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The rise in ecommerce and digital-first, contact-less customer journeys over the past year has been well documented. As we begin to emerge from the Covid-19 pandemic, the permanence of the drastically changed consumer behaviors will begin to take shape, and we will finally have a clearer picture of what the new normal looks like. One thing we can be certain of, however, is that it has become more of a challenge for marketers to connect with customers. In fact, according to a recent Prosper Insights & Analytics survey, the majority of consumers do not like when advertisers access their personal data for targeting purposes. Knowing this and given how dynamic and unpredictable customer journeys have become, marketers must think differently to be consistently relevant and reach consumers with the interactions and across the channels they prefer.
Prosper – Privacy Personal Data
Prosper Insights & Analytics
To better understand the challenges and opportunities that lie ahead for brands that even before the pandemic were faced with a daunting data overload, I spoke with Rob Fuller, the Managing Director of the Customer Data Orchestration group at Accenture. Rob has spent the last several decades working with companies on the intersection between marketing and technology and helping brands deliver transformative consumer experiences.
Gary Drenik: Rob, how does the Covid-19 pandemic add to the challenges that brands face for providing consistently relevant experiences?
Rob Fuller: I liken the personalization goal to the old-time shopkeeper example. If you walked into the store the week before Thanksgiving, the shopkeeper who knew you as a frequent customer would likely have a turkey set aside for you – and it’s the perfect size because he knows how many are in your household. He knows the desserts and side dishes you like, and that you’ll be rooting for the Dallas Cowboys that afternoon.
Brands always strive for that level of insight, but to achieve that same level of insight and create those interactions at scale for tens or hundreds of millions of customers at tens of thousands of locations – on channels that may not have even existed until recently – gets challenging.
Data helps us get to the level of understanding of the shopkeeper, but there are hurdles to clear. We have to track it, make sure it’s current, and map it to actual purpose to truly understand a customer’s behavior and give us the confidence that we’re deriving the right insight for a customer’s individual journey. But this can be difficult. In fact, in a survey from your company, Prosper Insights and Analytics, you found that respondents are split when it comes to sharing their personal information on connected devices. With over 40 percent of folks somewhat not willing or not willing at all to share data in this way, it is even more challenging given that connected devices are where most people are. The pandemic only adds to that complexity; with radically changed behaviors that can make it even more difficult for brands to create meaningful moments with customers. Customers themselves have also undergone personal change and displaying empathy for a customer’s situation can be an extremely powerful way to deliver a consistently relevant experience.
Prosper – Share Personal Data
Prosper Insights & Analytics
Drenik: Discuss some of the data challenges. The shopkeeper example resonates because it paints a vivid picture of today’s complexities compared with the old-school actual personal, face-to-face interactions.
Fuller: You’re right, when you contrast it in that way you quickly see that there’s a data overload problem. There are so many different parts that need to come together; marketers often don’t even know if they have the data, they need to create the moment or interaction they’re trying to deliver.
To answer that question, they need to determine the value of that moment, what form that moment should take, and how to measure it. The breadth of data available quickly becomes very large. There is also data governance to consider, as well as the need for marketers to align with brand and corporate objectives. What happens is that when the source of the data becomes abstracted, it becomes even more difficult to discern if data is fit for purpose – does it truly mean what you think it means, and is it actually representative of the moment you’re trying to create?
Data overload issues make it hard for marketers to plan a campaign, decide what they need and what will matter in terms of creating the perfect moment for a customer. To combat this increasing difficulty in discerning meaning from the customer data that’s available, we often see marketers requesting access to all the data with the notion that more is better – adding to the complexity. The better course of action is to decipher the data that we already have, figuring out the key indicators of purpose and what is relevant for an individual customer.
Drenik: You mentioned the issue of scalability and the challenge of creating relevant moments for tens or hundreds of millions of customers. Can you explain how machine learning tackles the scalability problem, and what are some common use cases?
Fuller: Machine learning fills both a reporting need and a transactional need. From a transactional standpoint, yes machine learning enables us to do things that would otherwise be too hard at scale, and to detect patterns that humans can’t detect. Because it continuously learns and gets better, machine learning can optimize existing touchpoints or the touchpoints a marketer is trying to create. It can optimize a specific moment and content in the moment of interaction.
As for reporting, machine learning does a good job indicating what types of content we may need more of – what opportunities we may capitalize on, but the content still needs to be created. By replacing value of certain moments, machine learning provides insight into which experiences provide value and where there are gaps in experience, which can then predict what content aspects will resonate the most and make predictions for what additional communications are needed – creating continual understanding and optimization of the customer journey.
Touchpoint optimization is an area we see many brands focus on. Many brands tend to over-communicate or under-communicate because they lack the ability to be consistently relevant. By using machine learning to predict coupons that are most relevant to a customer in the moment, or optimize which call center agent to rout a call to based on the totality of a customer’s behaviors up to the moment the call is routed, brands can quickly see an impact. Those are two good ways to get started, and generally produce crisp, undeniable results.
Drenik: What approach should brands take to advance their maturity level?
Fuller: Brands will have to start thinking about content in terms of data. From an analytical standpoint, to better predict a customer’s true purpose or intent, a sum total of behavior should include which images or words on a page the customer engaged with. Message analysis, too, will move past straightforward segmentation analytics to actually understand how a specific message resonates with a customer – and not just at the channel level, but its impact on the entire customer journey. To get there, we have to understand that content is data.
That’s the next level of maturity. Process, data, and channel siloes are the main barriers.
But when brands start to think in terms of the maturity model, they’ll quickly appreciate the need to form a single view of the customer. Cognitive personalization bases content on behavior – it is messaging not tied to moment or channel, but rather uses intelligent automation to understand a customer’s purpose.
Drenik: What role does technology play in helping to break through those siloes and begin to see results?
Fuller: To reach a level of sophistication that aligns with customer expectations for a holistic experience across dynamic customer journeys, having the right technology platform is a key component. Accenture’s CX group has partnered with Redpoint Global because the company’s rgOne platform uniquely delivers the level of perfect data integration needed to support the different types of communications and the marketing maturity model I alluded to.
Working with Redpoint, we’ve started to help clients layer existing, static experiences with innovative cognitive capabilities that optimize the experience for the customer – and ultimately strengthen loyalty for the brand.
The capabilities of a platform like Redpoint allow us to build the types of experiences that are generally too complex and costly to do via traditional approaches. Traditional approaches with heavy data integration needs, including integrating offline machine learning and analytics, can provide some of the same results but are more costly, rigid, and most importantly not available in the moment of customer interaction. Timing is mission critical in CX. The integrated platform’s inline, automated machine learning and real-time decisioning enables us to do things in the cadence of the customer and help bring up the overall marketing maturity level faster.
Drenik: What should brands be aware of in terms of what customer experience will mean in the years to come? Is urgency lacking for reaching that level of maturity that customers respond to?
Fuller: Delivering a personalized customer experience through an understanding of a customer and optimizing interactions used to be a differentiator that drove loyalty and lift. Now, it’s survival, particularly with the dramatic online shift and other pandemic-related repercussions.
The only way to provide consistently relevant experiences that move the needle is to derive them from a deep, personal understanding of the customer. Empathy and cognitive optimization are key to regaining that traditional shopkeeper view and the brand loyalty of the past, helping brands not only survive but thrive in this new environment where everything has changed.
Drenik: I want to thank Rob for taking the time to chat with me and offer insights on how brands can utilize technology to better personalize customer experiences.