May 12, 2021

You don’t need us to tell you that the data world – and everything it touches, which is, like, everything – is changing rapidly. These trends are driving the opportunities that will fuel your career adventure over these next few years. At the heart of these trends is a massive wave of data being generated and collected by organizations worldwide. With this data we can shift our focus as analysts from explaining the past to predicting the future. And in order to do this, we need to spend less time doing the same things over and over and more time doing brand new things. And accomplishing all these changes will require us to work together differently than we do now 1. Bigger, Larger and Faster Data You’ve probably already heard the fact that every two years we, as humans, are doubling the amount of data in the world. This literally exponential growth of data is impacting analysis in some big ways: 2. Predictive Analytics The vast majority of time spent by the vast majority of today’s analysts is on understanding data collected in the past, often in the form of reports and dashboards. Those days are coming to an end. The data and tools now available are allowing analysts to go beyond just convincing someone to do something and instead to often just do it themselves. For example: 3. Automation Of Tasks Once upon a time, analysts built a model in Excel, and once a month or so, they exported the model to PowerPoint and send it to (or even printed it out for) the managers who relied on regular reports. Soon, there were too many reports, so maybe they used macros in Excel to automate the creation of reports. Or maybe they were lucky enough to have a dashboard program that had some automation functionalities built in. The future promises even more than this:

As the internet has grown so has folks’ tendency to chat instead of talk. Whether it’s booking an appointment at your local paediatrician or asking your boyfriend if he wants to go out for some pasta, people like texting. This is what chatbots want to capitalize on – People’s aversion to talking on the phone. Companies all over the world have embraced chatbots with open arms. They bring along with them a sense of humanity that no IVR can match. One of the reasons is the complete lack of any voice based interaction. While those beautifully sounding ladies on the IVR systems might be speaking correct English (or any other language(s)), they speak it with such robotic emotions that the only thing the person on the other end of the phone wants to do , is strangle themselves (or the IVR lady). A lack of direct human interaction allow chatbots to be much more than a computer program. Employing the help of mankind’s greatest asset – Imagination, chatbots can (almost) substitute for a real live human person on the other end. How to build an Intelligent Chatbot using AI Computer Scientists from all over the world are doing great work in making sure that chatbots can really feel like talking to another live human. Conversational Artificial Intelligence (the field of study that chatbots fall under) has seen tremendous progress in the last few years. Tech giants like Facebook, Google and Apple are constantly coming up with both highly valuable research papers as well as publishing user apps that at the same time is both showing off the work they have done as well as training their chatbots to become even better. However, this huge praise that Chatbots have come to receive has also muddled up the market. There is a huge different between a generic chatbot that can only choose between a set of responses and intelligent chatbot which try to make sense of the user’s chats and respond accordingly. If you are a business, you need the latter but chances are the agency you hired to develop you a chatbot is trying to fool you by giving a very cleverly disguised version of a generic chatbot. Here are 8 things that your intelligent chatbot MUST have : 1. Chatbot Carry an Intelligent Conversation A conversation is much more than saying yes or no. Moreover, the longer a conversation the more complex it gets. To carry an intelligent dialogue, the bot must be able to maintain the context of the conversation at all times. It also has to understand that natural conversations don’t always progress linearly – the bot must be able to process an unexpected reply and adapt to changes in the course of the conversation. 2. Build Contextual Engagement A smart chatbot has to understand who it is chatting with. In order to provide a truly personal experience, the chatbot has to know about the user’s interests, attributes and personal information – then tailor the conversation to fit them. The bot needs to provide content, advice, and offers that exactly fit the user. If all the information is generic, it will be shallow, unengaging, and in many cases, not very useful. 3. Leveraging Real-Time Transaction Data.  Connected with the need for contextual engagement, an intelligent chatbot must be able to access real-time insights on transactions. Without real-time data access and analytics, the power of artificial intelligence (AI) and contextual advice (either human-based or with chatbots) is limited. 4. Chatbot Can Reuse Existing Content To have a meaningful impact, it is crucial for the chatbot to be able to access content created and maintained in digital repositories across all channels. From digital ‘brochureware’ to FAQs, rules and regulations, and rate information, bots must be able to access and leverage this insight in real-time. 5. Build Deep Knowledge To build engagement, a chatbot needs to be able to provide advice, not just balances. Personetics believes bots need to be purpose-built – with deep knowledge on issues important to the customer. With PayPal supporting payments through Facebook Messenger, the bar transactions through the bot channel has been set and is being raised. 6. Work Seamlessly Across Channels  Customers expect a consistent experience across the digital landscape – online, mobile app, Facebook Messenger, Amazon’s Alexa, etc. A bot can not be a silo, but should be able to traverse across and between multiple channels. This may be a challenge for organizations who still can not achieve this within internal channels (mobile, branch, online, call center). 7. Get Smarter Over Time  An intelligent chatbot must get to know customers better through over time as more conversations and transactions take place. It must improve based on how a customer reacts to information and advice provided by the chatbot over time. 8. Anticipate Customer Needs Almost half of all chatbots are only used once. This happens when a bot experience does not meet exceed expectations. To get customers in the habit of conversing with your chatbot, it needs to proactively reach out to customers with information, insight, and advice – presented at the right time and place based on predictive analysis of individual customer needs.