Loyalty Live: The Lacek Group on Infinite Personalization and How Artificial Intelligence (AI) Makes it Possible

Founded in 1993, The Lacek Group designs, builds, and maintains loyalty programs for top brands across the globe. As part of the Ogilvy network, the Lacek team converts disconnected tech stacks and processes into successful CRM programs powered by data-driven strategies. The company helps brands deliver relevant messaging at scale across channels to ensure connected, seamless experiences. The company works across a broad range of industries, including travel, financial services, hospitality, cruise lines, QSR, retail, automotive, health care, telecommunications, CPG, and more.
 
Loyalty360 spoke with Todd Hedberg, Senior Director of Digital Strategy at The Lacek Group. Hedberg has been with Lacek for just over three years and is still relatively new to the marketing side. He defines customer loyalty as an opportunity to strengthen customer bonds—both emotionally and transactionally—in every customer interaction. Hedberg and the Lacek team aspire to help clients achieve brand devotion with their customers.
 
In this article, Hedberg discusses working with clients to achieve deeper personalization, how artificial intelligence and machine learning fit into the equation, and going deeper to mine individual customer preferences.



 
Infinite Personalization and Artificial Intelligence (AI)
 
Lacek recently released its latest white paper, Infinite Personalization: AI Makes it Possible. Hedberg affirms there is much exploration into the big “what-ifs” and imaginative aspects of AI, noting it’s exciting to live in something that almost seems like a fantasy world.
 
“There’s a parallel path, though—practical applications,” begins Hedberg. “What’s realistic today, and what I’ve found exciting from a CRM and engagement marketing aspect, is the narrowing of the distance between those paths—that convergence.”
 
For Hedberg, infinite personalization is a view into not just the art of what’s possible from full utilization of AI marketing capabilities but also what’s realistic today. Much of what appeared to be fantastical only a year ago is becoming a reality. The overarching premise of infinite personalization is the possibility to create an individualized marketing communication plan for every recipient on a list.
 
This is not only from a content personalization aspect but also includes campaign delivery—the timing, cadence, and frequency of messaging. Hedberg explains that when both predictive and generative capabilities are considered, brands move from what Lacek views as a “mad libs” style approach to personalization.
 
Historically, personalization has involved dynamic content insertion—adding the customer’s name and recent purchase into a pre-built layout or a template. That has evolved into more modular templates, and that’s where Lacek has had a lot of success with deeper personalization for clients—i.e., key areas of templates are modified in real-time to meet the preferences of those clients.
 
“The possibility that’s put forth with infinite personalization is starting with a clean page that allows for reimagining each email or communication’s content and also the format, links, and style,” says Hedberg. “If a message recipient tends to scan and go right to the call the action, they prefer more imagery.”
 
If this is the case, messaging can be shortened, and more images can be included versus providing more copy for someone who prefers to read. Email and message formatting will be driven by individual preferences. Personalization will be based on recent actions and general substance and style preferences at scale.
 
“That’s the premise behind infinite personalization—the ability to take a blank page and apply a unique approach for every individual in a database to meet their specific preferences,” says Hedberg.
 
Of course, personalization at scale can be very challenging. Brands might struggle to understand how to put it into play in their organizations. They might also face resource constraints.
 
Hedberg believes the biggest opportunity for brands is to create a “data fusion” between their customer data and transactional history as well as customer engagement preferences. He points out that a customer data platform (CDP) can help brands understand how to best communicate with each individual and achieve customer preferences—making messages more timely and relevant.
 
“Whether that’s through a data cloud solution or their own in-house data lake, the opportunity to slice and dice that data in real-time—for segmentation or AI-driven personalization—is the great enabler of those possibilities,” says Hedberg.
 
Not only does the Lacek team explore the possibilities of infinite personalization, but they also adhere to a multi-step process to move toward that ambition. Hedberg shares that some brands are further along in the process and are actually putting infinite personalization into practice today. Still others are just getting started.
 
After completing the “data fusion” between customer data and transactional history and incorporating engagement preferences, Hedberg reports that the second step is ensuring that communications can be adaptive to evolving customer preferences and characteristics. This means looking at the traditional utilization of customer personas and evolving the understanding of personas to be less static and more dynamic. Brands need to recognize that people are a blend of multiple personas. They embody the attributes or characteristics of multiple personas—or they may fluctuate between different persona attributes over time.
 
That dynamic nature allows for content signals to be captured or engagement signals to be captured for content adaptivity.
 
“Another step is putting that insight into motion for each individual, not only adapting the content but also looking at more than the content personalization displayed on the surface level,” instructs Hedberg. “You need to look at timing and relevancy.”
 
AI and Machine Learning (ML)
 
While there may be some similarities between AL and ML, the key distinction factor for Hedberg is that these capabilities unlock new possibilities. A combination of the two and their capabilities play a huge role in delivering ongoing hyper-personalization for brands.
 
“It’s making sure that nobody has to be on the losing side of split tests and receive sub-par, sub-optimal outcomes,” explains Hedberg. “Testing deeper, doing it at scale, and going beyond what is typically in the bandwidth of small-to-medium-sized marketing teams. AI is the superpower that allows teams to do these things more quickly. With the right guidance and implementation from the human side, it can do it very precisely.”
 

 

Determining Metrics
 
As brands more deeply embrace artificial intelligence and its capabilities, they need to nail down the metrics (or methods) that they should be using to determine success. During Loyalty360 roundtable discussions with brand members, brand marketers have shared how metrics and KPIs may differ from those used in traditional analytics.
 
Hedberg acknowledges that the methods will differ greatly, but he doesn’t believe the core metrics to measure success change much.
 
“It will be exciting and important to measure success from incremental gains in those KPIs established when using this approach compared to methods of the past,” says Hedberg, citing Pizza Hut as an example.
 
The iconic pizza chain took its traditional testing efforts and then implemented ML, elevating the process and allowing for deeper and faster testing. This helped determine the incremental revenue that it drove from its efforts.
 
Improving Communication Processes
 
Hedberg offers advice to brands looking to increase the efficacy of their communication programs and processes.
 
“The principle of using connections through key insights for engagement marketing, based upon customer patterns or preferences, stays the same,” says Hedberg. “That should be the ambition. The ability to go deeper and mine individual preferences is really what should drive the pursuit of AI and ML.”
 
When implementing these capabilities, Hedberg recommends starting small and building gradually.
 
“Find some low-risk use cases,” he suggests. “Look at the background imagery of communications and how that can be tailored through ML and the AI implementation of that.”
 
What’s Next?
 
Hedberg really believes the industry is on the precipice of another great marketing renaissance. The more brands can truly deliver one-to-one personalization, the more brand efforts and ambitions will move forward in a positive way. Hedberg confirms that Lacek will continue to support its clients and help them take steps toward achieving richer personalization outcomes.
 
“Some of them are fired on that path, and others are just getting started,” finishes Hedberg. “There will always be a need to course correct and pursue new opportunities. From an engagement marketing aspect, we’re focused on increasing the outcomes of those interactions and driving brand devotion and deeper customer loyalty.
 
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Quick-fire Questions
  
What word or short phrase do you use to inspire others?
What if?
 
What is your least favorite word that others use?
Segmentation.
 
What excites you at work?
Turning possibilities into realities.
 
What do you find tiresome—at home or work?
Text messaging/IM messaging.
 
What book do you like to recommend to colleagues?
Fascinate, by Sally Hogshead.
 
What profession other than your own would you like to attempt?
I’m fascinated by behavioral science.
 
What do you enjoy doing that you don’t get to do often?  
Read.
 
Who inspired you to become the person you are today? 
In addition to my parents, I’m fortunate to have several lifelong friends.
 
What do you typically think about at the end of the day? 
Where to next? Or how do I make the upcoming trip as fun as possible?
 
How do you want to be remembered by your friends and family?
Considerate and thoughtful.
 

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