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SAS Customer 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 in NZ, something that he offered to do earlier. Troy gave me some more insight into the concept and how SAS software does support filling it with life. It bases on the SAS Digital Intelligence and Personalization platform “SAS Customer Intelligence 360”. The purpose of SAS Customer Intelligence 360 is to allow businesses the creation of relevant customer engagements, based upon data, which result in better customer experience. SAS dubs it as “create relevant, satisfying, valued customer experiences”.
SAS Customer Intelligence 360 consists of two applications that sit on top of the SAS analytics system and support marketing by enabling functionalities for real time decisions, intelligent marketing and campaign management. These applications are named SAS 360 Discover and SAS 360 Engage, which allow for collecting data from digital interactions, to gain insight out of these interactions, and then use this insight to meaningfully engage with customers across web, chat, e-mail, and mobile apps. One can roughly say that SAS 360 Discover feeds the analytics engine and that SAS 360 Engage uses the analytics results.
Businesses can define and maintain data collection and normalization rules and, based upon these, assign personalization rules. Customer interactions get tracked using a simple enhancement of e.g. the web site or app code, which helps to build their profiles, first anonymous ones, where possible identifying and merging those technical profiles. This data gets aggregated in a data mart and can get further enriched with data that comes from other sources that the business has, like product information and information out of the CRM-, and other systems. This information then can get used for further engagement using the core strength of SAS, which is the strong analytics system.
This engagement is the job of the SAS 360 Engage application, which allows to combine messages and assets to marketing tasks, which get aggregated to customer journeys, called activities by SAS. This, again, is supported by SAS analytics capabilities, including predictive analytics and machine learning.
The overall system runs on AWS and is mandatorily designed as an open platform. Connectivity to the source systems is given by APIs and ETL functionalities.

My Take

It is good to see a traditional analytics vendor stepping up and helping their customers to build an integrated solution that allows them to take advantage of the treasure trove of data they are sitting upon. Customer engagement and customer experience being some of the hottest topics around make for a good showcase of this ability. Of course SAS offers solutions for decision management, fraud detection, risk management, too.
SAS makes a pretty compelling case by its ability to combine a, if not the, leading analytics engine with business logic. Analytics is a means to an end – a business end. This case is supported by an API approach and the statement of offering an open platform.
Having said this, the market that is covered by SAS Customer Intelligence 360 is a very competitive one. Business applications vendors like SAP, Microsoft, Oracle, and Salesforce – or Adobe – are trying to corner it, too. They might have less powerful analytics engines but they command a lot of the business logic, and the business knowledge. Then we have specialty vendors, of which I want to mention only Kitewheel and Thunderhead here. These companies excel in the disciplines of discovery and engagement and have analytics engines that are geared towards supporting their specialization, and they are offering out-of-the-box (OOB) integrations into major business- predominantly CRM systems.
Integration is an important topic. While offering APIs is key the message of having OOB integrations is very powerful.

Lastly, it is about messaging and philosophy. Looking at the ‘get started’ info graphic is telling here. The thinking is company centric, and not customer centric. With that, it needlessly limits itself. While there are mentions of the customer being ‘fickle’ it assumes that the customer journey can get pre-planned by the company, which is wrong. The company can offer a many of touch points, out of which the customer chooses the ones (s)he finds most convenient at any given point in time. The messaging sincerely is about talking to the customer instead of talking with the customer. Changing the messaging to an outside-in viewpoint and then further improving the solution from there could help SAS really stand out.

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