Consumers primarily use Twitter as a review channel. It’s the place where they can bash a brand for a poor experience, or praise their newest product – either way the hope is that here their voices will be heard. But Twitter wants to move beyond being simply a soundboard and implement new technologies to become more customer-service friendly for brands and their customers.
Earlier this month, Twitter released new personalisation features, allowing customers to share their locations when interacting with branded chatbots through Twitter’s Direct Message service. This empowers brands to offer more tailored social customer service, equipping virtual agents on Twitter with the ability to offer suggestions on nearby storefronts or details regarding their local service area. Customisation is necessary for customer service today because it allows a brand to offer proactive support that is directly relevant to each individual customer. However, this is just one component of a much bigger initiative Twitter will need to invest in to drive brands to use the Direct Message platform as an additional customer service channel.
With recent data from Aspect Software Research showing nearly half (44 per cent) of online consumers prefer to use customer service chatbots if the experience is right, Twitter needs to examine which technological features will make it a valuable platform for both brands and users. This means improving some of the core capabilities that are crucial to an effective virtual assistant, incorporating smart technologies that don’t only offer quick, accurate customer support, but also drive insightful interactions.
Driving contextual, seamless conversations with AI and NLP
With innovative artificial intelligence (AI) and natural-language processing (NLP), virtual customer assistants are equipped with the ability to drive contextual conversations with customers. If Twitter wants to be an effective self-service platform, it will need to replicate these features, allowing seamless interactions between brands and their customers. Smart chatbots enable customers to freely express themselves and ask a question in any way that feels natural to them. NLP helps decipher and understand the question and customer intent, then delivers the most relevant answer possible.
By implementing similar virtual assistant technology, Twitter can also ensure that customers no longer need to repeat themselves when trying to solve an issue. For example, if a customer is looking for additional information regarding shipping costs, they might ask, “How much is standard shipping for a $50 order?” As a follow-up, they can simply ask, “What about express shipping?” Remembering that the first question was inquiring about shipping costs for a $50 order, the chatbot can provide an accurate answer without the customer having to repeat information. The ability to drive contextual conversations with the help of AI and NLP is an important capability Twitter should look to provide on Direct Message to make it a seamless support channel.
Gaining better understanding of customers through analytics
Facilitating conversations through virtual customer assistants creates massive opportunities for brands to collect useful data. With many consumers already interacting with their favourite – and least favourite – companies on social media, businesses could certainly consider Twitter as a valuable resource for customer data. However, it could be a waste of time and data if the tools on the Direct Message platform aren’t designed to drive real-time insights that matter to brands.
This is where data analytics comes into play. Smart chatbots don’t simply gather pools of communications data. They go a step further and effectively analyse insights, helping brands gain an understanding of customers and their experiences. Since virtual customer assistants allow end-users to freely express themselves, asking questions and providing feedback in their own words, brands are presented with entirely new types of data to interpret. Organisations can effectively examine all this communications data to see what’s working and what’s not to close the gap between what they’re providing and what their customers demand. The ability to extract these valuable insights is what makes data analysis another core technology Twitter should include on Direct Messages.
Improving responses and offering updates in near-real time with knowledge management
When it comes to smart customer communications via virtual assistants, consistency is key. Another important technological feature Twitter must consider is the ability to easily manage and update virtual agent support information. Developing accessible knowledge management systems means brands can understand the kinds of questions their customers are most interested in, and pinpoint where their support might be falling short. From there, the brands quickly improve responses and make updates in real time.
This is particularly important for pertinent questions during a crisis. For example, if an ecommerce company recalls a popular product, questions that a brand might not have previously considered will start to roll in. Knowledge management systems can detect when there’s a high volume of questions around a particular topic or theme and immediately alert the company to update customer resources with the most accurate information. Without knowledge management capabilities on platforms like Twitter, social media managers will often handle inquiries on their own, which can result in differing responses or customer inquiries that just go unresolved. Ensuring the right answers are available to customers at the right time is crucial to a strong customer service platform. For newer channels like Twitter’s Direct Messages, implementing smart technology that allows companies to easily manage their knowledge-bases will be what really gets brands on board with using this platform for customer support.
Twitter could be the next big customer service channel. It’s already the place consumers go to post their opinions of brands and be heard. However, if the social media giant wants to be truly successful, it will first need to take a page from intelligent chatbots and start incorporating the innovative technologies that are driving smart self-service today.
Yaniv Reznik, Chief Product Officer and SVP of Customer Success, Nanorep
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