Analytical Targeting & Interaction Optimization with SAS Customer Intelligence 360
Spanning across two distinct sections, in this article and video demonstration, we will cover:
- A brief introduction to SAS CI360’s capabilities for touchpoint orchestration across channels.
- Subsequently, it is a natural progression for brands to run optimization efforts through experiments, testing and segmentation to improve specific interactions with customers (and prospects).
- Finally, as new analytical techniques evolve and automation reduces the effort to leverage algorithmic scoring, CI360 enables users to execute supervised machine learning and action on the results of champion-challenger modeling pipeline-derived propensities to improve targeting intelligence on websites, mobile apps and more.
Regardless if your brand uses one or multiple solutions to orchestrate communications across touchpoints, there is an opportunity to optimize interactions with target audiences. The output of the insights derived from integrated marketing analytics specifically identifies which interactions across journeys deserve acute attention. It is within those meaningful interactions where the opportunity to optimize through recipes of experiment design comes into play. Within SAS, users can apply testing methodologies such as A/B/n testing, Multi-arm Bandit testing, and Multivariate testing. From sample size estimations and delivering creative messaging variants, to performance insights, segmentation and interpretable visualizations, embedded automation is infused in the software's features designed to support the desired agility of a marketer’s optimization efforts.
Figure 1: Analytical targeting
Building upon this, a special area to focus on is the intersection of experiments and testing with customizable (or DIY) machine learning. If your brand has the luxury of having a data science or customer analytics team within your ranks, then you may have already observed how this group is constantly wrangling, engineering and exploring data in a hands-on manner, as well as performing research with a variety of algorithms to improve their modeling fit of that information. This results in meetings with marketing teams to reveal insights that are exciting them. If they can tell you which milestone interactions of a customer experience are more meaningful to your conversion goals, then those are the specific areas of the consumer’s journey where tests should be prioritized and allocated to. But the insights don’t stop there…
A variety of behavioral attributes can be predictive of who has higher (or lower) likelihoods to meet conversion goals. Don’t you want to optimize the interactions where it’s going to truly matter within customer journeys? Furthermore, don’t you want to optimize the interactions with high likelihood segments to limit resource waste and increase targeting efficiency?
Figure 2: Conversions vs. efficiency
Before proceeding, the presence of a data science or customer analytics team is not a reality for some brands, and not a full stop solution for others. In the video demonstration below, we will highlight in detail how automation can assist in the challenge of targeting refinement without sacrificing considerations for meeting customizable objectives. Classification modeling, confusion matrices, classifier rules, cut off rates, and other analytical details represent an area of under-exploited potential in martech, and SAS is introducing a user experience that removes barriers in allowing brands to tap into the hype of ModelOps.
It's easy to recognize that every brand is customer obsessed, and each prospective interaction provides a potential opportunity to make an intelligent decision, deepen engagement and positively impact customer lifetime value. Analytical Targeting is the latest feature from SAS CI360 to automate the use of advanced machine learning enabled by the latest capabilities available from the SAS Viya platform. We are ecstatic to share with you how it works.
Learn more about how the SAS Platform can be applied for customer analytics, journey personalization and integrated marketing here.
