SAS for Customer Analytics & Real-Time Interaction Management: Q2 2022 Analyst Viewpoints
Over the last two years, brands continue to explore and stress-test new mechanisms in deriving actionable analytical insight. An emerging trend orbits around trust which is critical when using analytics effectively. This concept focuses on data/analytical literacy in how information is used to build models, accurate interpretation in models themselves, and confidence in an individual's own ability to use algorithmic scoring to make intelligent decisions. We are excited to announce that in the second quarter of 2022, SAS was recognized as a Leader in two influential reports released by Forrester Research relevant to the martech and business analytic industries. The two topics of research represent key themes behind SAS Customer Intelligence 360. Wait a minute. What does this have to do with marketing technologies? Allow me to focus your thinking.
It is encouraged to click on the reports below which provide readers free access to the research. The question I want you to consider after reviewing the content is:
Which software vendor has the strongest current offering across the totality of both research reports?
Forrester Wave(TM): Customer Analytics Technologies, Q2 2022
Forrester Wave(TM): Real-Time Interaction Management, Q2 2022
The hype of martech innovation in 2022 continues to soar, and every technology vendor is claiming to bolster the customer experience with machine learning & artificial intelligence. At the intersection of data, analytics, and marketing, detecting and acting on moments of significance between a brand and a customer matter. Is all AI built the same? No. Yet it seems every software vendor is pitching it. Let me be clear. It isn't enough to capture and store 1st/2nd/3rd/Zero-party customer data. Further, feeding this information into automated or custom prediction and segmentation models helps serve the marketer's mandate with accessible analytically-derived scores, but still falls short on potential.
Do you want to know what wedges separation for competitive advantage? Decisioning engines enhanced with model governance, AI bias detection and supervised/unsupervised/reinforcement/deep learning insights triggered by real-time customer behavioral events contextualized by forward-thinking CDP capabilities. Think CDPs with a DataOps and ModelOps enablement mentality. Lean in and look closely, and it becomes obvious that all AI is not built the same. Would you like a detailed example of what this means? Per the Forrester Wave(TM): Customer Analytics Technologies, Q2 2022 report:
"Perhaps most importantly, SAS delivers cutoff recommendations for propensity models to optimize a decision — for example, identifying which customers to contact to optimize conversions while minimizing costs."
The challenge for readers is clarifying what this actually looks like? Well, take a look here at a detailed presentation and demo on "Analytical Targeting" (the latest automated AI user feature released in SAS Customer Intelligence 360):
By leveraging SAS capabilities behind embedded functionality (or easy-buttons) within a marketer-centric designed user interface, the video above showed:
- End-to-end automation of the data science workflow.
- Champion-challenger modeling tournaments for propensity score optimization.
- The execution and ranking of machine learning pipelines across Lift, Gain, ROC, etc. to auto-assign treatment, exclusion and control groups to identify high-value audience deciles within SAS Customer Intelligence 360 targeting capabilities.
Moving on, remember when next-best-actions (NBA) were all the rage? Not anymore. Welcome to the era of next-best-experiences (NBX) expanding on the significant variance of approaches brands experiment with in personalizing products vs. offers vs. actions. Per the Forrester Wave(TM): Real-Time Interaction Management, Q2 2022 report:
"SAS differentiates by enabling its clients to fine-tune custom analytical models to ensure successful customer outcomes align with effective business operations. It applies its advanced analytics prowess to make NBX decisions for not only customer engagement but also operational use cases like risk and fraud management."
It's not enough to simply orchestrate a customer experience based on likelihood score or suppressions. We need to think bigger by activating and optimizing journeys using metrics like operational efficiency, profitability, and customer lifetime value (CLTV).You know where I'm going next. Let's exemplify transparently how SAS approaches decisioning during customer moments that matter. The storyline of this demo will be in a financial services context, and the next best experiences will highlight prioritization by expected customer value. We'll take this in two demo video steps. Let's begin with decisioning.
SAS Intelligent Decisioning provides user access to a comprehensive set of ModelOps capabilities. SAS recognizes the importance of removing friction to activating sophisticated decisioning in martech, and we are ecstatic to announce the release of our embedded decisioning connector within SAS Customer Intelligence 360 (July 2022 software release). Our vision is to provide brands with open access to rich digital data and sophisticated decisions using customizable business rules and real time analytical model calculations for timely insights and advanced personalization to accelerate conversions. Previously, users had to configure at least one agent in order to integrate with an external system. Now, the SAS Intelligent Decisioning native connector provides the ability to map SAS Customer Intelligence 360 data as inputs to published decisions through a no-code GUI.
With the connector configured, users can auto-trigger a decision based on customer behavioral events. Decision outputs are automatically made available to any SAS Customer Intelligence 360 supported channel/task (web, mobile app, email, etc.) for targeting and personalization. This feature enables users to exploit the advanced analytical capabilities of SAS Viya in SAS Customer Intelligence 360. For example, you can invoke a published decision based on a user action (pageview, click or micro-goal achievement). Then you can use the customer outcome of that targeted decision (such as a NBX recommendation) in a task or activity map for downstream personalization as that user's journey matures.
Per the Forrester Wave(TM): Customer Analytics Technologies, Q2 2022 report:
"SAS’s product roadmap emphasizes additional UI simplification — a request the company has heard loud and clear from its clients. From a functionality perspective, SAS continues to blaze a trail with cutting-edge analytics. It recently added interactive decision trees for propensity modeling, enabling users to overlay business rules on top of classification models to make algorithmic insights work in a business context."
That is exactly what readers can expect from SAS going forward. Identifying and expunging areas of adoption challenge to connect innovation from data science for practical use cases brands are energized to unleash. This is the perfect pivot to our second demo video that focuses on model management, governance, bias detection and design. If trust is critical when using analytics effectively, this is the moment in the ModelOps process where projects lift off for success, or crash.
Per the Forrester Wave(TM): Real-Time Interaction Management, Q2 2022 report:
"Its roadmap promises to further democratize customer understanding, intelligent decisioning, and journey management for people of all skill sets. That’s welcome news to customer references, who award SAS this study’s only perfect reference rating for a vendor’s roadmap..."
We look forward to what the future brings in our development process – as we enable marketing technology users to access all of the most recent SAS analytical developments.
Learn more about how SAS can be applied for customer analytics, journey personalization and integrated marketing here.
