thomas.wieberneit@aheadcrm.co.nz
Agent.AI – Customer Service with the AI Bot

Agent.AI – Customer Service with the AI Bot

Earlier in June I had the opportunity to talk to Barry Coleman, CTO of Agent.ai, an about 2-year-old company at the time of writing this. The company spun off of manage.com, a very different business that enable the delivery of in-app advertisements. In order to support this mission more and more, first internal, then external support capabilities were needed. At first they built chat functionality for internal and for support purposes. Then there was the question of how to efficiently provide 24/7 support. This resulted in giving birth to a bot structure that can help customer service agents in an assisting mode, called co-pilot mode, and an autonomous mode, called autopilot. And it gave birth to Agent.ai. Agent.ai’s mission is to enable “exceptional customer service for all”. While this mission is not particularly unique, their approach is. First, Agent.ai has built its customer service software around a machine-learning platform. Second, the company provides their solution without asking their clients for a huge upfront investment or the need to have of AI-proficient developers in house. Third, they wanted to avoid the pitfall of inflated expectations. With AI and machine learning being very hyped topics at the moment, this is a very valid concern. Going backwards through the objectives, Agent.ai opted for offering very specialized bots first. As there is no general AI yet, this is pretty straightforward. Specific, tightly framed topics are far easier to support with AI and exposed by bots than broader bodies of knowledge. For example, specializations include the handling of order inquiries or of support call closure surveys. The second objective was achieved by doing all...
SAS Customer Intelligence 360 – Turn Data into Experience

SAS Customer Intelligence 360 – Turn Data into Experience

A while ago Angela Lipscomb from SAS got in touch with me to get me introduced to SAS’s concept of a Customer Decision Hub. Their Customer Decision Hub is a solution concept that shall allow organizations to derive insights and to trigger actions from interactions with external parties, like customers based upon rules and the derived insights. A Customer Decision Hub e.g. orchestrates the determination of Next Best Actions, and allows responding to an incoming request in real time using analysis and decision logic. At the same time standard communications can get suppressed based upon the same set of rules. In other words, the Customer Decision Hub fosters customer engagement based upon inbound signals that get analyzed and processed through the organization. Why is this remarkable, I hear you asking? It is remarkable because SAS Software first of all is an analytics company with a strong reputation for enterprise analytics at the higher end of performance and price point. SAS describes itself on LinkedIn as “the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 70,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world the power to know®.” SAS is not a company that is widely known for being actively engaged in the customer engagement market (pun intended). So I was intrigued. And so should you be. Finally, a few days ago my somewhat erratic schedule allowed me to have a follow-up with Troy Kusabs of SAS Software in...
Customer Service – How to Turn a Poor Experience into a Positive One

Customer Service – How to Turn a Poor Experience into a Positive One

With mobile phones taking over our lives and conversational interfaces becoming ubiquitous there is certainly a new level of demand arriving at customer service centers. Customers do not accept a mediocre service experience anymore. With their smartphones they have the means to get to customer service with nearly no delay and they are certainly willing to use it. And they do it. In this situation customers are often already feeling some frustration or disappointment because they couldn’t achieve what they wanted to achieve in the first instance. They already had their taste of a suboptimal customer experience. Frustration, disappointment – customers’ negative emotions towards a brand have a corresponding negative impact on the business. Customers just might go buy somewhere else. After all, in times of smartphones this has become simpler than ever. The support center now has best chances to add the feeling of being disrespected and outright anger into the mix. Or it can create a feeling of relief, of being respected, valued, even some satisfaction; this in spite of having come into the need of asking for support. Here the service agents have the opportunity to create a positive customer experience out of a poor one – one that will overlay the negative one. Use Customer Service To Create Positive Emotions Which one is better for the company – and the company’s bottom line? The answer to this question is pretty obvious. Inmoment Research recently released a study that clearly established links between positive experiences and positive outcomes for a company. And this was not the first study finding that investing into positive customer experiences results...
AI and IoT at SAP – Yin and Yang

AI and IoT at SAP – Yin and Yang

During the 2017 SAPPHIRE NOW conference SAP told the stunned audience about how they connected some dots to create better value and more intelligent business applications for their customers. In essence SAP lifted the veil on how the company will go ahead with two technologies that will dominate the next years and that are ordinarily treated as different topics. But which, in essence, are like yin and yang. I talk about AI and machine learning on one hand, and IoT on the other. SAP has been fairly quiet on the former and fairly vocal on the latter, although the first announcement was about machine learning powered intelligent business applications, back in November 2016. At that time SAP announced the availability of the machine learning platform for SAPPHIRE NOW 2017. After this, SAP announced SAP Leonardo, the bundling of their IoT portfolio back in January 2017. On day 1 of SAPPHIRE NOW SAP delivered on the November promise by announcing “it’s time for machine learning to take the work out of your work flow. It’s time for billions of devices to go from thinking, to doing. It’s time for SAP Leonardo, the SAP system for digital innovation.’ With this approach they even go beyond only connecting two technologies but they also add Blockchain, Big Data, Data Intelligence and Analytics into one single platform. Whereas one could argue that Big Data, Data Intelligence and Analytics are essentially the same. With this powerful combination, as Holger Mueller, Principal Analyst of Constellation Research, aptly observed, ‘technology for the first time can do more than business best practices want’. To accommodate for this, SAP...
CRM evolution 2017 – Customer Experience via AI

CRM evolution 2017 – Customer Experience via AI

Just on may way back from CRM evolution 2017 it is time for a little recap. The conference, once more chaired by CRM Grandmaster Paul Greenberg, was again co-located with sister conferences Customer Service Experience and Speechtek. Why there is a separate – and smaller – conference for Customer Services co-located with a CRM conference is beyond me, as Customer Service is an integral part of CRM. But be it as it is. CRM Evolution attracted around 500 professionals, being second to Speechtek. The main topics this year seemed to be Customer Engagement, Customer Experience, and AI, nothing of this coming as a surprise. The size ratio of the conferences and the topics were also confirmed by the exhibitors in the Customer Solutions Expo. We saw an abundance of little booths with AI- and bot-vendors. The mainstays of CRM had fairly small presences, notably SugarCRM, which had a big presence last year. Both keynotes dealt with delivering to maximize customer experience and to measure the result. In the opening keynote Gerry McGovern answered the question what great customer experience is in a digital world and then how to measure it. His premise is that customers want to get something done and that it therefore is imperative to help them getting it done as fast and easy as possible. That begins with page load times, goes on with simple check-out processes like Amazon’s famous one-click or Uber’s payment process – hint there is none at the end of the ride. Things are as easy as saying good-bye to the driver and opening the door. Throughout his keynote Gerry made the...