CRM Evolution 2015 was a very vibrant conference with lots of discussion that included a number of high profile industry influencers. For me as a first time attendee it was amazing how approachable many of these people are. But then this might come with the territory.
To understand these takeaways it is important to know that my reason for attending was getting into closer touch with what is going on in the CRM world outside SAP – and New Zealand. So, these are purely notes and thoughts that result from sessions, discussions with influencers, speakers and other conference attendees, and not learnings from vendor briefings. Also, this event was split into three separate conferences:
- CRM Evolution
- Customer Service Experience
I nearly exclusively concentrated on CRMEvolution and one session from the Customer Service Experience.
First things first: Was it worthwhile coming all the way from NZ? This is very clearly a yes. Paul Greenberg and the team did an amazing job in lining up interesting speakers.
What now are the topics that currently seem to move the industry in random order?
- Customer engagement (CEM), customer experience (CEX), customer journey (CJ) and how these topics relate to CRM
- Big Data, with a view on the Internet of Things IoT, and related to it: Predictive analytics
- How to do things CRM right
- Not surprisingly: The Future of CRM (technology as well as industry)
Also not surprisingly these are all interrelated.
CEM, CEX, CJ and CRM
The intersection of these three topics is extremely interesting. These are also controversially discussed topics. Paul Greenberg recently, in another “stake in the ground” article, gave current definitions of CRM, CEX, CRM, together with good rationales. I would like to not dive too deep into this topic for the moment and think that I will write down some more thoughts of my own soon. Only so much: A good customer experience and positive customer engagement rely heavily on relevancy. Relevancy is increased by addressing a customer/prospect with the right communication at the right time, using the right communication channel as well as the ability to consistently do it across all channels. I would call this channel agnostic, rather than omni channel.
Customer Journeys and their mapping are topics that still evolve, both from a vendor point of view but also looking at what analysts say. Of course customer journeys are handled differently in B2B and B2C scenarios. Mitch Lieberman presented the Sugar CRM implementation in a B2B scenario, which reminded me of the cross of a buying centre with an action plan, including predefined actions and communications channels for these actions that suit the corresponding stakeholder and the information. The idea is that a customer engagement happens best using the touch points suiting the customer representative best.
On the B2C side things are quite similar. Ray Wang sees customer journeys being mapped “intent driven”. This does basically mean to use all available data (i.e. Big Data, to use the buzz word) to figure out a user’s intentions and to construct touch points in a way that these intentions are already taken into account. This sounds like magic but is started to be put in place, e.g. in support scenarios. An example that came up in a later session is a telco that uses data as different as that gathered through a user’s web search activity, the status of her web router, browser, other users’ experiences, etc, to prioritise and suggest solutions – and this consistently through the diverse support channels.
This directly brings us to the next group of topics.
Big Data, Internet of Things, and Predictive Analytics
Big Data is probably last year’s big thing but the term still brings a point across. All of us are generating incredible amounts of data, structured as well as unstructured. One of my customers for example, a not so big retailer, sits on several tera byte of sales data, a treasure trove for targeted marketing. The amount of data is growing fast and thanks to this year’s buzzword: Internet of Things, which describes connected sensors that interact with each other, we with them and they with us, the pace of this growth will even explode. This amount and growth of data continues to be a challenge, although technology meanwhile allows intelligent near real time analysis of huge amounts of data. The good news is that IoT is creating structured data, but then all data that is generated via social media, including sentiments, is unstructured.
This is where Predictive Analytics, or Intent Analytics, kick in to support businesses in their customer engagement and CRM processes, and providing a satisfactory customer experience, which brings us back to the previous section. The telco in the example above uses the huge amounts of data that are generated via their touch points and applies predictive analytics “algorithms” on them to be able to help customers in case of a problem. This help will be offered via channels that are as different as chat, voice, IVR, the company web site. Of course this help also relies on a very good integration into their internal knowledge base that gets constantly updated so that the relevance of articles can get determined based upon all available data.
Other applications of Big Data- and Predictive Analytics are Oracle’s release of a social analytics engine that helps determining the priority of calls for help on social media (apparently based on the number of followers, e.g, who cries loudest gets better support …) or an energy grid provider’s ability to constantly analyse the status of its network with the ability to predict failures up to 8 days in advance. This is incredible useful for preventive action and the optimal planning of maintenance.
But back to the Internet of Things. We all are starting to carry around an increasing number of sensors. These sensors interact with us, we with them, and increasingly they with each other. It also leads to the development of platforms and APIs between platforms that increase the range of services that businesses can provide. Think of decades old scenarios like the your fridge ordering a refill of butter because butter is going to run short soon, or the current experiment of Amazon Dash, that essentially is a button that gets hooked up to your wifi network and does exactly one action: It orders a set product, which then gets delivered right to your house – maybe via a drone. Just be sure that the button is out of reach of your kids, or else you might get more washing powder than you can use in the next decade.
This interaction of sensors in combination with platform integration will allow the creation of services and experiences that we currently can only partly imagine. But I do not think that anyone has a clear vision of where this will lead, who will benefit of it (except the platform providers), how privacy can get maintained and what regulatory requirements are coming up.
CRM Done Right
This is a kind of eternal topic. Theoretically it is not that difficult to apply a number of seemingly common sense principles. Of course I need to acknowledge that every business and organisation has some constraints. Still it is really surprising – at least for me – how often simple principles like
- start with an end in mind
- iterate, have goals use small steps
- write it down and make it measurable
- foster an appropriate corporate culture
- get your processes straight
- provide the employees with what they need. CRM systems are not only for the management
are not applied. These are only the ones that were referred to most commonly at CRM Evolution but I think they paint a fairly complete picture.
Instead we still seem to see technically driven implementations that are intended to support management with more reporting and control capability and that do not yield positive results and lead to dissatisfaction. I think that this gets increasingly understood as being a problem, by businesses as well as by vendors, which is evidenced by user interfaces of these business systems getting more and more consumer grade and by an increasing ability of the software stacks to support little, targeted applets, either native ones or ones that are plugged in via an integration layer like REST.
The vendors getting their act done leaves the businesses in the hot seat. Without a strategy, a customer focused corporate structure and culture, and an implementation plan that is flexible enough to be regularly adapted to follow changing realities CRM implementations will continue to fail.
At this point let me bang my head against a wall once more: To me it still seems that CRM is a strategy, regardless whether the market has “agreed” upon calling it a technology. Technology doesn’t help. It is a tool, not more.
But now let us have a look into the Glass Ball.
The Future of CRM
CRM was pronounced dead by many pundits – multiple times. But it is still around and it is here to stay.
CRM evolved and it will continue to evolve. But what are the next evolution steps? What are the main drivers?
Main drivers that I see are
- an increasing need for real time decision making
- the necessity for companies to identify signals in a world with a lot of noise
- the necessity for companies to be relevant to their customers, to stand out in a world that has a lot of noise
I think that these will result in some main lines that will govern the next steps of this evolution:
- in the shorter term best-of-breed will continue to get stronger; we see it already now with many departmental and point implementations, many of them thanks to the cloud. In this respect we have gone full circle since the beginning of the nineties, from point implementations to suites, and back. This will be followed by
- platforms with open APIs, rather than suites. Platforms and ecosystems are already there. What is not yet there is real platform interoperability. This is still project work. In the future this should lead us to a world where business objects and -services that are provided by different providers can get easily combined to assemble end-to-end processes – or, hopefully not, to a world that has only one remaining platform. Hasso Plattner formulated this thought of free combination of business objects to processes at the end of the nineties (OK, limited to SAP products) and had SAP Business by Design built to follow this thought; these days Bob Stutz formulates it fully generic. And he is right. The CxM market is more than big enough.
- very, and I mean VERY, strong analytics capabilities that are directly (and automatically) actionable, driven by AI systems. These analytics capabilities support superior customer experience and superior customer engagement, which forms a kind of relationship between customer and business, whether the customer wants it or not. The customer engagement will be pre- and post-sale, always with the intention of making the next sale (the current buzz for this is “service is the new marketing”). It will happen on the “channel” that the customer prefers and have and use enough contextual information to provide relevant information, at the right time and place. To achieve this the analytics engines will be fed by both, structured and unstructured data, fed by numerous sensors and devices of sorts that we can only start to imagine now
- customer engagement will first become channel agnostic and then, depending on how IoT develops, device centric. This is where it gets really fuzzy. We just don’t know enough about this yet.