AiThority Interview with Ya-Bing Chu, VP of Product at Formation

Could you tell us about your role and the team/technology you handle at Formation?

I’m the Head of Product at Formation. We’re building technology that is making offers and promotions more engaging, personalized, and effective.

What makes Formation’s AI-based Marketing Platform distinctly different from other platforms?

At the end of the day, we’re about building journeys. Most AI-based Marketing platforms are about next-best-actions. But these tools only incentivize one-off purchases. We want to build life-long behaviors. The way we do this is by creating offers that require the customer to take multiple related actions rather than just make a single transaction. Doing so helps establish and reinforce customer behaviors and, moreover, just leads to more engaging customer experience.

What is the current technology roadmap to build a powerful Experience-driven loyalty program?

Marketers are overwhelmed by the number of channels that customers now use, but you can’t afford to not have a presence on these channels. At the same time, it’s unsustainable to build out a technology roadmap for a loyalty program that requires companies to invest in developing a team and product for each of these channels. Marketers should start by creating pilot programs, evaluate what’s working and then put a stop to anything that isn’t seeing results.

The next big goal is to break down the barriers between loyalty and other Marketing programs. Marketing tends to be siloed by channel, and loyalty is often left out on its own because it requires a system of earning and redeeming currency. Brands that can unify their Marketing, and take smart risks to figure out what works, are well on their way to developing a powerful loyalty program.

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Why is Amazon still unbeatable in E-Commerce? What should other retail platforms do to compete better?

Amazon certainly excels at many things—price, convenience, selection—but these aren’t the only factors that go into a purchasing decision and they’re not unbeatable in e-commerce. Retailers have many tools in their Amazon arsenal—most importantly, the three “C’s”: Customization, Community, and Customer Experience.

MiAdidas, Adidas’s line of custom sneakers, for example, has been a huge success for the brand. Goop and Kylie Cosmetics have been successful not just because they’re celebrity-backed but because they’ve built real communities around their celebrity founders. Sephora’s success really turns on its excellent in-store experience, with its team of highly trained beauty consultants and in-store beauty services.

What are the various Personalization formats that you expect to further evolve for Retail and B2B?

Today, most Personalization is based on user data. This can be something as simple as retargeting or a Product recommendation—I know you bought a sweater, so I’m going to show you more sweaters or boots or a coat. But that’s really just the tip of the iceberg. What we’re really interested in is how we can match personalize something based both on the customer’s preference and the company’s objective—essentially creating a win-win situation for buyers and sellers alike. Finding that optimal moment where both the customer and the brand walk away happy is really the Holy Grail, and that’s certainly where our focus is.

Can Video platforms ever replace TV? If yes, how? If no, what are the possible outcomes? What is your forecast on Personalization for TV customers?

I think this TV-OTT distinction is quickly becoming outdated. TV is becoming just one of the many Video platforms consumers can choose from. It’s no surprise that in the next 12 months, each of the Big Three networks will have a full-blown, Netflix-like streaming service complete with original programming. Personalization for Video is really in its infancy. It’s essentially limited to Product recommendations—you watched this, so watch that. And we’ll certainly see more of that, upending the linearity of the television experience—the era of must-see (together) TV will soon be a thing of the past, dragons or no dragons. But the truly interesting question is what happens when Personalization intersects with storytelling.

Why do brands fail to fully understand real-time Customer Data Analytics? How do you train your focus to deliver these analytics better at Formation?

I don’t know that they fail to fully understand it, but I do think there’s this misconception that “real-time customer data analytics” is this all-or-nothing proposition. That’s where brands often get tripped up—thinking that their data has to be perfect before engaging in any sort of real-time, data-driven Marketing. The fact is that for every question you answer with data, it tends to open up 5 more questions because it often ‘depends’. And, achieving that outcome of centralized, clean data will be an expensive one and one that does not change business results by itself. Instead, taking a “detect and act” strategy would be more effective and affordable and can allow brands to focus on pragmatic customer-centric scenarios.

Could you tell us more about your AI and Machine Learning initiatives for Mobile Experiences?

We really believe in thinking about experiences from an Omnichannel perspective. We want to be where our customers are and connect with them on their terms. For mobile, we really wanted to move apps away from a transactional experience to an engaging experience. In other words, you usually only use a company’s app when you want to make a purchase, book a ticket, take a flight—but we want consumers to want to engage with the apps on a more regular basis. We want consumers to want to engage just for the sake of engaging, and so we’ve really tried to make that the priority in our mobile experiences.

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What are the biggest challenges in measuring the ROI of Mobile-focused Shopping? How do these compete with Video formats in the Search, Display and Programmatic environments?

These are very AdTech-focused metrics and give a pretty narrow slice of the total picture. One of the limitations of AdTech is that marketers end up caring much more about metrics that correspond to specific channels because things are very siloed—your pre-roll is separate from your display is separate from your paid social and so on. With Loyalty Marketing, you have this much richer picture because the customer is willingly sharing information about who they are, what they do, what they like and so you’re able to test things a lot more granularly.

What is your prediction on the disruptive application of AI-based Customer Data Analytics in B2B and B2C Marketing initiatives?

When it comes to Marketing initiatives, I think AI changes everything. Where we’re at today, even the best optimization algorithms can only optimize against known situations. At the end of the day, it’s A/B (C/D/E/F) testing. But AI can start testing for unknown situations—things that the marketer may not have thought of — and that opens up a whole world of options for marketers and loyalty.

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