- data activation. This reflects recognition that customer data delivers most of its value when it is used to personalize customer treatments. In other words, it’s not enough to simply assemble a complete customer view and use it for analytics. “Activation” means taking the next step of making the data available to use during customer interactions, ideally in real time and across all channels. It’s one of the advantages of a Customer Data Platform, which by definition makes unified customer data available to other systems. This is a big differentiator compared with conventional data warehouses, which are designed primarily to support analytical projects through batch updates and extracts. Conventional data warehouse architectures load data into a separate structure called an “operational data store” when real-time access is needed. Many CDP systems use a similar technical approach but it’s part of the core design rather than an afterthought. This is part of the CDPs’ advantage of providing a packaged system rather than a set of components that users assemble for themselves. CDP vendors exhibiting at the show included Treasure Data, Tealium, and Lytics.
- orchestration. This is creating a unified customer experience by coordinating contacts across all channels. It’s not a new goal but is standing out more clearly from approaches that manage just one channel. More precisely, orchestration requires a decision system that uses activated customer data to find best messages and then distributes them to customer-facing systems for delivery. Some Customer Data Platforms include orchestration features and others don’t; conversely, some orchestration systems are Customer Data Platforms and some are not. (Only orchestration systems that assemble a unified customer view and expose it to other systems qualify as CDPs.) Current frontiers for orchestration systems are journey orchestration, which is managing the entire customer experience as a single journey (rather than disconnected campaigns), and adaptive orchestration, which is using automated processes to find and deliver the optimal message content, timing, and channels for each customer. Orchestration vendors at the show included UserMind, Pointillist, Thunderhead, and Amplero.
Of course, it wouldn’t be MarTech if the conference didn’t also provoke Deeper Thoughts. For me, the conference highlighted three long-term trends:
- continued martech growth. The highlight of the opening keynote was unveiling of martech Uber-guru Scott Brinker’s latest industry landscape, which clocked in at 5,300 products compared with 3,500 the year before. You can read Brinker’s in-depth analysis here, so I’ll just say that industry growth shows no signs of slowing down.
- primacy of data. Only a few presentations or vendors at the conference were devoted specifically to data, but nearly everything there depends on customer data in one way or another. And, as you know from my last blog post, the main story in customer data today is the increasing control exerted by Google and Facebook, and to a lesser degree Amazon, Apple, and Microsoft. If those firms succeed in monopolizing access to customer information, then many martech systems won’t have the inputs they need to work their magic. That could be the pin that bursts the martech bubble.
- new privacy regulations. As Doc Searles (co-author of The Cluetrain Manifesto) pointed out in the second-day keynote , new privacy regulations also threaten to cut off the data supply of marketing and advertising systems, creating an “extinction level event”. Searles announced a “customer commons” that lets consumers share data on their own terms . It’s an interesting concept but I suspect few consumers will put that much work into personal data management.
My initial inclination was to agree with Searles about the implications of new privacy rules, but I’ve since adjusted my view. It’s just inconceivable that an economic force as powerful as Internet marketing will let regulations put it out of business. It's much more likely that companies like Google and Facebook will learn to work within the new regulations, which after all don’t ban personal data collection but merely require consumer consent. Surely firms with products that are literally addictive can gain consumer consent in ways that will satisfy even the most determined regulators. More broadly, big companies in general should be able to make the investments needed to comply with privacy regulations with minimal harm to their business.
Small businesses are another matter. Many will lack the resources needed to understand and comply with new privacy regulations. In other words, privacy regulations will have the unintended consequence of favoring big businesses – which can afford to find ways to comply – over small businesses – which won’t. Google and Facebook will spend whatever they must to protect their businesses, in the same way that auto manufacturers found ways to comply with safety and pollution regulations. Indeed, as the auto industry illustrates, the actual cost of compliance is likely to be slight and may even result in better, more profitable products. The impact on small businesses will be to push them to use packaged software – yes, including Customer Data Platforms – that have regulatory compliance built in by experts. The analogy here is with financial and human resources packaged software, which similarly provides built-in compliance with government and industry standards.
Of course, if Google, Facebook, and a handful of others take near-total control over access to customers, there won’t be much data for anyone else to manage. But it seems likely that companies will find ways around those toll booths, especially when dealing with customers who have already purchased their products. Ironically, this would return marketers to the situation that existed before the Internet, when data on prospects was limited but customers could be reached directly. That might put a small crimp in martech growth but would still leave plenty of room for innovation.
"Martech growth" - sprawl may be more accurate. I am surprised at the ratio of tech companies to potential buyers?
ReplyDeleteAnd when you expand - look at general AI -the list doubles or triples -
So what should a company buy? Of course it depends - but 'data activation' or embedding a combination of customer intelligence and business objectives (desired outcomes) per interaction, per channel, per segment, per life stage...should be a priority
And should a company buy anything? Or lease a service(s) - agency, CDP as a service?
ps
I am working on a external and internal listening hub and evaluating off label applications from ai vendors,machine learning and some of the 5200 referenced - - But I MUST HAVE THE ACTUATOR - https://medium.com/@VentureScanner/the-state-of-artificial-intelligence-in-six-visuals-8bc6e9bf8f32 considering the required integration, embedding with SFDC, triggering events, transactions, alerts, treatments, pricing, inventory across legacy systems.