thomas.wieberneit@aheadcrm.co.nz
Forrester Wave CRM Suites for Mid-Sized Businesses – What it Means

Forrester Wave CRM Suites for Mid-Sized Businesses – What it Means

Finally, the much-anticipated Forrester Wave on CRM Suites for Mid-Sized Businesses Q4/2016 has been published by Kate Leggett and her team at Forrester Research. Besides the usual suspects Oracle, Microsoft, Salesforce, and SAP it covers 7 more vendors that fulfil Forrester’s definition of a CRM suite for mid-sized businesses. This definition roughly is To be considered a suite the software covers at least three of the CRM disciplines Marketing Sales Force Automation Customer Service Field Service E-Commerce Customer Analytics There needs to be prebuilt integration between the products, if they are not within the same system; integration shall be via open standards to allow for integrating other applications. The software needs to be targeted at organizations between 250 and 999 employees. Multiple industries need to be targeted. Of course, the solutions need to be in active use and there need to be customer references. The Forrester Wave has some interesting results, some confirming what other people see, too, others somewhat surprising. Let me start with the confirmations, continue with bits that surprised me, and close with an SAP specific view. The Confirmations Of course, we are talking cloud – cloud and nothing else. As can be expected all vendors strive to deliver a toolset that helps their customers to deliver consistent customer experiences. Now I, and others, would argue that the experience is largely in the realm of the end customer and the users and that there is nothing like a ‘system of experience’. Delivering consistent experiences encompasses far more than a CRM suite. But then it is far easier (and sexier) to talk about delivering experiences than about...
It is the Customer’s Way – Or No Way!

It is the Customer’s Way – Or No Way!

Today’s customer is impatient. They want – and have the right to – get answers to their questions and concerns about a company’s products and services without being in the need to preform lengthy searches or to dig around. This holds true for pre-purchase questions as well as to post-purchase questions. We regularly see or read statistics that tell us that customers are not very forgiving in cases of poor customer service, but on the contrary are inclined to leave when encountering a single instance of poor service. If customers do not get the answers to their questions without difficulties they are moving on, no matter of the company or its size. This meanwhile has become a kind of public domain knowledge. The only way for a company to avoid customers leaving with the first bad experience is by building up and maintaining a good and credible history of helping a customer with solutions to address their needs (aka jobs-to-be-done) and by regularly providing good customer service. At all stations of the customer journey. An important part of this good service is being available to help the customers on their preferred channels, at the time of their choosing, and at their pace. Theirs, not the company’s! This includes that a customer initiating a conversation, or engaging in a conversation that is initiated by a company, may not respond in a while, or chooses to continue using another device, or both. On the other side a customer will not accept the company being unresponsive or losing information during handovers between different service agents. The conversation between a company and a customer...
SAP and MachineLearning – A Strong Approach, but none too early

SAP and MachineLearning – A Strong Approach, but none too early

In my yesterday’s analysis of SAP’s HANA announcement, I wondered why SAP stays silent on the AI and MachineLearning frontiers. Well, today I know. They saved this announcement for today. And the announcement is a bang. SAP will deliver what they call ‘intelligent business applications’ that are based upon SAP’s new machine learning platform. The platform itself shall be made available with SAPPHIRE NOW 2017. The first significant intelligent application by SAP that is mentioned, is a brand intelligence application that leverages deep learning to analyze brand exposure in video and images to provide ‘accurate, real-time insights into sponsoring and advertising ROI”. You may remember that SAP earlier showcased an application to reduce recruiting bias, which is based on the machine learning platform, too. According to Juergen Mueller, Chief Innovation Officer at SAP, the new machine learning platform is intended to serve SAP’s and their ecosystem’s applications with the goal of creating more business value. Consequently, there are two more aspects to the announcement. SAP launched a partner program dedicated to SAP Application Intelligence. SAP invests into education offerings, starting with a ‘massive open online course’ on Enterprise Machine Learning on their OpenSAP platform. MyPoV This announcement clearly shows that SAP is as serious about machine learning as the company is about leveraging the power of its ecosystem. As I, and many other people, have often said, SAP is a formidable organization if and when it chooses to drive a topic. This is shown here again. And SAP is absolutely on the right track by pursuing this three-pronged approach of delivering a platform with first solutions, encouraging partners, and...
SAP HANA 2 – Revolution or Evolution?

SAP HANA 2 – Revolution or Evolution?

Yesterday SAP announced SAP HANA 2, an updated and improved version of its flagship product SAP HANA, and new SAP HANA microservices through SAP Hybris as a Service. SAP HANA 2 will be available for first customers on November 30 and an express edition shortly after its general availability. Note: if SAP talks about RTC this usually differs from General Availability, which is only after a successful ramp-up period of about 3 months to validate a product with early adopter customers. So the Express Edition will probably be released around end of Q1/2017. In usual bold marketing words SAP HANA 2 is poised to be a “new foundation for digital transformation” and is according to Bernd Leukert, member of the executive board, Products and Innovation at SAP SE, the continuation of “breakthrough innovation on a highly stable core data platform for our customers”. SAP HANA 2 shall deliver enhancements in the areas of database management, data management, analytical intelligence and application management as well as well as two more services for cloud customers: Text Analysis and Earth Observation Analysis. The latter in a beta status only. These latter two new HANA functionalities are likely to be the reason of tying the two announcements. The update cycle of HANA 2 shall be 6 months. Some Observations It is interesting that SAP refers to the new HANA services as microservices. This suggests that these services are built on top of the HANA 2 core – or else HANA itself has been rearchitected to be built on a microservice architecture. I rather think the former, also as the delivery is via YaaS....
Omnichannel – Myth, Reality or Utopia?

Omnichannel – Myth, Reality or Utopia?

Omnichannel – is it a Myth, Reality or Utopia? Over the past 20 or so years the way products and services get sold and customer service as well as marketing get delivered changed dramatically. Gone are the times where a potential customer was addressed via a radio- or TV-spot or an ad printed in a newspaper, advertising mail in the mailbox … – well, it still happens, but the focus shifted dramatically. We started off from one single ‘channel’ – customer goes to the store and interacts with a person – and added an ever increasing number of additional ones, like the ones mentioned, plus many more. For retail businesses the store will not go away. Generally spoken, human interaction will stay important, probably increase in importance; human customer service will not vanish – but is likely to change … please hold this thought. In today’s omnichannel world we also have telephone, e-mail, web-delivered ads, mobile apps, branded and white-label communities, social media like Facebook, Instagram, Twitter, etc., knowledge bases in combination with self-service, chat, messenger applications like WhatsApp, FB Messenger, Snapchat, iMessage; chat supported by ‘machine intelligence’, exposed via so called chatbots, and what not. The list could virtually go on and on. This is all supported by and implemented on a platform that leverages integrated applications, which work on a joint, or at least consistent data model – with clean data – utilizing strong real-time analytics capabilities that powers both, customer segmentation and knowledge categorization for efficient search. And it delivers a great customer experience. In Real Life Uhhm, I am just awaking from my dream …...