Amdocs’ AI-powered Smartbot is making customer service in comms & media much more personalised

    Amdocs debuts first bot designed and pre-integrated for the communications and media industries

    Communications software giant Amdocs recently launched their Smartbot, a machine learning-based bot that enables digital service providers to provide customer care, sales and marketing engagements and deliver highly personalized, self-service interactions with customers that are simple, quick and helpful.

     Roni Dvir, Product Marketing Manager, Amdocs Digital Intelligence answers our questions about the Smartbot below.

    What is the Amdocs Smartbot?

    Amdocs SmartBot is the first bot that is intelligence-driven, pre-integrated with back-end, mission-critical systems and uniquely designed for the communication and media industry. These capabilities enable digital service providers (DSPs) to transform self-service engagements by making them highly personalized and contextual, as well as simple, efficient and effective.

    Amdocs SmartBot leverages best-of-breed artificial intelligence (AI) and natural language processing (NLP) capabilities to engage customers in intuitive, personalized, contextual and intelligent conversations. Infused with 35 years of Amdocs domain expertise and pre-trained on business processes and telecom-specific intents, it provides intelligence-enabled bot-to-human customer experiences to meet consumers’ precise and immediate needs.

    Amdocs SmartBot leverages aia, Amdocs’ intelligence platform, to inject intelligence into every customer engagement, including next best offer/action (NBO/NBA) offers based on the customer profile, past behaviors, current context, all in alignment with the organization’s marketing and customer care objectives. It understands context to execute transactions on behalf of users and expedites resolution through proactive service.

    The integration with aia is a major industry differentiator as it boosts Amdocs SmartBot’s predictive capabilities and enables it to proactively deliver personalized engagements as the customer’s context changes throughout their journey.

    • Channel agnostic– Amdocs SmartBot helps digital service providers transform their customer experience on mobile, web and on social messaging platforms. This omni-channel experience includes text channels such as Facebook Messenger, Kik, Skype, Slack, SMS, Telegram and Twitter as well as voice assistant channels like IVR and Amazon Alexa.  Amdocs SmartBot also has the capability to seamlessly shift the bot interaction to a human agent in the digital service provider’s support center when needed.
    • Deeply integrated with a digital service provider’s core information systems such as CRM, order management and catalog, Amdocs SmartBot has a 360-degree view of the customer and the context of the interaction, which enables digital service providers to provide their customers with an end-to-end experience, with the potential to grow care-to-commerce revenue opportunities by making more relevant predictive care and promotional offers to customers.

    How does it help media and entertainment companies increase customer satisfaction and drive customer experience?

    The trend towards using chatbots as the medium of choice for customer engagements is well underway. Still, the most widespread ones in use today are those that answer only simple questions, such as basic product, price or bill information and high-level support requests. These are “rule-based” chatbots, which are programmed to understand predefined commands that are specific to the processes related to the request at hand. Ironically, while adequately functional, such chatbots can ultimately wind up having the opposite effect to that which both the consumer and the service provider seek: once a conversation veers slightly from predefined scripts, things can get complicated – since the chatbot is ill-equipped to handle dynamic dialogues.

    Amdocs' AI-powered Smartbot is making customer service in comms & media much more personalised TechNative

    Service providers who want to add chatbots to their customer engagement arsenal will want them to have capabilities that live up to their customer experience promise. To achieve this, they will need to overcome a number of strategic challenges:

    • Overcome the chasm that exists between virtual and live agents: When the typical, functional type of chatbot arrives at an impasse and doesn’t “know” how to answer a certain question or provide relevant information, the customer experience is placed at risk. To be effective, chatbots need to (a) be able to handle many more types of content that traditionally, only live agents handle; and (b) be seamlessly integrated with live agent channels, with smooth handoff that is transparent to the customer.
    • Ensure chatbots don’t miss out on care-to-commerce opportunities: Service providers who leverage chatbots for simple support information-driven interactions will miss out on unique revenue- generating opportunities. However, if a chatbot can “know” what a customer likes, needs and wants – and make relevant and timely marketing offers accordingly, this would significantly impact the top line.
    • Ensure the chatbot “understands” telecom-specific intents: Even if the chatbot can learn from every customer interaction and converse in a more human way, if it lacks industry domain knowledge, it will still lack the capability to accurately understand what the customer wants and needs.
    • Integrate the chatbot with mission- critical business systems: A chatbot that is not integrated with systems such as billing, order management, CRM and so on, will not have access to a full 360-degree profile of the customer. Without knowing what was purchased in the past or historical and current usage patterns and status, for example, they will not be able to provide relevant information and support, or predict what the customer may need next.
    • Meet digital consumers’ expectations for personalized conversations: The simple engagements currently prevalent with chatbots do not satisfy digital consumers’ needs for personalized and contextual conversations: they do not address their specific needs, their unique journey with the brand or the types of support best suited to them.
    • Ensure the bot learns from every engagement: Forthcoming customer interactions and experiences must be finely attuned to each individual customer, and delivered with great accuracy.

    What are the benefits to digital service providers in terms of its ability to match up to their back office systems and infrastructure?

    Pre-Integration with back-end/mission critical systems provides a single source of truth for customer data, product and promotions and order management, which is critical for ensuring consistent and personalized experiences. Amdocs SmartBot is flexible – working with both Amdocs and non-Amdocs BSS back-end systems.

    Systems of record (e.g. billing and CRM systems) are updated with every chatbot interaction to support subsequent human assisted interactions. Also, root-cause analysis of customer interactions are used to improve customer experiences:

    • Specifically, this means analyzing customer interactions in order to uncover the drivers behind increased spend, positive sentiment, and referrals.
    • Machine learning is helping the chatbot to learn which activities are most likely to improve first contact resolution rates, average handle times, and customer satisfaction.
    • Combined with artificial intelligence, Amdocs SmartBot can use this learning to tailor each new customer interaction and achieve desired objectives.

    Amdocs SmartBot has a 360-degree view of the customer and the context of the interaction, which enables digital service providers to provide their customers with an end-to-end experience, with the potential to grow care-to-commerce revenue opportunities by making more relevant predictive care and promotional offers to customers.

    Why was Microsoft such a key component in bringing the platform to market?

    Cognitive Services

     Amdocs has partnered with Microsoft Luis, a leading NLP solution provider, as the core NLP engine on top of which the CSP specific intents and the bot application are built.

    The NLP engine is responsible for providing the conversational capability for the bot to understand the customer. In order to provide such information to the bot, the NLP engine will:

      • Discover Intent: Using a set of defined Telco intents and examples the NLP algorithms will return a list of possible customer intents with accuracy ranking. When receiving this list the bot Application will turn to the intent with the highest score if it exceeds a certain threshold.
        • Telco Intents: Once the NLP engine identifies the phrase and the utterances by the customer (whether via text or voice), it is essential to associate it to a Telco-specific intent. For example, when a customer says, “I have lost my device”, defining an intent for lost device and associating the intent to the dialog of “suspend customer services” is a key function of the bot. The ability to do this is accomplished by extending the horizontal NLP capabilities with industry domain and knowledge. Amdocs delivers out of the box intents, which can be further extended and added based on specific service provider requirements. The intents are built such that they can either be consumed by a bot application or by any other incoming form of customer interaction.
      • Extract Entity: The NLP is capable of identifying certain parts of the customer sentences as entities. The entities are isolated and sent to the bot Application in the context of the identified intent. The bot will use the entities as attributes that are needed to execute the dialog. Example of simple entities are: name, date, country etc. So if customer is flying to a trip the destination and dates will serve the bot in the roaming plan activation flow.

    With deep understanding of the CSP world, Amdocs defines a variety of specialized entities: device, plan, bundle and more. Utilizing the different entity types in the NLP service we define groups and hierarchies to provide deeper understanding per each entity.

    For example: when defining an entity of ‘device’ we can know that Samsung S8 is a device – for some intents this information is enough (e.g. intent: ‘need help with network definitions’, entity: device = Samsung S8), but we can also create groups of device types by category and include Samsung S8 in the entity of ‘top tier devices’ and apply different dialog approach when getting sales inquiry for a device of this group. So it’s all about knowing the industry and utilizing the tools based on this knowledge.

      • Determine Sentiment: Per shared customer sentence the NLP service returns a score for customer sentiment. The bot framework can use the sentiment score for decision points and to share it with other systems.
      • Detect language: Per shared customer sentence the NLP service returns the detected language that can be used in a multilingual implementation.

    Are there new revenue opportunities for service providers?

    With the Amdocs SmartBot, service providers can grow revenue by automatically and intelligently identifying upsell / cross-sell opportunities and providing relevant and personalized offers.

    Deeply integrated with a digital service provider’s core information systems such as CRM, order management and catalog, Amdocs SmartBot has a 360-degree view of the customer and the context of the interaction, which enables digital service providers to provide their customers with an end-to-end experience, with the potential to grow care-to-commerce revenue opportunities by making more relevant predictive care and promotional offers to customers.

    Tags : AmdocsMWC
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