Executive Q&A with Anthony Chong, Founder, IKASI
Editor’s Note:
IKASI helps mainstream businesses leverage big technology to improve results. We published an article written by Mridula Saini, Chief Revenue Officer, “How AI Can Recession-proof Your Business” here. We reconnected with IKASI founder Anthony Chong to examine the challenge that every business has in deciding how much to invest in each individual customer. He explains how, in the current business landscape, artificial intelligence (AI) is revolutionizing the way companies conduct experiments across the organization and is fundamentally changing how marketers are uncovering untapped revenue.
Executive Interview
Wise Marketer (WM): AI is all the rage now but in practical terms, how can AI-powered database marketing revolutionize the way loyalty and rewards programs are conceptualized, executed, and measured, especially in the context of economic volatility and fluctuating consumer behaviors?
IKASI: AI is proving to be instrumental in how organizations interact with customers. AI aside, the trouble with most current consumer-based marketing efforts is that practitioners don't necessarily think about each of their customers on an individualized level, which is kind of ironic. Customers are the lifeblood of any business, and their lifetime value (LTV) and perceived risk are actuarial exercises determined with generalized formulas and grouping.
Consider what would happen if marketers were able to evaluate each customer and know exactly how much they should be investing and the exact triggers that will yield a specific result at an individual level. Now imagine knowing how much a customer is currently worth at every stage of their lifecycle. How is that worth changing? And how much individual investment should be spent to get more revenue/trips out of each person?
Even among large companies with millions of customers, this is not something they’ve been able to consider, until now. These are just some of the game-changing insights that AI-powered database marketing can provide and some of examples of how they are making a significant impact on profits and losses (PnL) and enable businesses to stay ahead of economic volatility and consumer fluctuations.
Today, we are seeing the early stages of this transformation. So, when we talk about AI-powered database marketing (and how it can be used to drive loyalty and rewards), this is where AI really shines. Brands may think they have all the data in the world, but the reality is that without the help of AI, there’s not a lot of personalization they can do with that data. By leveraging an AI system, marketers can figure out what the right size investment is for each customer.
Pricing is another focus area of AI-powered database marketing. Lyft, Uber, and Amazon experiment with pricing all the time, and they do it on an individual customer basis. Until now, this approach was only done by people with large data science teams. However, AI is changing the paradigm so that every company – even those that don't have a cadre of data scientists – can create experiments and offers down to the individual level.
WM: As businesses face mounting pressures from a disrupted economy, what AI-driven solutions can marketing leaders adopt to sustain and enhance the effectiveness of customer loyalty initiatives?
IKASI: There will always be disruptions to companies that are out of their control like inflation, a supply chain disruption, a competitor saturating the market with promotions, unforeseen trends, or even subtle changes in customer behavior. However, there are many other things that happen on a continuous basis that are really hard to manage. Either way, trying to figure out what's going on when the main mode of analysis is a year-on-year comparison makes it ineffective (and too late) to react. A lot happens over that time, so determining the cause and attempting corrections is hard. For example, did sales drop because inflation just went crazy or was it because of this supply chain disruption or both?
The most effective way to do this analysis is through simultaneous testing where, for part of your population, it's business as usual and, for another part of the population, you leverage AI to offer randomized tests under purview to see any relative changes. This way, when inflation comes around, or when there is a supply chain disruption that affects both the “business as usual” as well as the randomized group that you're testing, you can begin to isolate these types of effects.
This approach is the gold standard of measurement in many fields like science and medical studies. The difference with innovative AI solutions is that they make this kind of testing easier. It also helps to ensure this type of experimentation is distributed rather than just a one-off, incidental thing and that it doesn’t require huge amounts of human hours to conduct. AI empowers marketers to execute this type of activity on a continuous basis.
WM: How can marketing teams optimize loyalty experiences for customers and how are they using these programs to foster deeper engagement, ROI, and operational efficiency?
IKASI: The ability to determine things like personalized pricing is extremely important and can give marketers a huge competitive advantage. Organizations are adopting AI to support hyper-personalization, enabling them to understand individual preferences and incentives in real time so they can engage with customers in highly personal ways that foster loyalty.
Marketers using AI are also seeing meaningful changes in their market share. It's one thing to overcome any type of defection for a short period. but if that continues year-over-year, this compounding effect can have a lasting effect on the business as competitors figure out the optimal pricing strategies and ways to engage with the finite customer base that they're competing over. Businesses simply can’t afford to be on the slow end of disruptions and AI helps them overcome these challenges.
WM: As AI continues to be adopted, what are some of the lessons learned? How can marketing leaders stay ahead of their peers and what should they avoid?
IKASI: One of the biggest misconceptions is the notion that their data scientist teams or consultants can build these AI solutions themselves. AI requires a very particular skill set that prevents even some of the well-known consulting firms from being successful and/or being able to deliver a timely and effective solution.
When organizations become serious about leveraging AI, they must work with seasoned people otherwise the effort quickly becomes a waste of time and money. There are many instances where people investing in AI-powered solutions move the bottom line in months instead of years, but rarely do they do so using a custom-made offering.
WM: What do marketers need to know about these AI solutions?
IKASI: There are many different types of AI. To get the greatest value from an AI investment, marketers need to know what each type does, what they're good at, and what they are not. Once they have identified the problems, they believe will make a big impact, the next step is to understand the core competencies of available solutions.
Marketers also need to connect with team members to determine where they are repeating work unnecessarily or establishing micro teams that toy with one-off experiments that don't have much impact. AI is a different, albeit powerful, beast and is one that most internal teams and consultants are not yet equipped to handle.
WM: What are some misconceptions about AI replacing jobs and how should companies think about the future of their marketing organization?
IKASI: While no one can predict the future exactly, none of the organizations we've worked with have even remotely thought about starting to replace jobs, never mind specific functions or teams. In fact, it’s quite the opposite, as many are starting to double down on the areas that are making the most impact. They consider AI a force multiplier on the rest of the business, so the majority are investing more in AI, not less.
Don't get me wrong, there are certain types of AI that are oriented toward replacing jobs but, again, this is not the case for marketers or those responsible for generating profit, loyalty, and engagement. AI gives them the ability to act on their various ideas and then conduct experiments they never could have done before because it was either too ineffective or it would have taken massive amounts of hours.
Technology provides them with the ability to try things out now and see if different approaches would actually drive more traffic. Rather than one-off campaigns, we allow them to try hundreds of ideas which is why the people we help think AI is so transformative. The sky's the limit right now, as there are so many creative approaches that were locked away under this chasm of practicality. AI is making it possible for marketers to try, test, learn, and apply campaigns in ways that were previously impossible, And the best part of all is that we’re just getting started.
About the Author
Anthony Chong is CEO of IKASI, providers of an innovative self-learning platform powered by AI. IKASI specializes in hyper-personalizing engagement experiences for business and marketing professionals at the customer level, aiding them in enhancing their net revenue growth. For more information, follow them at www.ikasi.ai and on LinkedIn.
