thomas.wieberneit@aheadcrm.co.nz
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...
Experience requires Engagement – Are Companies Prepared?

Experience requires Engagement – Are Companies Prepared?

Today’s businesses are in a difficult situation. Their customers demand more experience and contextually relevant engagements than they are equipped to deliver. This places them on a difficult trail that they need to navigate in order to be and stay successful. Their challenge is that technology does help everyone, especially their customers, because, also thanks to the consumerization of technology, it is far easier and cheaper for customers to implement and use technologies. Good technology examples of the past decade include the meteoric rise of messaging services and, before that, social media. As a consequence of this today’s customer is less depending on company marketing- or sales organizations and has a far higher reach when it comes to satisfying an information need. Consequently, Google finds that a whopping 99.8 per cent of all online ads are simply … ignored. Sales representatives are on the verge of becoming irrelevant. An increasing number of studies find that customers contact a sales representative only after a product decision has been made. This was a topic that was already discussed during CRM evolution 2016. Other studies determine that customers are abandoning shopping carts already following a single poor service experience. While these studies often are commissioned by vendors there still are too many of them to not indicate that there is a problem. After all there is bound to be a fire where there is smoke. The 1990’s customer was happily working with and believing in corporate messaging that got delivered via unidirectional channels like TV, radio, or the newspaper. Today’s customer uses available technologies and is always online, digitally connected and socially...
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...
eCommerce is Dead! Long live iCommerce!

eCommerce is Dead! Long live iCommerce!

My new column article on how to take advantage of AI and MachineLearning in eCommerce is live on CustomerThink. It gives you background and actionable information, answering pressing questions like ‘Where does AI come into the picture’? Not wanting to spoil, here a little hint: There is far more than merely product recommendations. But read for...
Tenacity – Improving Customer Experience by bettering Employee Experience

Tenacity – Improving Customer Experience by bettering Employee Experience

Following some of my posts on AI in customer service environments I got contacted by Daniel Doctor from Tenacity who invited me for a chat with Ron Davis, the founder and CEO of the company. Which I had. And it was an interesting conversation. In my articles I spent a lot of time focusing on how AI, machine learning and chatbots can help improving both, the customers’ and the service agents’ experiences by making sure that all relevant data is collated and available, reducing wait times for customers, being able to already suggest good solutions to both, customers and agents, and so on. The objective is at all times to have the customer get a good solution as frictionless as possible and to enable the service agent to concentrate on the hard jobs. The idea behind this approach is that it reduces customer irritation by having the answer faster and improves the agent situation by making the work more attractive. After all, who of us loves dull, boring and repetitive work. Not many, I bet – certainly not I. Of course, this is only half of the truth. Service agents, like all employees also react strongly on who they work with, who they work for, whether they have the right tools at hand to get their job done, how their stress levels are, whether their private lives are untroubled, whether they have enough sleep, and so on. Additionally, the more interesting situation of the dull jobs being taken care of by the machine creates stress, as the customers tend to already have an elevated level of frustration that was...