Yesterday, Loyalty360 CEO Mark Johnson connected with Ya-Bing Chu, VP of Product for tech supplier Formation, in an engaging webinar on the topic of marketing challenges in the age of the customer. From recent qualitative research, Loyalty360 has discovered that marketers in the current environment believe they face four significant challenges. These are harnessing data, anticipating customer needs, differentiating themselves, and adapting to changing customers. Johnson and Chu discussed these challenges and came up with some interesting insights.
First, Johnson pointed out that the main obstacles to harnessing data include data collection and management, data proliferation, and creating insights. Chu replied, “GDPR has made companies more mindful of data. They are looking at what data they need and what value they offer in exchange for that data. With these privacy regulations, they have to quickly and continuously provide value to the customer.”
Providing this value, however, isn’t always easy. “Driving insights and action from the data is really tough,” continued Chu. “Everyone has had an experience where the same data says different things to different people.” For this reason, Chu said that business goals and priorities have to be strictly defined.
He also discussed the concerns customers have about brands using their data. In fact, a recent study from FigLeaf suggests that customers believe that their data will never be safe when shopping online. Chu said the way to deal with this problem is loyalty programs: “We don’t need to use personally identifiable data, or PII, to create personalized experiences, but there’s an assumption out there that you would need to pass PII such as emails and other data to the vendor. The advantage with loyalty and retention marketing is that you keep this data in-house.”
Following up, Johnson asked a question we’ve seen surface over and over again in our conversations with senior-level brand representatives. “What’s the right amount of data?”
Chu answered, “The main pain point I see is how to prioritize the activation of data. We’ve seen a lot of companies who have trouble instituting a customer-centric mentality. One way to focus on it is to think about the customer lifecycle.”
Chu described a situation in which a brand has two customers, one who purchases once a week, and another that purchases once every three months. In this kind of situation, it doesn’t make sense, Chu said, to consider both churned after 60 days. This is where understanding customer lifecycles can help brands “activate data.”
On the topic of the next main challenge, anticipating customer needs, Johnson argued that brands must figure out ways to differentiate themselves from competitors so that they are part of a customer’s consideration set. From our conversations with brand representatives, Loyalty360 has found that customers want value and experience, hyper-personalization, frictionless experiences, and convenience. So, providing unique options within these categories should help brands stand out from the competition.
Chu said, “Brands are rapidly attempting to be more customer-centric. It’s all about the experience now.” To create these experiences, he said that technology can be a huge benefit. “Machine learning can automate so much with ease. It can set aside assumptions that don’t reflect reality. If you’re generating millions of variables for an offer, you can’t rely on your human team to do the job.”
However, Chu also stated that human teams do have to set up the right rules for machine learning to function properly. “You have to allow for business rules and manipulation,” he said.  He then described a situation in which a customer is planning an expensive, decadent picnic on a Saturday. “When is the right time to market to this person?” Chu asked rhetorically.
He wondered if the right time to market is Friday, the day before the picnic. If so, then the proper channel to market through is probably SMS, since many people don’t check their email after leaving work for the weekend. And certainly, Monday is too late. These are the kinds of issues that human teams have to think about correctly so that technology like machine learning can do its job.
On the topic of the third challenge, differentiation, Johnson said that, in the age of the empowered customer, brands have to “double-down on trust with the customer” to stand out. Chu agreed, but with one caveat. “It’s never been easier to start a company,” he said, “but it’s never been harder to differentiate and earn trust.”
He did offer a solution, however. He said, “How do you make rewards more achievable? It’s hard, since trust is way more complicated. Convenience is a little bit harder, and customers don’t want to come into a location to visit and talk with people they don’t know. This means you have to start curating things more, reframing things in an emotional context.”
Indeed, emotional connections and experiences are huge concepts in the industry right now, probably for good reason. Emotion does seem like an intuitive part of trust. If a customer doesn’t like a brand, or has negative feelings toward it, then trust will be difficult to come by. In this scenario, a brand will have differentiated itself, but in a way that will only hurt or hinder profitability.
On the topic of the final challenge, adapting to changing customers, Johnson said that many brands feel they have to use new technological innovations to gain an edge. However, Johnson also argued that many of them don’t understand how to do so, and they don’t know how to explain the ROI to executives. These obstacles have to be solved, however, because technology enables personal interaction with customers.
Chu added, “Tech allows you to automate, but how close are you to personalization? You can get there if you’re committed to low-risk pilots with vendors and you have partners that can help train you along the way. Giving your team the right incentives also helps.”
It seems, then, that this is a core issue surrounding changing customers: personalization. They want individualized content in the moment, on demand. This wasn’t always the case, but with exponential growth in technological capabilities, it is now. Fortunately, Chu said, “There are a lot of tools and vendors out there that can help, which is great, because there’s a lot to do.”

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