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Published On: October 18, 2021
In our last post on Data, we highlighted our White Paper, The Present and Future of Restaurant Personalization, which explores how this industry has evolved and begun to adapt to a new reality: more readily available information on your customers and their behaviors than ever before. A key framework from this highly collaborative work is The 3D Model: a tool to help make sense of this new reality and guide your journey down the path towards guest personalization at scale.
The 3D Model
Today our topic is the second D: Decisioning – and the central role it plays in developing and implementing personalization at scale. Dialogue with customers has been around long before the days of “Mad Men.” Data has existed just as long, having taken a big step forward with the introduction of the computing and data processing. The new and critical piece that makes the 3D Model really work is Decisioning. Decisioning necessitates the other two D’s evolve in a way that supports the Decisioning and not the other way around.
Capturing data on your customers and better understanding their behaviors offers up more ways than ever to customize or personalize your communications with them. All of this data gives you options, from which you must now make decisions! This new future opens the door to using advanced analytics to develop decision logic and algorithms whereby restaurants can break down guest profiles to decide what offers, prices, and messages to serve to each customer. Your customers are all different — why message them like they are all alike? Personica can assist and in many cases automate these decisions to optimize your level of personalization, which will increase open rates, engagement, offer redemption and ultimately increase Customer Lifetime Value (LTV).
When creating a machine learning-driven decision engine, defining what makes a high-value customer is crucial. Once a brand identifies its KPIs, these can be linked to customer behavior goals that enable customer scoring. These scores can then be used to segment and target customers, whether with a surprise and delight reward for a frequent visitor, or a win-back campaign for a lapsed guest. Here there are numerous ways, or Journeys, in which your brand can engage with customers.
Most programs segment members into targetable groups based on factors like visit frequency and key items ordered. With more data and AI-driven marketing automation, marketing and loyalty programs will evolve from segment-level personalization to 1:1 communication rooted in, and automatically triggered by, individual transaction data. The first step in this segmentation process is finding scaleable niches big enough to pursue. For instance, when a customer is classified as vegetarian (either by declared or inferred data) and visits the Panera website, they see the “hidden menu” of vegetarian items that are customized versions of products on the main menu. With Personica, your brand can replicate these types of segmentations just like the largest brands in the industry.
Reporting & Measurement
A decision engine can only learn through rigorous testing. A system that supports A/B/Control testing, tracking, and measurement is key in determining which recommended actions are most valuable. This testing can be applied to any set of variables a brand wants to test, from campaign subject lines and images to price and menu customizations.
The Bottom Line
With Data comes Decisioning. Evaluating your customers and segmenting them will allow you to create unique and in many cases automated messaging that will engage them with personalized communications to guide and inform them along their journey – – helping create more frequent and loyal guests. Decisioning is critical but doesn’t need to be intimidating. Personica can guide you along this path and help you with your efforts. Reporting and measurement will help you optimize these efforts as you learn, thereby providing greater engagement and personalization at scale.
Contact us to learn more. We look forward to hearing from you.
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