions to facilitating post purchase services, AI provides merchants with powerful machine learning and algorithms to elevate the entire online shopping experience. In recent years, AI has already started managing online customer relationships without any human intervention.

Benefits of AI for E-commerce
1. Predictive Marketing

Predictive marketing is usually associated with big data and machine learning. With these two technologies, online retailers are able to collect customers’ data from various touchpoints. The data is then used to produce customer profiling with the help of artificial intelligence.
Dataism believes that algorithms could understand human beings better than human beings understand themselves, which is not unreasonable. Statistical modelling, machine learning, and deep learning enables AI to predict behavioural patterns accurately. Applied to marketing, this technology could predict things such as a consumers’ taste, household type, and seasonal demand. All this information can insights can help marketers design the most effective promotion for specific periods. E-commerce merchants can then create more effective sale strategies and be well prepared for future demand.

2. Efficient Sale Processes

AI creates a more efficient sales process by collecting customer insights, integrating with the existing CRM, and automating subsequent abandoned cart reminders. Even a simple chatbot can help customers in their purchasing activities. Leveraging on AI technology, online merchants can automate business management and free themselves from mundane tasks that used to require human support, such as price setting and answering frequently asked questions. In addition, AI helps enhance communication between merchants and customers. AI can quickly unlock customers’ hidden emotions during the conversation, providing guidelines for the system to communicate with the customer in a more relevant way. AI is able to engage with the customers more appropriately, and deliver the message more effectively. Retailers can thus lead customers through the funnel in a more intelligent and modern approach.

3. Increase Customer Retention

Customer retention is closely connected with the level of personalisation of product and service offers. Delivering personalised marketing content and shopping experiences to targeted audiences is one way to increase customer retention. With AI technology – in particular, deep learning and statistical modelling – e-commerce retailers can analyse consumers’ historical behaviour, demographics, and other information at scale. Retailers can then generate personalised advertisements, send direct emails, recommend products, and set prices uniquely suited to the shopper. Intelligent personalisation helps online business owners to build stronger emotional connections with their customers, and therefore increase customer retention and make customer more loyal.

The use of AI in E-commerce
1. Chatbot & Talkbots

Chatbot can be programmed to answer routine inquiries to customers, becoming an intelligent Frequently Asked Questions (FAQ) bank. It is one of the AI technologies that is used the most frequently in supporting 24/7 customer service in the e-commerce industry. The Chatbot mainly provides prompt solutions for routine questions and helps customers with their purchase decision. Talkbots or voice bots, on the other hand, provide human-like conversational voice support over the phone, thanks to artificial intelligence. Unlike the chatbot sitting at the landing page, the Talkbot is usually deployed in call centers. Other than answering customer inquiries, the Talkbot is able to help the retailer manage schedules, send out reminders, and conduct outbound telemarketing tasks as well. Talkbots primarily ease the pressure caused by surge of demand, helping reduce operating costs and accelerate business growth.

2. Visual Search

Visual search is the process of mimicking the same processes that people use when we see and identify objects. This technology is designed to make the search process quick and easy by taking or uploading photos to the engine. For visual search, an image is used as a query. Search engines will need to understand it instead of just recognizing the image. Visual search vastly helps to enhance and optimize customers’ search results when shopping online.

3. Intelligent Inventory Management

Inventory management is one of the strategic areas for e-commerce merchant management. It is much more than delivering items from one place to another and sorting them out. Intelligent inventory management relies on large amounts of data to achieve operational efficiency. As mentioned above, artificial intelligence helps with better demand prediction, which at the same time resolves issues of inventory overstock and understock. Also, supported by AI data mining, e-commerce retailers can build efficient factory-to-warehouse transportation, which is critical for products with shorter shelf lives and higher demand volatility. AI bots can also boost inventory management efficiency by scanning and locating stock, then updating stock information.

Combined with capabilities of analyzing data, predicting demand, and suggesting the best delivery route, AI is becoming a powerful technology for retailers to expand inventory management capacity and improve merchant services.

4. Dynamic Pricing

AI-enabled dynamic pricing is the suite of tools that include competition monitoring, automatic repricing, and promotion assistance. By collecting information of inventory conditions, supply and demand relations, customer expectations, and other market information, AI technology can automate the pricing process. Online merchants no longer need to decide the discount and amend the price manually. Dynamic pricing improves the efficiency of the entire pricing process, which in return will optimize the profit for the merchants over time.

Conclusion

Artificial intelligence has been proven to be able to save businesses a lot of effort, time, and money in every aspect of their business. In a tech-crazy and data driven climate, AI is a must for many e-commerce business owners to keep businesses competitive edge.


11
Oct
Pengenalan Talkbot
Apa Itu Talkbot?
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

Teknologi Artificial Intelligence yang mampu mendengar, memahami, bahkan berkomunikasi seperti kita

Jadi, sebenarnya apa itu Talkbot? dan yang lebih penting lagi bagaimana Talkbot dapat membantu bisnis anda? Sebelum kita berbicara lebih jauh tentang Talkbot, pertama-tama kita harus memahami bahwa Talkbot bukan hanya sebuah perkembangan drastis dalam teknologi masa depan, melainkan puncak dari berbagai penelitian dan pengembangan tentang artificial intelligence (A.I.) selama beberapa dekade.

Pada tahun 1950-an, Alan Turing, — bapak dari Ilmu Komputer (Computer Science) — pertama kali mengusulkan sebuah sistem pengujian yang kemudian dikenal dengan nama Uji Turing (Turing Test). Turing berpendapat bahwa komputer dikatakan memiliki artificial intelligence (kecerdasan buatan) jika dapat menunjukkan perilaku seperti manusia yang tidak dapat dibedakan. Tujuan dari Uji Turing adalah untuk membuktikan kemampuan komputer dalam menunjukan perilaku cerdas layaknya manusia. Jika manusia sebagai penilai dapat “ditipu” dan berpikir mereka sedang mengobrol dengan manusia lain yang sebenarnya adalah sebuah program komputer, maka program itu dianggap lulus Uji Turing. 

Pada tahun 2013, Uji Turing akhirnya dikalahkan oleh sebuah program bernama Eugene Goostman saat didemonstrasikan di University of Reading. Namun, tes-tes tersebut hanya dilakukan lewat tulisan, program-program komputer ini sekarang dikenal sebagai chatbots atau asisten virtual (Virtual Assistant).

Langkah selanjutnya yang terbaik dalam pengembangan artificial intelligence adalah membuat asisten virtual yang dapat berinteraksi dengan manusia melalui bahasa dan cara berbicara layaknya manusia. Pengembangan inilah yang menjadi awal terciptanya beberapa aplikasi percakapan A.I seperti Siri dari Apple dan Alexa dari Amazon yang telah mempermudah hidup jutaan orang setiap harinya. 

Terlepas dari pencapaian tersebut, aplikasi penggunaan ini masih satu dimensi dan hanya memiliki fungsi robotik terbatas yang disebabkan oleh kurangnya pengembangan pada fungsi-fungsi yang spesifik. Contohnya, anda dapat bertanya kepada Siri dimanakah restoran pizza terbaik, tapi siri tidak dapat memesan atau menyesuaikan pesanan sesuai keinginan anda. siri juga tidak dapat menawarkan produk unik dari perusahaan anda kepada calon konsumen dalam jumlah besar.

 

Memperkenalkan Talkbot

Di sinilah Talkbot berguna. Talkbot adalah asisten percakapan suara dengan kecerdasan artifisial (Voice A.I.) khusus, yang dapat mewakilkan anda melakukan pekerjaan dan dapat mengotomasi berbagai tugas rumit yang harus diselesaikan melalui percakapan di telepon. 

Talkbot yang baik tidak hanya berbicara seperti manusia, tapi juga memiliki pemahaman seperti manusia. Di WIZ.AI, kami memiliki tim peneliti data khusus yang telah mendedikasikan waktunya selama bertahun-tahun menyempurnakan solusi ini untuk pelanggan kami.

A.I. Talkbot yang dibuat oleh WIZ.AI menawarkan Voice A.I. dengan suara hyper-realistic  untuk berinteraksi dengan konsumen lewat telepon— begitu realistis, hingga 95% dari konsumen tidak menyadari bahwa mereka sedang berbicara dengan sebuah kecerdasan buatan.

Walaupun bahasa manusia memiliki nuansa yang spesifik, makna yang ambigu, dan sering kali bergantung pada konteks dan nilai budaya, dengan menggabungkan sistem natural language processing (NLP) yang dimiliki WIZ.AI dan teknologi automatic speech recognition (ASR) memperbolehkan Talkbot untuk dapat memahami maksud dari suatu statement, dan akhirnya menghasilkan percakapan yang tidak dapat dibedakan dengan percakapan antar manusia.

Hal yang berkontribusi membuat Talkbot memiliki suara hyper-realistic adalah kemampuannya untuk mengidentifikasi dan merespon interupsi dalam panggilan telepon, serta kemampuannya untuk mendengar secara terus menerus. Saat penelepon merasa bingung dan terdiam, atau meminta untuk mengulangi sebuah statement, Talkbot dapat memberikan respon lanjutan atau klarifikasi sehingga Talkbot dapat menjaga perbincangan agar terus berlanjut.

Kami secara progresif meningkatkan akurasi sistem ASR dan Natural Language Understanding (NLU) lewat pelatihan model NLU yang kami lakukan secara reguler, di samping memperluas perpustakaan percakapan kami berdasarkan data percakapan dengan konteks yang spesifik. Kami akan terus membangun dan meningkatkan Voice A.I. kami untuk menyediakan pengalaman telepon terbaik bagi pelanggan kami. 

 

Bagaimana WIZ.AI dapat mengoptimalkan bisnis anda?

Talkbot yang kami bangun adalah bagian dari teknologi baru yang memastikan bahwa  tugas-tugas repetitif, seperti menelpon klien untuk mengingatkan mereka tentang pembayaran hutang dan pembuatan janji dapat sepenuhnya dilakukan secara otomatis. Dengan begitu, tenaga kerja anda dapat diarahkan ke aspek-aspek lain dimana kemampuan agen call center anda dapat dimanfaatkan sebaik-baiknya. Selain itu, pelanggan dengan waktu terbatas mampu mendapatkan respon atas permasalahan mereka dengan cepat, efficient, dan effective. Berlawanan dengan interaksi pelanggan (customer engagement), Talkbot memperbolehkan klien untuk mengubah percakapan pada panggilan telepon menjadi lebih proaktif. 

Ketika call center mengalami lonjakan panggilan telepon tak terduga dalam volume yang tinggi, seringkali terjadi kekurangan staff untuk merespon seluruh telepon yang masuk. A.I. Talkbot mampu menangani peningkatan volume penelepon pada situasi tidak terduga. Ditambah lagi, dalam situasi seperti pandemi covid-19, Talkbots dapat menjadi solusi penurunan jumlah tenaga kerja. Sebagai tambahan, efisiensi tenaga kerja adalah bentuk konsolidasi seluruh best practice yang harus dilakukan oleh seluruh agen call center ke dalam satu entitas, yakni Talkbot.

Tidak akan ada kesulitan dalam belajar atau waktu yang dihabiskan untuk melatih seluruh tim call center, belum lagi usaha lanjutan untuk memonitor panggilan sebagai upaya memastikan bahwa para agen call center telah bekerja sesuai dengan arahan yang telah diberikan. Sebaliknya, Talkbot memastikan secara konsisten standar layanan di call center tetap tetap tinggi dan terus ditingkatkan secara berkala dengan lewat sistem machine learning models yang kami kembangkan. Selain itu, meningkatkan kualitas call center untuk melayani jumlah konsumen yang banyak dengan beberapa bahasa yang berbeda tidak lagi menjadi tugas berat bagi departemen Human Resource. berkat kemampuan Talkbot yang dapat disesuaikan dengan kebutuhan anda. WIZ.AI saat ini mendukung bahasa Inggris, Mandarin dan Bahasa Indonesia — bahkan bahasa dengan aksen seperti Singlish. Hal ini memungkinkan bisnis untuk mengelola basis pelanggan mereka dengan lebih baik lewat penggunaan bahasa lokal..

Mengingat fakta bahwa seluruh aspek bisnis semakin banyak menggunakan tenaga outsourcing, terutama agen-agen call center, Talkbot juga memungkinkan perusahaan untuk kembali mengatur aktivitas branding dan marketing. Sekarang dapat dipastikan dengan lebih bahwa Talkbot yang anda miliki dapat merepresentasikan identitas perusahaan anda, dan lebih penting lagi, mewujudkan perubahan, dan secara konsisten menjaga kualitas layanan tetap tinggi.

Saat kotak masuk email kita terus dibanjiri dengan konten-konten promosi, komunikasi verbal masih tetap menjadi medium utama yang kita andalkan untuk mengekspresikan maksud dan tujuan kita serta untuk mengajak orang lain untuk melakukan sesuai. Talkbot dengan A.I. ini dilengkapi dengan kemampuan untuk menyampaikan pesan tepat waktu dan mempermudah interaksi langsung dengan pelanggan anda. hal inilah yang dapat membangun loyalitas pelanggan anda. yang juga berarti kesuksesan dibalik investasi marketing anda. 

Talkbot WIZ.AI juga dapat langsung diintegrasikan dengan sistem call center yang anda gunakan sekarang, termasuk juga dengan relationship management software seperti WhatsApp, Email, atau perangkat-perangkat lain yang anda gunakan untuk menjaga hubungan yang baik dengan pelanggan anda.

Inovasi berbasis Data

Untuk memastikan keuntungan investasi yang lebih tinggi, perusahaan harus tahu apa yang harus ditingkatkan, dan bagaimana caranya. Talkbot mampu memberikan memberikan pengetahuan mendalam secara empiris tentang panggilan telepon yang sudah dilakukan dengan konsumen, sehingga penyesuaian dan peningkatan kualitas panggilan dapat dilakukan sesuai tujuan dan terarah. Sebagai contoh, Talkbot kami memungkinkan anda untuk mengidentifikasi saat panggilan diputus karena pelanggan merasa bosan atau merasa tidak terbantukan, dengan begitu anda tahu jika anda harus memperbaiki skrip telepon untuk memastikan interaksi konsumen yang lebih baik. Dengan kata lain, peningkatan kualitas berdasarkan data dapat dilakukan untuk memastikan Talkbot anda memenuhi tujuan bisnis anda dari waktu ke waktu.

Saat ini aktivitas marketing yang personal atau ditargetkan sangat marak dan telah terbukti secara efektif mendorong penjualan, A.I. Talkbot dapat digunakan dalam pendekatan serupa. Setelah kita mengetahui karakteristik pelanggan, Talkbot dapat disesuaikan untuk memenuhi kebutuhan pelanggan anda dan sebagai gantinya, informasi yang diperoleh dari log panggilan juga dapat digunakan untuk meningkatkan sistem A.I. lebih jauh dalam hal membuat skrip yang lebih strategis untuk memastikan kualitas layanan terbaik dapat tercapai, selain juga memastikan peningkatan rasio konversi. 

Teknologi canggih seperti Talkbot adalah kunci untuk mengoptimalkan pekerjaan di call center dan menurunkan biaya operasional. Teknologi ini pasti akan merevolusi aktivitas manajemen pelanggan dan akan membawa bisnis anda ke level berikutnya. 

 

26
Feb
Talkbot Basics
Chatbot VS Talkbot
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

What is a chatbot?

Have you ever encountered a pop-up along the sidebar of the website you are browsing, asking if you need help? That would be a chatbot. Driven by emerging technology in Artificial Intelligence, chatbots use Machine Learning (ML) and Natural Language Processing (NLP) to understand and answer a range of questions that are commonly asked. Given that chatbots can answer queries at any time— even in the dead of the night – they have become a popular form of technology adopted by many businesses looking to make the most of their website traffic.

However, chatbots are generally limited in their capabilities. While they are fed with a answer script that mirrors the way call centre service agents respond, chatbots usually only provide very general answers to a selected range of queries which may or may not be satisfying to the customers. More often than not, complex questions and requests would still require escalation to a customer service agent before they can be resolved.

Examples of common FAQ questions handled by a chatbot may include the operating hours of the company, or directions to their office. While the chatbot is able to fulfill some fundamental needs of a business through its on-demand service or prompt clarification of basic queries, the answers are mostly structured with little variance to the questions asked.

What then is a Talkbot?

A Talkbot, on the other hand, is more than a simple bot service. Involving more customisation to build, Talkbots are highly sophisticated customer service tools which are able to understand the user’s natural spoken language. A combination of technologies which include Natural Language Understanding (NLU), Natural Language Processing (NLP), Automatic Speech Recognition (ASR) and Machine Learning (ML) allows the Talkbot to understand questions in context and even detect and handle multi-intentions in a single sentence.

With its more nuanced understanding of the user’s queries, the conversation becomes more life-like, allowing a multitude of questions that can be posed and answered. Beyond simply fulfilling a passive role in the dialogue, the Talkbot is capable of initiating conversations and thereby prompt deeper engagement in any assigned topics—A key to building customer loyalty for your business.

A more superior solution to chatbots, Talkbots are able to proactively call on customers and engage in a realistic conversation. In other words, it is no different from a customer service agent. This is the magic of conversational A.I., which has the potential to supercharge your customer service standards.

What should I use? Chatbot or Talkbot?

It depends largely on the needs of your company. As mentioned earlier, chatbots are easily deployed and capable of answering simple queries like the email address of your office or even a list of services you provide in a short and concise manner, at any given time of the day. To a certain extent, they can also provide valuable insights by tracking what the common questions from your customers are. However, chatbots take a more passive role in the dialogue, are capable only of answering questions asked in a direct manner, and are often not able to understand and operate on contexts. When dealing with a chatbot, the customer would also have to be the more proactive party who initiates the conversation.

In contrast, Talkbots utilising conversational A.I technologies are able to proactively engage with customers in multi-round dialogues and can even handle vague responses in various contexts. Its capabilities can be deployed in a wide range of applications, across both inbound and outbound scenarios, such as FAQ hotline, appointment reminder calls, debt collection, customer surveys, cold calls, making them viable solutions for companies facing labor shortages during peak business periods or labor attrition problems. 

As opposed to using a human agent, Talkbots provide specific and useful customer insights to businesses as they are capable of tracking the call conversation and sieving out critical intentions. The Automatic Speech Recognition function in Talkbots allows all calls to be automatically logged, transcribed, labeled, and filed away for future action.

With Talkbots being more data-driven as compared to chatbots, audience segmentation can commence with ease, allowing for more targeted and strategic marketing efforts. In the long run, the Talkbot system can be continually improved with machine learning and can be tweaked to meet your customer’s ever changing needs.

It is not surprising that customers who surf the net often are able to easily identify who they are speaking to, whether it is a bot or a human agent. Customers may still feel distant from the companies they approach, even when there is a chatbot, because they know that this process of answering their queries are often automated. However, 95% of users are unable to distinguish between a Talkbot and a human agent. Talkbots listens, understands and speaks several different ASEAN languages with localised accents, it even incorporates human-like actions such as pauses, clarification statements and chasing statements. Furthermore, the text to speech (TTS) function of the Talkbot allows for the A.I’s voice to be programmed to read out certain client details. So instead of a cookie-cutter, generalised answer, Talkbots are able to embed the client’s information into their responses and this would facilitate a more personalized and realistic experience. For instance, Wiz. A.I’s bots are able to embed your date of purchase of an item into parts of the conversation in order to better relay information that might be useful for you.

The key defining feature that differentiates the Talkbot from the chatbot is the Talkbot’s ability to build a stronger relationship between the customer and your business. Picture this: When someone gets a call from a clinic to remind them of an appointment or if patrons of a website hosting service are called to be reminded of a free service that can boost their website traffic, the business will often come off as sincere and conscientious and this is enough to build a strong brand loyalty. With the Talkbot’s ability to proactively engage the clients and provide them with a customer service experience that highly resembles that of a human agent, Talkbots can automate repetitive processes and contribute to the optimization of your workforce.

Both the chatbot and the Talkbot are all part of our efforts to automate and optimise work efficiency. Before choosing which is better for your business, it is the best to think about your immediate and long term goals and how these two intelligent machines can meet your business needs.

 


29
Jan
Talkbot Basics
What is a Talkbot?
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

Voice Artificial Intelligence that listens, understands and even sounds like us

What exactly is a Talkbot and more importantly how can it improve your business? But before we talk (pun intended) about Talkbots, we need to first understand that it is not just a quantum leap in futuristic technology but the culmination of decades of research and development into Artificial Intelligence (AI).

In 1950, Alan Turing—the father of computer science—first proposed a test which became known as the Turing test. Turing proposed that a computer is said to possess artificial intelligence if it can exhibit human-like behaviour, indistinguishable from that of a human. The goal of the test was to showcase a computer’s ability to exhibit intelligent behaviour and if human evaluators were able to be “fooled” into thinking they were chatting with a human when it was in fact a computer programme, that programme would have been deemed to have passed the Turing test.

In 2013, that test was finally passed by a programme called Eugene Goostman, during a demonstration at University of Reading. However, that test was done using text and today, these computer programmes became known as chatbots or virtual assistants.

The next natural step for artificial intelligence development was to create a virtual assistant which could interact with a human through natural spoken language. This has led to popular applications of conversational A.I. like Apple’s Siri and Amazon’s Alexa which assist millions of lives every day. Despite such progress, these consumer applications still remain one dimensional and have limited robotic functionalities due to the lack of development in certain specialised verticals—e.g. you can ask Siri where the best pizza restaurant is but she cannot order or customize the pizza on your behalf nor can she sell your firm’s unique product offering to masses of prospective customers.

Enter the Talkbot

This is where Talkbots come in. Talkbots are highly specialised conversational voice AI assistants that can do the work on your organisation’s behalf and automate the many complex tasks needed to be achieved over a phone conversation.

A good Talkbot is not only one that speaks like a human but also understands like one. At Wiz.AI, we have a team of highly specialised data scientists who have spent years refining our solution for our customers.               

Wiz.Ai’s conversational AI Talkbots provide a hyper-realistic voice AI experience that engages customers through phone calls—so realistic that 95% of users do not recognise that they were talking to a voice AI in a real-life scenario.

Even though the human language is dotted with nuances, ambiguities and is often reliant on context and cultural cues, Wiz.AI’s natural language processing engine coupled with its customisable automatic speech recognition (ASR) technology enables the intents to be recognised, thereby facilitating conversations that are virtually indistinguishable from human-to-human ones.                         

What contributes to its hyper-realism is the Talkbot’s ability to identify and handle interruptions during calls and to listen continuously. When the caller has expressed confusion by keeping silent or is asking for a repeat of the statement, the Talkbot is able to pose clarification statements or chasing statements, thus maintaining the conversational nature of the Talkbot

We progressively improve our system’s ASR accuracy and natural language understanding (NLU) through regular NLU model training and the expanding of our speech corpus based on context-specific speech data. We continue to build and refine each successful AI model to give the most seamless call experiences to customers.

How can Wiz.AI optimize my business operations?

The Talkbots we build are part of an emerging technology that ensures rule-based tasks or repetitive jobs, such as calling clients to remind them about their debt payment and appointment dates, can be fully automated. This way, valuable labour can be channelled to other aspects where the expertise of the call centre agents can be fully utilised. Additionally, time-crunched customers are able to get direct responses to their problems, efficiently and effectively. As opposed to a reactive customer engagement, the Talkbots enable clients to shift their call conversations to ones that are more proactive.

When call centres experience unforeseen times of high-volume surge in calls, there may be a shortage of labour to respond to every call. Conversational AI Talkbots are able to handle the increased call volume in unexpected situations like these. Furthermore, in the context of Covid-19, Talkbots could also be a solution to labour attrition.

To add, labour efficiency comes in being able to consolidate all the best practices of your call centre agents into one entity—the Talkbot. There would not be any steep learning curve or time spent training an entire team, not to mention the follow-up action of having to monitor the calls to ensure that the directions have been adhered to. Instead, the Talkbot ensures that the service standard in the call centre is kept consistently high and is continuously improved over time with our machine learning models. Additionally, scaling up the call centre to cater to a multilingual audience is no longer a Herculean task for the HR department all thanks to the high customisability of a Talkbot. Wiz.AI currently supports English, Mandarin and Bahasa Indonesia—even creoles such as Singlish. This allows businesses to better manage their customer base in the forms of local languages.

Given that everything is becoming increasingly outsourced, especially call centre agents, Talkbots also allow for companies to once again take control of their branding and marketing. It is now easier than ever to ensure that your Talkbot embodies your company persona and more crucially, concretize changes and keep the service standards consistently high.

While our inboxes continue to be flooded with promotional emails, voice communication nevertheless remains a medium that is heavily relied on to express our thoughts and to catalyse actions. Conversational A.I Talkbots are equipped with the ability to deliver timely messages and facilitate direct interaction with your customers, and this in turn builds customer loyalty and hence higher returns on marketing investments.

Data-driven innovation

To ensure higher returns on investment, businesses would definitely need to know how and what to improve on. Talkbots provide empirical insights into what the calls were like so that changes can be intentional and targeted. For instance, our Talkbot allows you to identify the common points where the call drops off which then prompts you to improve on the scripting to ensure higher levels of customer engagement. In other words, data driven upgrades can be made to ensure that your Talkbots meet your business goals over time.

Now that personalised or targeted marketing is all the rage and have proven to effectively drive sales, conversational AI Talkbots can be used in a similar approach. Once we have established a customer persona, talkbots can be engineered to tackle your customer’s needs and in return, the information obtained from the call log can also be used to further improve the AI system in terms of making the script more strategic in order to ensure that not only high service standards are achieved but also conversion rates are raised.

I already have a call centre system up and running, can I merge it with a Talkbot?

We can integrate our Talkbots with your pre-existing call centre systems as well as relationship management software such as WhatsApp or emails to maintain healthy customer relations.

Wrapping up

The cutting-edge technology that is a Talkbot is the key to optimizing work at call centres and lowering costs. This emerging technology is bound to revolutionize customer management and take your business to the next level.


17
Nov
Talkbot Basics  ·  Voice AI Technology
Understanding Asia – Natural Language Processing in AI
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

NATURAL PROCESSING LANGUAGE

 Natural processing language is an aspect of artificial intelligence and computer science that handle the interface between human languages and computers. It involves the computational modelling of different characteristics of language and the deployment of variety of systems. These systems include spoken language systems incorporate natural language with speech. NLP works with linguistic computational features, it employs computer in comprehending, handling speech and text of natural language to achieve useful feat. There are several fields NLP can be applied to; speech recognition, expert systems, artificial intelligence, cross language information retrieval (CLIR), text processing, language translation, speech recognition, and user interfaces. This innovative technology is saddled with getting computers to communicate and process human languages, and perform closer to human level of language thoughtfulness. Computers are yet to reach same instinctive comprehension of natural language like humans do. There is clear difference in the method in which human communicates with one another and the way they do with computers. During program development phase, the structure and syntax are carefully selected to suit the intended task, unlike conversing with other people whereby a lot of freedoms are considered. Ranging from sentence length, sarcasm and jokes, to several ways of expressing same thing.

Recent advancement in innovative technologies has enabled computers to perform range of things with human or natural language. Deep learning supports the implementation of programs to perform task like text summary, language translation, and semantics understanding. The rise in the implementation and application of artificial intelligence to our daily activities has made it ubiquitous. It is imperative for human to be able to communicate more with computers in the language we are familiar and comfortable with, speaking to computers in their natural language. Natural Language Processing (NLP) is seen as the canopy term that binds other natural language technologies which include Natural Language Understanding (NLU), Natural Language Generation (NLG), and Natural Language Interaction (NLI).

COMPLEXITIES OF UNDERSTANDING DIFFERENT LANGUAGES USING NATUAL LANGUAGE PROCESSING

Recently, significant feat has been recorded in enabling computers to comprehend human language using Natural Language Processing (NLP). Nevertheless, the multifaceted multiplicity and dimensionality features of data sets, make the execution a problem in some cases. Concerning implementation of NLP in Asia, with main focus on south East Asia, voice and text-based data and their practical applications will vary. In other to capture the whole process, NLP needs to include several diverse procedures for interpreting Asia local language. It could involve machine learning, statistical, algorithmic, or rules-based approaches. Ambiguity is an aspect of cognitive sciences without a definite resolution, range of language ambiguity differs greatly based on the speaker. Technically, any language sentence with plenty grammar can generate another meaning, for human to find it challenging in dealing with conversation vagueness sometimes, then it is inevitable for natural language understanding systems.

  1. TYPES OF AMBIGUITY

Outlining ambiguity can sometimes seems vague. There are different forms of ambiguity regarding natural language processing (NLP), and artificial intelligence (AI) systems.

  1. Lexical Ambiguity: This is a single word ambiguity. A word can be ambiguous with respect to its syntactic category. Lexical ambiguity can be decided by Lexical type clarification like parts-of-speech labeling. It also stores word and complementary knowledge.
  2. Syntax: This is a part of grammar that define how words are assembled and linked with one another to make a sentence. Syntax involves the transformation of a linear order of tokens (a key to each word or punctuation mark in natural language) into a classified syntax tree. The main issue with syntax level are: sentence assembling, speech tagging, and identifying syntactic categories.
  • Semantics: This type of ambiguity is characteristically associated with sentence interpretation. It includes task like interpreting one natural language to another, synonyms searching, creating question-answering systems, and clarification of word sense.
  1. Morphology Ambiguity: This ambiguity came into being due to advance processing carried out on the root words to make use of them in a specific sentence. It involves processing of word forms.
  2. Discourse: Discourse level processing needs a pooled knowledge and the interpretation is carried out using this context. Anaphoric ambiguity comes under discourse level. One of the exhausting task in Natural Language Processing (NLP), some of the problem are belief, sentiment, and user intention processing. It also process connected text.
  3. Pragmatic Ambiguity: This is refer to the situation whereby whereby the circumstance of a phrase gives it multiple meaning. It involves user modelling, and intention processing.
  • Referential Ambiguity: When a phrase or a word in a particular sentence could refer to two or more properties or things, it is referential ambiguity. It is always clear from the circumstance which meaning is intended but not always.
  • Phonology: It is described as words that sound the same way but have different meaning. This type of ambiguity forces the NLP model to interpret the context of the sentence and place it in the right context. It can be referred to processing of sound.
  •  

STAGES IN NATURAL LANGUAGE PROCESSING (NLP)

Basic steps necessary to be followed to build Natural Language Processing (NLP) model are as follows:

Stage 1: Segmentation of Sentence

The first stage required to build NLP model is breaking of prearranged paragraph into single sentences. This is done to process the meaning line by line.

Stage 2: Word Tokenization

After sentence segmentation, it is followed by word extraction from each sentence one after the other. The tokenization algorithm can be programmed to identify a word whenever a ‘space’ is observed. All these would be achieved following Asian natural language.

  • Stage 3: Prediction of Parts of Speech

It involves classifying words into their respective part of speech as duly represented in Asian language. Parts of speech classification will help the machine learning model to comprehend its role in sentence. Machine learning might not actually know the meaning of each word in sentence setting the way human being do. A lot of data has to be fed into the model along with precise label of each word’s meaning and part of speech.

  1. Stage 4: Text Lemmatization

The machine learning model learns to identify the most basic form of words in a sentence. By differentiating between closely related words.

Stage 5: Pinpointing Stop Words

This stage is saddled with identifying the importance of each word in a sentence. There are a lot of filter words in that appear frequently in English language, and it is definite that Asia Language will also have some commonly used filter words that introduces a lot of noise into a sentence. It is necessary for machine learning to identify them and flag them as stop words i.e. words that can be filtered out before undertaking statistical investigation.

Stage 6: Dependency Parsing

It is the stage where grammatical laws of Asian language would be employed to identify how words are related to one another

Stage 7: Entity Analysis

This is achieved by going through the entire sentence in Asian Language and identify all the important words in the text. And the words in the sentence will be categorized as been programmed to work.

Stage 8: Pronouns Parsing

This is the last stage in building NLP model and it is one of the hardest stage. This stage will employ machine learning to keep track of pronouns with respect to the sentence context. It is very easy for human to comprehend the meaning right from the context of the sentence unlike computers. Therefore, a Machine Learning model is required to be fed with a lot of data alongside correct tags for the model to be able to identify the pronouns effect in a sentence.


17
Nov
Talkbot Basics  ·  Voice AI Technology
The Rise Of Conversational AI In Customer Service
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

THE RISE OF ARTIFICIAL INTELLIGENCE IN ASIA AND THE WORLD

First coined by American computer scientist John McCarthy in 1956, artificial intelligence (AI) refers to the cognizant abilities of machines which have been programmed to autonomously perform, think and learn like a human. Today, from unassuming home appliances such as robotic vacuums, to more awe-inspiring projects such as autonomous cars and self-learning weather forecast technologies, AI has permeated into various aspects of industry and society. As its applications become increasingly adapted into various aspects of our lives, its ability to bring about the digital transformation of the world would pose various disruptive implications for the economy, environment and our day-to-day lifestyles.

Arguably, the main attraction or headliner of AI, as it has captured the attention of the commercial world, is its potential to drastically increase productive and cost efficiencies. It’s transformative effects have been echoed by various industry experts, who have projected that such technologies would boost corporate profitability in 16 industries across 12 economies by an average of 38% by the year 2035[1]. By eliminating repetitive, low level tasks which were traditionally performed by humans, one of AI’s most noticeable disruption would definitely be on the labor market, as companies look into using AI to optimise internal operational process and alter the way service and products were originally offered to their customers. The nature of long-established roles are also likely to evolve in the meantime.

Global investment in AI is growing rapidly, with an estimated investment of $26 to $39B investment in AI. At present, the two major global hubs of AI development are the United States and China. Funding for artificial intelligence companies in the United States has increased exponentially in recent years, growing from around 300 million U.S. dollars in 2011 to around 16.5 billion in 2019[2]. For China, PricewaterhouseCoopers predicts that $7 trillion of China’s $38 trillion GDP by 2030 would be attributed to AI through new business creation in fields such as autonomous driving and precision medicine, as well as existing business upgrades in terms of improved efficiencies and reduced costs[3].

While the bulk of AI investments are presently made by tech giants Alibaba, Amazon, Google, Baidu and Facebook in a race towards AI as a long-term strategy for business sustainability and competitiveness, AI as a concept is still poorly understood and intimidating to the ASEAN region. However, despite the region’s relatively slow advances in AI technologies, its oncoming impact is undeniable. Previously published MGI research estimated that currently demonstrated technologies have the potential to automate roughly half of the work activities performed in ASEAN’s four biggest economies: Indonesia (52 percent of all activities), Malaysia (51 percent), the Philippines (48 percent) and Thailand (55 percent), with these tasks currently generating more than $900 billion in wages[4].

Out of the ASEAN member states, Singapore, as the region’s technology capital, has made the greatest AI advances thus far, and is a natural first choice for AI tech startups to establish their presence in Asia. WIZ.AI, having its research institute based in Nanjing, China, established its first overseas headquarters in Singapore in 2019, from whence it aims to continue developing its pioneering and proprietary conversational AI talkbot technologies and push it out to ASEAN. 

 

CONVENTIONAL CHATBOTS VERSUS AI CONVERSATIONAL TALKBOTS

2.1 THE RISE OF CHATBOTS IN CUSTOMER SERVICE

Chatbots are computer programs built on the concept of artificial and data analytics, and is commonly installed on websites or social media platforms. With a chatbot application,  companies are able to automatically respond to customer messages round the clock, through a virtual assistant which recognises entered keywords and is able to provide instantaneous, standardised text replies and guidance to the customer.

 

This rise of chatbots is projected to be significant; as reported by Global Market Insights, the chatbot market will be worth $1.34 billion by 2024, with 42.52% of that alone from the customer service sector[5]. The rise of chatbots is tightly linked to new technological advancements and evolving customers’ expectation of brand interactions. With the prevalence of social media and mobile messaging applications, the average consumer now expects a company’s to resolve issues and respond to requests with speed.  Based on a 2017 customer survey conducted by Microsoft, 54% of those polled expressed higher expectations for customer service today compared to the previous year, with the percentage increasing to 66% for younger respondents at the 18 – 34 age group[6]. Falling back on traditional forms of communication such as emails or text messages are no longer acceptable; in the same survey, 68% of the respondents have a more positive view of brands which take the initiative in providing proactive customer service notifications.

 

In addition to it being used as a medium to provide basic customer service, chatbots are also suitable for use in marketing & sales of products, which further spurs demand and market growth in this sector. These platforms aid companies to expand their reach by connecting with a larger audience, aiding in decision making by addressing customer queries on the spot and subsequently pushing suitable product recommendations.

 

2.2      WIZ’S AI CONVERSATIONAL TALKBOT – ONE STEP UP FROM CHATBOTS

In the 2017 Global State of Customer Service Report by Microsoft, email and telephone are still the primary communication channels for many customers, while live chat, self-service, social media, and chatbots are relatively lower in terms of raw volume[7].

 

It would seem then that maintaining a hotline available for urgent customer queries 24/7 is key to keeping customers happy and loyal. Despite the increasing number of self-service options made possible by technology, customers still express a preference for live-agent support, with 30% of global respondents frustrated when they are not able to do so. The value of being reachable to customers is further demonstrated when 30% of people polled are of the opinion that being able to speaking with a knowledgeable and friendly agent is a significant factor that makes or break a customer service experience.

 

Working from the same belief that voice conversations are still the most natural way of interaction for humans, and that artificial intelligence is key in the next wave of hyper-personalized customer engagement, WIZ.AI combines the best of both worlds, integrating its intuitive AI conversation capabilities into the simplicity and familiarity of a phone call. Pioneering a new market category, its AI Conversational Talkbots takes centre stage as a cutting-edge, turnkey customer service solution.

 

Capable of understanding human speech in a variety of accents, expressing empathy and engaging in unlimited multi-round conversations with the customer, WIZ’s AI Conversational Talkbots provide a more interactive, human-like and fulfilling customer service experience that is superior to text-based chatbots. Compared to human agents, its Talkbots are also more consistent and reliable. Offered at the fraction of the costs of maintaining a human call centre, WIZ’s AI Conversational Talkbot allows any corporations with heavy customer communication needs to maintain its personal touch with its customers in a cost-effective manner, with endless scaling possibilities for both new inbound and outbound call campaigns. Its backend CRM system captures and sorts through customer intentions in real-time, collecting and digitalising valuable customer intention data.

 

WIZ.AI’s proprietary AI talkbots have been adapted for mass commercial applications in the banking, telecommunications, health care and e-commerce industries. Besides Singapore, WIZ.AI also operates offices in China, Jakarta and the Philippines with a team of scientists, developers, linguists, and dialogue designers.

 

  1. AI – BRINGING CONVERSATIONAL AI INTO THE MAINSTREAM

3.1      COMPONENTS OF WIZ’S AI CONVERSATIONAL TALKBOTS

WIZ.AI’s proprietary AI talkbots can be broadly broken down into three main elements:

  • Natural Language Processing & Understanding: Recognises and processes speech patterns and nuances through the responses of the speaker, allowing the talkbot to understand the intent of the speaker.
  • Automatic Speech Recognition: Recognises and understands local accents and lingo
  • Text to Speech: AI voice tailored to sound human and speak with local accents

 

3.1.1   NATURAL PROCESSING LANGUAGE

Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence, employing the computer in comprehending and handling speech and text of natural language. There are several fields NLP can be applied to; speech recognition, expert systems, artificial intelligence, cross language information retrieval (CLIR), text processing, language translation, speech recognition, and user interfaces.

In other to capture the whole process, NLP needs to include several diverse procedures for interpreting Asia’s local languages. It could involve machine learning, statistical, algorithmic, or rules-based approaches. The steps to to build a Natural Language Processing (NLP) model are as follows:

  1. Stage 1: Segmentation of Sentence

The first stage required to build an NLP model is the breaking of prearranged paragraph into single sentences. This is done to process the meaning line by line.

  1. Stage 2: Word Tokenization

After sentence segmentation, it is followed by word extraction from each sentence one after the other. The tokenization algorithm can be programmed to identify a word whenever a ‘space’ is observed. All these would be achieved following Asian natural language.

  • Stage 3: Prediction of Parts of Speech

It involves classifying words into their respective part of speech as duly represented in Asian language. Parts of speech classification will help the machine learning model to comprehend its role in the sentence. Machine learning might not actually know the meaning of each word in sentence setting the way human being do. A lot of data has to be fed into the model along with precise label of each word’s meaning and part of speech.

  1. Stage 4: Text Lemmatization

The machine learning model learns to identify the most basic form of words in a sentence by differentiating between closely related words.

  1. Stage 5: Pinpointing Stop Words

This stage is saddled with identifying the importance of each word in a sentence. Similar to the English language, Asia Languages also contains many commonly used filter words that introduce noise to a sentence. It is necessary for machine learning to identify them and flag them as stop words i.e. words that can be filtered out before undertaking statistical investigation.

  1. Stage 6: Dependency Parsing

It is the stage where grammatical laws of Asian language would be employed to identify how words are related to one another.

  • Stage 7: Entity Analysis

This is achieved by going through the entire sentence in Asian Language and identifying all the important words in the text.

  • Stage 8: Pronouns Parsing

The last and most challenging stage of building a NLP model, this step employs machine learning to keep track of pronouns with respect to the sentence context, allowing the bot to comprehend the meaning right from the context of the sentence. To achieve this, the Machine Learning model has to be fed with a lot of data alongside correct tags for the model to be able to identify the pronouns effect in a sentence.

3.1.2 AUTOMATIC SPEECH RECOGNITION (ASR)

This is where a chatbot is differentiated from a AI conversational talkbot – the latter has the added challenge of first having to understand the different accents and local lingo in order to recognise the customer’s intention. ASR training involves collecting speech samples from a variety of language backgrounds, and through machine learning over time, the talkbot gets more adept at deciphering the local accents and lingo.

3.1.3   TEXT-TO-SPEECH (TTS)

Text-to-Speech (TTS) is the channel whereby the talkbot responds and converse with the customer in real-time. WIZ.AI’s proprietary TTS generation system has been designed to be life-like, encouraging customers to share more, and allowing companies to gain deeper insights into customer intentions and needs.

With customisable voices, the customer call experience is further enhanced with a quality TTS which matches the brand persona. The use of a single distinguishing voice sets your company apart from competitors and also ensures brand consistency across all different customer touchpoints.

  1. LOOKING FORWARD

A disruptive technology, AI is transforming the face of customer service and forcing companies to relook into their customer touchpoints and service strategy in order to retain customer loyalty, business sustainability and competitiveness in the long run. Conversational AI technologies are likely to lead this evolution, and as the talkbot product gets better understood and commercialised, we expect more companies in Asia to adopt this product, changing the landscape of ASEAN customer service and economies permanently. 

[1] Accenture, How AI boosts industry profits and innovation, June 21, 2017

[2] Shanhong Liu, Artificial Intelligence funding United States 2011-2019, June 6, 2020 https://www.statista.com/statistics/672712/ai-funding-united-states/ 

[3] PwC Global, Sizing the Price – PwC’s Global Artificial Intelligence Study – Exploiting the AI Revolution, June 2017. https://www.pwc.com/gx/en/issues/data-andanalytics/publications/artificial-intelligence-study.html

[4] Mckinsey Global Institute, Artificial Intelligence and Southeast Asia’s Future, 2017 https://www.mckinsey.com/~/media/mckinsey/featured%20insights/artificial%20intelligence/ai%20and%20se%20asia%20future/artificial-intelligence-and-southeast-asias-future.ashx

[5] Global Market Insights,  Global Chatbot Market worth over $1.34bn by 2024, August 26, 2019 https://www.gminsights.com/pressrelease/chatbot-market

[6] Microsoft, State of Global Customer Service Report, 2017 https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-Report-DynService-2017-global-state-customer-service.pdf

[7] Microsoft, State of Global Customer Service Report, 2017 https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-Report-DynService-2017-global-state-customer-service.pdf


17
Nov
Talkbot Basics  ·  Voice AI Technology
The Changing Landscape Of Customer Service
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

To date, customer service is widely known as being the top-most business priority with a sure link between customer satisfaction, as well as retention, and profitability. Recently, the Aberdeen group statistically reported that organizations that achieved a height of over 90% customer satisfaction rate reached an annual service growth of 6.1%, and overall revenue growth of 3.7%, and also 89% customer retention level. With approximately 78% of the UK GDP gotten from the service sector, customer service is becoming hugely seen as a strategic plan and, as stated by customer service institute, Organizations/businesses that do not add it in their boardroom meetings and discussions won’t last for a very long term.

Now, for businesses and organizations across all industries and niches, It has been proven that artificial intelligence (AI) is seen as a perfect solution for efficiency improvements, the efficacy of customer experience, and a lot more. Starting from startups to large multinational corporations, AI otherwise known as artificial intelligence has the power to transform specific aspects of businesses. Most times, we have heard about how AI can help a business to become hugely efficient with its resources. Other than this, AI also has tremendous value for customer experience, and should be introduced by brands/companies if being the best is the upmost priority of that brand/company.

Why Introduce AI into Customer Experience?

What do you understand by the statement ‘customer experience’? Most times, people mislabel it as a ‘customer service’ but this is just one aspect of the idea. Customer service is a specific area of customer experience (sometimes referred to as CX); I will be throwing more light on how to actually boost customer service with AI marketing soon. However, customer experience (CX) actually covers the entire customer journey. Right from the point of contact with the brand to the moment they get to see your product, this is regarded as a customer journey. When an organization gets customer feedback, it usually covers every stage rather than the customer service section only.

How AI Supports Marketing & Sales in Understanding the Customer Journey

The marketing and sales tools strengthened by Artificial Intelligence (AI) isn’t something to be scared of, rather it’s something we should embrace. The reason because Unlike usual human customer service, the AI technology can boost a better understanding of a company and its customers, as well as the journey of individual buyer customers before making a purchase.

Research on Google proves that 53% of visitors will leave if a mobile page takes more than three seconds to load. When customers interact with your marketing, they won’t have the patience to wait around till they get a response from you. A quick response is vital when talking about customer experience.

If you are unable to respond immediately when B2B buyers make inquiries about your product or service, there’s every tendency that you will miss that opportunity. So what do you do in other not to miss out on closing opportunities? Well, it’s all about bringing AI to the frontline.

For instance, if you work for a university or an educational institution, and someone requests information directly from your website through a lead gen suite, or at a recruiting event, your AI assistant can help you interact conversationally with the use of the email or a chatbot on your website. Then log pieces of information gotten into its system for proper analysis, Thereby serving as an all in one team; a sales team, a marketing team, and an assistant team.

The AI assistant can also answer questions, handle objections, as well as respond to requests. Immediately the connection is made, you can guide customers through the tunnel with the help of automation to intelligently nurture your lead with personalized follow-ups.

It directs conversation as it engages, until the lead becomes qualified (based on parameters) then hands the lead to the right person on your team.

The artificial intelligence (AI) is seen as a set of algorithms that informs a machine on what to do and what to learn. These algorithms assist marketing sales professionals by reducing time on important repetitive tasks such as analyzing data, locating opportunities in content, monitoring social posts and so many more.

With this, it means a better improvement in marketing and sales jobs. And it means a more personalized and great customer experiences.

Below, I have explained how artificial intelligence or machine learning can be utilized during the four stages of the customer journey — attract, engage, win, and support and delight. Stage 1: Using Machine Learning to Attract the Right Audience

In the recent digital world, one of the key ways to succeed is to get found. This may sound simple, but in the real sense, it isn’t as easy as it sounds. It is mostly easy for a brand to get lost in the noise of the online world today.  Check out these 2019 statistics:

  • There are 1.94 billion websites on the internet.
  • 388 billion People using the internet.
  • There 3.484 billion people using social media.
  • And 90 percent of brands are on social media

This proves that a brand needs to distribute, as well as promote the right content at the right time, in other to be outstanding in the eyes of its target audience.

How can AI be of help in supporting this? No. 1 — Buyer personas. Artificial Intelligence can help collect data about your target audience, and in turn, allows you to create precise buyer personas. The more you know about your ideal consumer, the easier it is for you to sell your products and service.

Having a concrete buyer persona, marketing gets a vivid understanding of your interests, prospects, spending motives, buying habits and obstacles, as well as frequent questions.

With this, you can create a personalized social media campaigns and contents for your platform or website that appears in search engines and gets the attention of the audience your company seeks,

Another reason for the existence of AI technology is to support social media monitoring. Because social media moves so swiftly, so it’s quite easy to Miss Key opportunities. Making use of AI monitoring can help a company to identify thought influencers, stay firmly on top of brand mentions, see all customers’ feedback and sentiments, and also identify phrases or topics that are trending.

Stage 2: Engaging Your Buyers with Optimal Efficiency

Haven successfully generates traffic to your website and social media channels, now, how do you engage with these potential buyers? AI technology can assist you in efficiently creating more personalized experiences.

See these statistics from the 2018 salesforce’s state of Marketing: 52% of customers would probably want to change the brand if the company doesn’t give personalized communication. The method of sending out generic mass emails to the purchased list is no more valid in today’s world.

Platforms that are AI-enabled can analyze behavioral patterns from a list of inputs that will probably take your team years to capture, organize, and understand manually.

Having this data, your market team can start to segment your audience and also create personalized content based on different factors such as demographics, interests, level of engagement, and behaviors of your customers.

The artificial intelligence system can also assist your team to see when, and how frequently they should distribute content via social channels, emails, and websites for maximum impact and stop wasting time on content that that has no value to customers.

Stage 3: No More Cold-Calling; Let AI Lead Sales to Top Prospects

With the aid of machine learning, team sales can now receive notifications when a lead moves from cold-to warm-to hot — all before sales have even reached out. Good-bye, cold-calling for both sales and the customer!

Using AI, a system a can receive the behaviors of potential customers and score them based on things like the social media post they saw, the website pages they visited, the emails they opened, how long they were on a website, the number of times they came back to the site, and lot more. The machine helps to predict when a lead will become hot so your sales team will be informed on when and when not to reach out.

With the aid AI-powered data, sales can work at a higher rate much more efficiently.

Stage 4: Delight Customers so they keep visiting

You can improve customers’ loyalty by offering them what they want, and when they need it. Artificial intelligence technology can collect data to assist your team in creating personalized customer experiences even after purchase. This could be in incentives form, related products for upsells, or content that supports the product or service purchased by customers.

Good examples of AI technology in place in the delight and retention stage of the buyer’s journey are Amazon, Netflix, and Spotify. Amazon provides “other products you might be interested in”, while Netflix and Spotify both select and recommend movies or music based on your interests and previous interactions.

With the aid of AI technology, the above-mentioned companies have been able to keep their customers satisfied and loyal.

A lot of companies are also putting AI-powered chatbots in place to assist customer service. Instead of calling a company for product support, you can easily visit the website, type in what you are searching for and a chatbot will instantly provide you the answer.

There are a lot of things a brand may not do well, from a rather complicated on boarding when customers are not offered easy-to-understand information about product usage as well as its capabilities to poor communication, an example is lack of feedback or delayed answered to queries or pondering questions. Another point: Long-serving clients may feel they are less appreciated because they don’t get as many bonuses as new ones.

Bad experiences may alienate even loyal customers. Source: PwC

Generally, it is the all-round customer experience that defines brand perception and influences the way customers recognize the value of the money of the product and service they make use of.

It is ideal for a business or brand to know that even loyal customers will not tolerate a brand if they’ve had one or numerous issues. For example, according to pricehousewaterhouseCoopers (PWC), 59% of the US respondent surveyed by them noted that they will say goodbye to a brand after several bad experiences, while 17% of them say they will say goodbye after just one bad experience.

In other to eliminate the idea of prospect customers having a bad experience with your brand/company, there are things AI assistance can help you with, to make sure customers do not have to wait for a long time before they are attended to.

Collections/Payments

You can make use of a VoiceBot when you are having several pending payments. You can reach out to your customers with the aid of your AI assistant and inform them about bill dues that are already overdue or upcoming payments. Schedule as many calls as you need and monitor your payments; when necessary, have an account executive step in.

Surveys and Customer Reviews

You can also make use of your VoiceBot for surveys as well as customer review calls; this will help you to know the customer’s thought on your products or service, as well as the overall rating of your product or service.

Custom Branded Messages

With the use of Ai assistance, you can spread the word! You can reach your prospects with custom messages using different VoiceBots. You can send messages to maybe recommend similar products, send thank you messages or promotion messages.

Customer Support

A VoiceBot can help provide basic customer service and support to your clients. The Bot can swiftly take care of your all customer’s inquiries and provide way simple solutions.

Promote a new product

Are you launching a new version of your product and looking for a means to get the word out? Well, you can easily build a simple Workflow/sequence that includes an email/call combo, and the VoiceBot can take over by helping you carry out a simple and straightforward call that will allow you to warm your leads and start qualifying them.

Event invitation/promotion

Drive more engagement and attendance to your events with the aid of an AI assistant. You can give more information to your leads about the event, venue and also track RSVPs with a simple call, the Bot will give you reports of all live call.

The reality is that artificial intelligence has greatly affected every stage of the customers’ journey; right from prospects finding your company, to potential customers engaging with your product or service down to gaining loyal customers.

If you wish to stay on top as a brand or business, now is the ideal time to leverage AI within your sales and marketing teams

 


17
Nov
Talkbot Basics  ·  Voice AI Technology
Employing AI To Attract, Engage And Delight Your Customers
Jennifer Zhang

Jennifer Zhang

CEO & Co-Founder

In the world of business, there are two key priorities; to maintain a healthy equilibrium between time and money, and to ensure customer satisfaction. AI has already transformed modern living, with presence everywhere we turn – from home to phone, from car to self-service checkout. In the context of business, there is a particular strain of AI technology that serves to both enhance the customer experience while ensuring a harmonious balance of time and money. That is in the form of AI and AI voice-driven chatbots.

 

Chatbots respond to humans like humans through adaptive machine learning technology. AI voice-driven chatbots have come a long way since humble beginnings in 1966, with the affectionately named ELIZA who had the technological prowess to answer a whole three questions. AI technology has developed and evolved, and chatbots have become as familiar to us as air in 2020. One of the greatest functions of AI voice chatbots is in the realm of customer service.

 

So, why should a company employ AI technology to attract, engage and delight its customers? In this article, we will examine the benefits of implementing such technology to accomplish both customer satisfaction and business KPIs.

AI Voice Enhances The Customer Experience

Through harnessing machine learning, AI voice technology is advancing at an incredible velocity. AI voice technology is readily available. It has the ability to troubleshoot, multitask and provide a warm customer experience at the drop of a hat, making it an obvious solution to round-the-clock customer service. Chatbots are accessible at every touchpoint of the customer journey, and the tailored response is shaped by the comprehensive customer profile produced by machine learning.

 

AI voice systems are a fantastic facilitator to traditional call centres. From the first point of customer contact, AI will identify the needs and respond by either directing them to the appropriate person/department, or leading through a series of questions to answer autonomously. AI voice has the capacity to take the load off humans at busy periods (and with COVID testing all manners of customer service, this couldn’t be a more current requirement) while taking up no physical space. The streamlined nature of this modern process is a massive benefit to effective customer service for being straightforward and adaptive. 

Machine Learning Chatbots Cut Processing Time

Each manufacturing brand producing AI technology boasts an edge to process certain business requirements (ours, for example, is the ability to understand different Asian languages and their local dialects). The ever-evolving capabilities of machine learning offer AI technology the means to identify, process, and respond to greater business demands while also reacting to customer requests simultaneously.

 

Primarily, AI has the ability to aggregate data from multiple sources to generate a tailored response in real-time. This is critical both for condensing the time to process data and demands, but also for improving the net promoter score – the system where a brand or company is measured against customer loyalty. If a customer is satisfied with the processing time of the service they receive when contacting a company, they are likely to remain loyal.  

 

AI technology also works to the benefit of the customer’s processing time. Through machine learning, AI tailors an experience of a product or service to the interests of the user; for example, ‘suggestions for you’ on Netflix, or a personalised playlist on Spotify. Such measures take away the time to ‘think’ (or process) what to watch or what to listen to. Therefore, AI provides time-efficiency for the customer while ensuring the brand is providing autonomous top-quality service.

Implementing AI To Deliver Personalised Customer Service

AI has the ability to aggregate data to deliver a comprehensive personalised service that takes all available information about a customer into account – from language to local weather, from buying behaviours to social media interactions. AI formulates a customer profile while synchronously producing bespoke content specific to the user needs (for example, tailored suggestions on Amazon in response to your search for an umbrella as the weather turns sour in September). Such a response enhances customer satisfaction for recognition of immediate needs at the exact moment it is required.

 

In the context of AI voice chatbots, the level of customer satisfaction is enhanced by the bots’ ability to build an intuitive profile on the customer when a conversation is initiated (using data such as account information, past purchases, and geographical location). Chatbots are then able to manipulate the service so that it is personalised and aligned to the customer profile. Chatbots are able to build a conversation centred specifically on the customer’s requirements in a way that is totally relevant and organic according to the immediate needs. 

Using AI To Attract, Engage And Delight Your Customers

Customer satisfaction and customer loyalty are crucial elements when it comes to a successful business – and this can be difficult to accomplish with limited resources. However, machine learning AI technology makes the process of understanding and responding to customers with a level of care and quality both accessible and cost-effective. The tailored experience for the customer not only increases their level of satisfaction but also enhances productivity. Less time is spent directing them to the right area of business, their questions are answered almost entirely autonomously. Service is slick and consistent, personalised and specific, and enough to attract, engage and delight each and every customer.




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